TCC_ PUC MINAS.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TCC CIÊNCIA DE DADOS E BIG DATA - PUC MINAS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Dados a serem trabalhados\n",
    "###### PC-MG: https://dados.mg.gov.br/dataset/violencia-contra-mulher/resource/f2957178-7f1d-4890-84af-a2aeb5e603fb \n",
    "###### IBGE: https://www.ibge.gov.br/cidades-e-estados/mg.html"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tratamento de dados - PC CIVIL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importação das bibliotecas\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import plotly.express as px\n",
    "import seaborn as sns\n",
    "import seaborn.objects as so\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "from sklearn.cluster import AgglomerativeClustering\n",
    "from sklearn.cluster import DBSCAN\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Leitura do csv - Base da Polícia Civíl de Minas Gerais\n",
    "df_pc = pd.read_csv('violencia_domestica_2022.csv', sep =\";\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>municipio_cod</th>\n",
       "      <th>municipio_fato</th>\n",
       "      <th>data_fato</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "      <th>risp</th>\n",
       "      <th>rmbh</th>\n",
       "      <th>natureza_delito</th>\n",
       "      <th>tentado_consumado</th>\n",
       "      <th>qtde_vitimas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>310010</td>\n",
       "      <td>ABADIA DOS DOURADOS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>10º Departamento - Patos de Minas</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>310020</td>\n",
       "      <td>ABAETE</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>7º Departamento - Divinópolis</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE-CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE-CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>310090</td>\n",
       "      <td>AGUAS FORMOSAS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>15º Departamento - Teófilo Otoni</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101867</th>\n",
       "      <td>317090</td>\n",
       "      <td>VARZELANDIA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>11º Departamento - Montes Claros</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101868</th>\n",
       "      <td>317120</td>\n",
       "      <td>VESPASIANO</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>3º Departamento - Vespasiano</td>\n",
       "      <td>2) RMBH (sem BH)</td>\n",
       "      <td>ATEND. DENUNCIA INFRACOES CONTRA MULHER(VIOLEN...</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101869</th>\n",
       "      <td>317130</td>\n",
       "      <td>VICOSA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101870</th>\n",
       "      <td>317200</td>\n",
       "      <td>VISCONDE DO RIO BRANCO</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101871</th>\n",
       "      <td>317220</td>\n",
       "      <td>WENCESLAU BRAZ</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>17º Departamento - Pouso Alegre</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>101872 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        municipio_cod          municipio_fato   data_fato  mes   ano  \\\n",
       "0              310010     ABADIA DOS DOURADOS  2022-01-01    1  2022   \n",
       "1              310020                  ABAETE  2022-01-01    1  2022   \n",
       "2              310030              ABRE-CAMPO  2022-01-01    1  2022   \n",
       "3              310030              ABRE-CAMPO  2022-01-01    1  2022   \n",
       "4              310090          AGUAS FORMOSAS  2022-01-01    1  2022   \n",
       "...               ...                     ...         ...  ...   ...   \n",
       "101867         317090             VARZELANDIA  2022-12-31   12  2022   \n",
       "101868         317120              VESPASIANO  2022-12-31   12  2022   \n",
       "101869         317130                  VICOSA  2022-12-31   12  2022   \n",
       "101870         317200  VISCONDE DO RIO BRANCO  2022-12-31   12  2022   \n",
       "101871         317220          WENCESLAU BRAZ  2022-12-31   12  2022   \n",
       "\n",
       "                                     risp               rmbh  \\\n",
       "0       10º Departamento - Patos de Minas  3) Interior de MG   \n",
       "1           7º Departamento - Divinópolis  3) Interior de MG   \n",
       "2             12º Departamento - Ipatinga  3) Interior de MG   \n",
       "3             12º Departamento - Ipatinga  3) Interior de MG   \n",
       "4        15º Departamento - Teófilo Otoni  3) Interior de MG   \n",
       "...                                   ...                ...   \n",
       "101867   11º Departamento - Montes Claros  3) Interior de MG   \n",
       "101868       3º Departamento - Vespasiano   2) RMBH (sem BH)   \n",
       "101869     4º Departamento - Juiz de Fora  3) Interior de MG   \n",
       "101870     4º Departamento - Juiz de Fora  3) Interior de MG   \n",
       "101871    17º Departamento - Pouso Alegre  3) Interior de MG   \n",
       "\n",
       "                                          natureza_delito tentado_consumado  \\\n",
       "0                                          LESAO CORPORAL         CONSUMADO   \n",
       "1                                                  AMEACA         CONSUMADO   \n",
       "2                                          LESAO CORPORAL         CONSUMADO   \n",
       "3                                 VIAS DE FATO / AGRESSAO         CONSUMADO   \n",
       "4                                                  AMEACA         CONSUMADO   \n",
       "...                                                   ...               ...   \n",
       "101867                                     LESAO CORPORAL         CONSUMADO   \n",
       "101868  ATEND. DENUNCIA INFRACOES CONTRA MULHER(VIOLEN...         CONSUMADO   \n",
       "101869                                             AMEACA         CONSUMADO   \n",
       "101870                                     LESAO CORPORAL         CONSUMADO   \n",
       "101871                            VIAS DE FATO / AGRESSAO         CONSUMADO   \n",
       "\n",
       "        qtde_vitimas                                                                  \n",
       "0                                                     1.0                             \n",
       "1                                                     1.0                             \n",
       "2                                                     1.0                             \n",
       "3                                                     1.0                             \n",
       "4                                                     1.0                             \n",
       "...                                                   ...                             \n",
       "101867                                                1.0                             \n",
       "101868                                                1.0                             \n",
       "101869                                                2.0                             \n",
       "101870                                                1.0                             \n",
       "101871                                                1.0                             \n",
       "\n",
       "[101872 rows x 10 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(df_pc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "natureza_delito\n",
       "AMEACA                                                28997\n",
       "VIAS DE FATO / AGRESSAO                               20155\n",
       "LESAO CORPORAL                                        16874\n",
       "DESCUMPRIMENTO DE MEDIDA PROTETIVA DE URGENCIA         5570\n",
       "ATEND. DENUNCIA INFRACOES CONTRA MULHER(VIOLENCIA      3444\n",
       "                                                      ...  \n",
       "FRUSTRA DIREITO ASSEGURADO NA LEI TRABALHISTA             1\n",
       "ATENDIMENTO DE DENUNCIA DE INFRACOES ENVOLVENDO AR        1\n",
       "CONCORRENCIA DESLEAL                                      1\n",
       "CRUELDADE CONTRA ANIMAIS                                  1\n",
       "FRAUDE PROCESSUAL                                         1\n",
       "Name: count, Length: 188, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Verificação de qual natureza de delito há maior frequência\n",
    "df_pc[\"natureza_delito\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Seleção das três maiores naturezas de delito:Lesão corporal, ameaça e vias de fato / agressão\n",
    "\n",
    "df_pc = df_pc[df_pc['natureza_delito'].isin(['LESAO CORPORAL', 'AMEACA', 'VIAS DE FATO / AGRESSAO'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>municipio_cod</th>\n",
       "      <th>municipio_fato</th>\n",
       "      <th>data_fato</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "      <th>risp</th>\n",
       "      <th>rmbh</th>\n",
       "      <th>natureza_delito</th>\n",
       "      <th>tentado_consumado</th>\n",
       "      <th>qtde_vitimas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>310010</td>\n",
       "      <td>ABADIA DOS DOURADOS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>10º Departamento - Patos de Minas</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>310020</td>\n",
       "      <td>ABAETE</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>7º Departamento - Divinópolis</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE-CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE-CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>310090</td>\n",
       "      <td>AGUAS FORMOSAS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>15º Departamento - Teófilo Otoni</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101866</th>\n",
       "      <td>317070</td>\n",
       "      <td>VARGINHA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>6º Departamento - Lavras</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101867</th>\n",
       "      <td>317090</td>\n",
       "      <td>VARZELANDIA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>11º Departamento - Montes Claros</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101869</th>\n",
       "      <td>317130</td>\n",
       "      <td>VICOSA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101870</th>\n",
       "      <td>317200</td>\n",
       "      <td>VISCONDE DO RIO BRANCO</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101871</th>\n",
       "      <td>317220</td>\n",
       "      <td>WENCESLAU BRAZ</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>17º Departamento - Pouso Alegre</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66026 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        municipio_cod          municipio_fato   data_fato  mes   ano  \\\n",
       "0              310010     ABADIA DOS DOURADOS  2022-01-01    1  2022   \n",
       "1              310020                  ABAETE  2022-01-01    1  2022   \n",
       "2              310030              ABRE-CAMPO  2022-01-01    1  2022   \n",
       "3              310030              ABRE-CAMPO  2022-01-01    1  2022   \n",
       "4              310090          AGUAS FORMOSAS  2022-01-01    1  2022   \n",
       "...               ...                     ...         ...  ...   ...   \n",
       "101866         317070                VARGINHA  2022-12-31   12  2022   \n",
       "101867         317090             VARZELANDIA  2022-12-31   12  2022   \n",
       "101869         317130                  VICOSA  2022-12-31   12  2022   \n",
       "101870         317200  VISCONDE DO RIO BRANCO  2022-12-31   12  2022   \n",
       "101871         317220          WENCESLAU BRAZ  2022-12-31   12  2022   \n",
       "\n",
       "                                     risp               rmbh  \\\n",
       "0       10º Departamento - Patos de Minas  3) Interior de MG   \n",
       "1           7º Departamento - Divinópolis  3) Interior de MG   \n",
       "2             12º Departamento - Ipatinga  3) Interior de MG   \n",
       "3             12º Departamento - Ipatinga  3) Interior de MG   \n",
       "4        15º Departamento - Teófilo Otoni  3) Interior de MG   \n",
       "...                                   ...                ...   \n",
       "101866           6º Departamento - Lavras  3) Interior de MG   \n",
       "101867   11º Departamento - Montes Claros  3) Interior de MG   \n",
       "101869     4º Departamento - Juiz de Fora  3) Interior de MG   \n",
       "101870     4º Departamento - Juiz de Fora  3) Interior de MG   \n",
       "101871    17º Departamento - Pouso Alegre  3) Interior de MG   \n",
       "\n",
       "                natureza_delito tentado_consumado  \\\n",
       "0                LESAO CORPORAL         CONSUMADO   \n",
       "1                        AMEACA         CONSUMADO   \n",
       "2                LESAO CORPORAL         CONSUMADO   \n",
       "3       VIAS DE FATO / AGRESSAO         CONSUMADO   \n",
       "4                        AMEACA         CONSUMADO   \n",
       "...                         ...               ...   \n",
       "101866  VIAS DE FATO / AGRESSAO         CONSUMADO   \n",
       "101867           LESAO CORPORAL         CONSUMADO   \n",
       "101869                   AMEACA         CONSUMADO   \n",
       "101870           LESAO CORPORAL         CONSUMADO   \n",
       "101871  VIAS DE FATO / AGRESSAO         CONSUMADO   \n",
       "\n",
       "        qtde_vitimas                                                                  \n",
       "0                                                     1.0                             \n",
       "1                                                     1.0                             \n",
       "2                                                     1.0                             \n",
       "3                                                     1.0                             \n",
       "4                                                     1.0                             \n",
       "...                                                   ...                             \n",
       "101866                                                1.0                             \n",
       "101867                                                1.0                             \n",
       "101869                                                2.0                             \n",
       "101870                                                1.0                             \n",
       "101871                                                1.0                             \n",
       "\n",
       "[66026 rows x 10 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tentado_consumado\n",
       "CONSUMADO    65473\n",
       "TENTADO        553\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quantidade de fatos consumados e tentados, sobre os três delitos selecionados\n",
    "df_pc[\"tentado_consumado\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Exclusão de dados que contém fatos tentados, mantendo somentos os fatos consumados\n",
    "df_pc = df_pc[df_pc['tentado_consumado'].isin(['CONSUMADO'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>municipio_cod</th>\n",
       "      <th>municipio_fato</th>\n",
       "      <th>data_fato</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "      <th>risp</th>\n",
       "      <th>rmbh</th>\n",
       "      <th>natureza_delito</th>\n",
       "      <th>tentado_consumado</th>\n",
       "      <th>qtde_vitimas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>310010</td>\n",
       "      <td>ABADIA DOS DOURADOS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>10º Departamento - Patos de Minas</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>310020</td>\n",
       "      <td>ABAETE</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>7º Departamento - Divinópolis</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE-CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE-CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>310090</td>\n",
       "      <td>AGUAS FORMOSAS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>15º Departamento - Teófilo Otoni</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101866</th>\n",
       "      <td>317070</td>\n",
       "      <td>VARGINHA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>6º Departamento - Lavras</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101867</th>\n",
       "      <td>317090</td>\n",
       "      <td>VARZELANDIA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>11º Departamento - Montes Claros</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101869</th>\n",
       "      <td>317130</td>\n",
       "      <td>VICOSA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101870</th>\n",
       "      <td>317200</td>\n",
       "      <td>VISCONDE DO RIO BRANCO</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101871</th>\n",
       "      <td>317220</td>\n",
       "      <td>WENCESLAU BRAZ</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>17º Departamento - Pouso Alegre</td>\n",
       "      <td>3) Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>65473 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        municipio_cod          municipio_fato   data_fato  mes   ano  \\\n",
       "0              310010     ABADIA DOS DOURADOS  2022-01-01    1  2022   \n",
       "1              310020                  ABAETE  2022-01-01    1  2022   \n",
       "2              310030              ABRE-CAMPO  2022-01-01    1  2022   \n",
       "3              310030              ABRE-CAMPO  2022-01-01    1  2022   \n",
       "4              310090          AGUAS FORMOSAS  2022-01-01    1  2022   \n",
       "...               ...                     ...         ...  ...   ...   \n",
       "101866         317070                VARGINHA  2022-12-31   12  2022   \n",
       "101867         317090             VARZELANDIA  2022-12-31   12  2022   \n",
       "101869         317130                  VICOSA  2022-12-31   12  2022   \n",
       "101870         317200  VISCONDE DO RIO BRANCO  2022-12-31   12  2022   \n",
       "101871         317220          WENCESLAU BRAZ  2022-12-31   12  2022   \n",
       "\n",
       "                                     risp               rmbh  \\\n",
       "0       10º Departamento - Patos de Minas  3) Interior de MG   \n",
       "1           7º Departamento - Divinópolis  3) Interior de MG   \n",
       "2             12º Departamento - Ipatinga  3) Interior de MG   \n",
       "3             12º Departamento - Ipatinga  3) Interior de MG   \n",
       "4        15º Departamento - Teófilo Otoni  3) Interior de MG   \n",
       "...                                   ...                ...   \n",
       "101866           6º Departamento - Lavras  3) Interior de MG   \n",
       "101867   11º Departamento - Montes Claros  3) Interior de MG   \n",
       "101869     4º Departamento - Juiz de Fora  3) Interior de MG   \n",
       "101870     4º Departamento - Juiz de Fora  3) Interior de MG   \n",
       "101871    17º Departamento - Pouso Alegre  3) Interior de MG   \n",
       "\n",
       "                natureza_delito tentado_consumado  \\\n",
       "0                LESAO CORPORAL         CONSUMADO   \n",
       "1                        AMEACA         CONSUMADO   \n",
       "2                LESAO CORPORAL         CONSUMADO   \n",
       "3       VIAS DE FATO / AGRESSAO         CONSUMADO   \n",
       "4                        AMEACA         CONSUMADO   \n",
       "...                         ...               ...   \n",
       "101866  VIAS DE FATO / AGRESSAO         CONSUMADO   \n",
       "101867           LESAO CORPORAL         CONSUMADO   \n",
       "101869                   AMEACA         CONSUMADO   \n",
       "101870           LESAO CORPORAL         CONSUMADO   \n",
       "101871  VIAS DE FATO / AGRESSAO         CONSUMADO   \n",
       "\n",
       "        qtde_vitimas                                                                  \n",
       "0                                                     1.0                             \n",
       "1                                                     1.0                             \n",
       "2                                                     1.0                             \n",
       "3                                                     1.0                             \n",
       "4                                                     1.0                             \n",
       "...                                                   ...                             \n",
       "101866                                                1.0                             \n",
       "101867                                                1.0                             \n",
       "101869                                                2.0                             \n",
       "101870                                                1.0                             \n",
       "101871                                                1.0                             \n",
       "\n",
       "[65473 rows x 10 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tratamento de Dados da coluna \"rmbh\"\n",
    "df_pc = df_pc.replace([\"3) Interior de MG\", \"2) RMBH (sem BH)\", \"1) Belo Horizonte\"], [\"Interior de MG\", \"Região Metropolitana\", \"Belo Horizonte\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Renomeação de colunas\n",
    "df_pc = df_pc.rename(columns={'qtde_vitimas                                                                ': 'Quantidade vítimas', 'municipio_fato' : 'Município'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 65473 entries, 0 to 101871\n",
      "Data columns (total 10 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   municipio_cod       65473 non-null  int64  \n",
      " 1   Município           65473 non-null  object \n",
      " 2   data_fato           65473 non-null  object \n",
      " 3   mes                 65473 non-null  int64  \n",
      " 4   ano                 65473 non-null  int64  \n",
      " 5   risp                65473 non-null  object \n",
      " 6   rmbh                65473 non-null  object \n",
      " 7   natureza_delito     65473 non-null  object \n",
      " 8   tentado_consumado   65473 non-null  object \n",
      " 9   Quantidade vítimas  65473 non-null  float64\n",
      "dtypes: float64(1), int64(3), object(6)\n",
      "memory usage: 5.5+ MB\n"
     ]
    }
   ],
   "source": [
    "#tipos de dados por coluna\n",
    "df_pc.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>municipio_cod</th>\n",
       "      <th>Município</th>\n",
       "      <th>data_fato</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "      <th>risp</th>\n",
       "      <th>rmbh</th>\n",
       "      <th>natureza_delito</th>\n",
       "      <th>tentado_consumado</th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>310010</td>\n",
       "      <td>ABADIA DOS DOURADOS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>10º Departamento - Patos de Minas</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>310020</td>\n",
       "      <td>ABAETE</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>7º Departamento - Divinópolis</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE-CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE-CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>310090</td>\n",
       "      <td>AGUAS FORMOSAS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>15º Departamento - Teófilo Otoni</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101866</th>\n",
       "      <td>317070</td>\n",
       "      <td>VARGINHA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>6º Departamento - Lavras</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101867</th>\n",
       "      <td>317090</td>\n",
       "      <td>VARZELANDIA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>11º Departamento - Montes Claros</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101869</th>\n",
       "      <td>317130</td>\n",
       "      <td>VICOSA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101870</th>\n",
       "      <td>317200</td>\n",
       "      <td>VISCONDE DO RIO BRANCO</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101871</th>\n",
       "      <td>317220</td>\n",
       "      <td>WENCESLAU BRAZ</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>17º Departamento - Pouso Alegre</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>65473 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        municipio_cod               Município   data_fato  mes   ano  \\\n",
       "0              310010     ABADIA DOS DOURADOS  2022-01-01    1  2022   \n",
       "1              310020                  ABAETE  2022-01-01    1  2022   \n",
       "2              310030              ABRE-CAMPO  2022-01-01    1  2022   \n",
       "3              310030              ABRE-CAMPO  2022-01-01    1  2022   \n",
       "4              310090          AGUAS FORMOSAS  2022-01-01    1  2022   \n",
       "...               ...                     ...         ...  ...   ...   \n",
       "101866         317070                VARGINHA  2022-12-31   12  2022   \n",
       "101867         317090             VARZELANDIA  2022-12-31   12  2022   \n",
       "101869         317130                  VICOSA  2022-12-31   12  2022   \n",
       "101870         317200  VISCONDE DO RIO BRANCO  2022-12-31   12  2022   \n",
       "101871         317220          WENCESLAU BRAZ  2022-12-31   12  2022   \n",
       "\n",
       "                                     risp            rmbh  \\\n",
       "0       10º Departamento - Patos de Minas  Interior de MG   \n",
       "1           7º Departamento - Divinópolis  Interior de MG   \n",
       "2             12º Departamento - Ipatinga  Interior de MG   \n",
       "3             12º Departamento - Ipatinga  Interior de MG   \n",
       "4        15º Departamento - Teófilo Otoni  Interior de MG   \n",
       "...                                   ...             ...   \n",
       "101866           6º Departamento - Lavras  Interior de MG   \n",
       "101867   11º Departamento - Montes Claros  Interior de MG   \n",
       "101869     4º Departamento - Juiz de Fora  Interior de MG   \n",
       "101870     4º Departamento - Juiz de Fora  Interior de MG   \n",
       "101871    17º Departamento - Pouso Alegre  Interior de MG   \n",
       "\n",
       "                natureza_delito tentado_consumado  Quantidade vítimas  \n",
       "0                LESAO CORPORAL         CONSUMADO                   1  \n",
       "1                        AMEACA         CONSUMADO                   1  \n",
       "2                LESAO CORPORAL         CONSUMADO                   1  \n",
       "3       VIAS DE FATO / AGRESSAO         CONSUMADO                   1  \n",
       "4                        AMEACA         CONSUMADO                   1  \n",
       "...                         ...               ...                 ...  \n",
       "101866  VIAS DE FATO / AGRESSAO         CONSUMADO                   1  \n",
       "101867           LESAO CORPORAL         CONSUMADO                   1  \n",
       "101869                   AMEACA         CONSUMADO                   2  \n",
       "101870           LESAO CORPORAL         CONSUMADO                   1  \n",
       "101871  VIAS DE FATO / AGRESSAO         CONSUMADO                   1  \n",
       "\n",
       "[65473 rows x 10 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Transformando a coluna \"Quantidade vítimas\" em inteiro\n",
    "df_pc['Quantidade vítimas'] = df_pc['Quantidade vítimas'].astype(np.int64)\n",
    "df_pc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Função para tratamento da coluna \"Municípios\"\n",
    "def corrigir_nome(nome):\n",
    "  nome = nome.replace('Â','A').replace('Á','A').replace('Ã','A').replace('Ç','C').replace('É','E').replace('Ê','E').replace('Ó','O').replace('Ô','O').replace('Õ','O').replace('Í','I').replace('Ú','U').replace('-',' ').strip()\n",
    "  return nome"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pc['Município'] = df_pc['Município'].apply(corrigir_nome)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Verificando se os registros são únicos\n",
    "df_pc.columns.is_unique\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Verificando se os index são únicos\n",
    "df_pc.index.is_unique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 65473 entries, 0 to 101871\n",
      "Data columns (total 10 columns):\n",
      " #   Column              Non-Null Count  Dtype \n",
      "---  ------              --------------  ----- \n",
      " 0   municipio_cod       65473 non-null  int64 \n",
      " 1   Município           65473 non-null  object\n",
      " 2   data_fato           65473 non-null  object\n",
      " 3   mes                 65473 non-null  int64 \n",
      " 4   ano                 65473 non-null  int64 \n",
      " 5   risp                65473 non-null  object\n",
      " 6   rmbh                65473 non-null  object\n",
      " 7   natureza_delito     65473 non-null  object\n",
      " 8   tentado_consumado   65473 non-null  object\n",
      " 9   Quantidade vítimas  65473 non-null  int64 \n",
      "dtypes: int64(4), object(6)\n",
      "memory usage: 7.5+ MB\n"
     ]
    }
   ],
   "source": [
    "# Verificação de campos nulos\n",
    "df_pc.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>municipio_cod</th>\n",
       "      <th>Município</th>\n",
       "      <th>data_fato</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "      <th>risp</th>\n",
       "      <th>rmbh</th>\n",
       "      <th>natureza_delito</th>\n",
       "      <th>tentado_consumado</th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>310010</td>\n",
       "      <td>ABADIA DOS DOURADOS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>10º Departamento - Patos de Minas</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>310020</td>\n",
       "      <td>ABAETE</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>7º Departamento - Divinópolis</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>310090</td>\n",
       "      <td>AGUAS FORMOSAS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>15º Departamento - Teófilo Otoni</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101866</th>\n",
       "      <td>317070</td>\n",
       "      <td>VARGINHA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>6º Departamento - Lavras</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101867</th>\n",
       "      <td>317090</td>\n",
       "      <td>VARZELANDIA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>11º Departamento - Montes Claros</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101869</th>\n",
       "      <td>317130</td>\n",
       "      <td>VICOSA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101870</th>\n",
       "      <td>317200</td>\n",
       "      <td>VISCONDE DO RIO BRANCO</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101871</th>\n",
       "      <td>317220</td>\n",
       "      <td>WENCESLAU BRAZ</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>17º Departamento - Pouso Alegre</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>65473 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        municipio_cod               Município   data_fato  mes   ano  \\\n",
       "0              310010     ABADIA DOS DOURADOS  2022-01-01    1  2022   \n",
       "1              310020                  ABAETE  2022-01-01    1  2022   \n",
       "2              310030              ABRE CAMPO  2022-01-01    1  2022   \n",
       "3              310030              ABRE CAMPO  2022-01-01    1  2022   \n",
       "4              310090          AGUAS FORMOSAS  2022-01-01    1  2022   \n",
       "...               ...                     ...         ...  ...   ...   \n",
       "101866         317070                VARGINHA  2022-12-31   12  2022   \n",
       "101867         317090             VARZELANDIA  2022-12-31   12  2022   \n",
       "101869         317130                  VICOSA  2022-12-31   12  2022   \n",
       "101870         317200  VISCONDE DO RIO BRANCO  2022-12-31   12  2022   \n",
       "101871         317220          WENCESLAU BRAZ  2022-12-31   12  2022   \n",
       "\n",
       "                                     risp            rmbh  \\\n",
       "0       10º Departamento - Patos de Minas  Interior de MG   \n",
       "1           7º Departamento - Divinópolis  Interior de MG   \n",
       "2             12º Departamento - Ipatinga  Interior de MG   \n",
       "3             12º Departamento - Ipatinga  Interior de MG   \n",
       "4        15º Departamento - Teófilo Otoni  Interior de MG   \n",
       "...                                   ...             ...   \n",
       "101866           6º Departamento - Lavras  Interior de MG   \n",
       "101867   11º Departamento - Montes Claros  Interior de MG   \n",
       "101869     4º Departamento - Juiz de Fora  Interior de MG   \n",
       "101870     4º Departamento - Juiz de Fora  Interior de MG   \n",
       "101871    17º Departamento - Pouso Alegre  Interior de MG   \n",
       "\n",
       "                natureza_delito tentado_consumado  Quantidade vítimas  \n",
       "0                LESAO CORPORAL         CONSUMADO                   1  \n",
       "1                        AMEACA         CONSUMADO                   1  \n",
       "2                LESAO CORPORAL         CONSUMADO                   1  \n",
       "3       VIAS DE FATO / AGRESSAO         CONSUMADO                   1  \n",
       "4                        AMEACA         CONSUMADO                   1  \n",
       "...                         ...               ...                 ...  \n",
       "101866  VIAS DE FATO / AGRESSAO         CONSUMADO                   1  \n",
       "101867           LESAO CORPORAL         CONSUMADO                   1  \n",
       "101869                   AMEACA         CONSUMADO                   2  \n",
       "101870           LESAO CORPORAL         CONSUMADO                   1  \n",
       "101871  VIAS DE FATO / AGRESSAO         CONSUMADO                   1  \n",
       "\n",
       "[65473 rows x 10 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Análise Exploratória de Dados - POLÍCIA CIVIL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "risp\n",
       "12º Departamento - Ipatinga               6611\n",
       "4º Departamento - Juiz de Fora            5013\n",
       "2º Departamento - Contagem                4740\n",
       "7º Departamento - Divinópolis             4667\n",
       "11º Departamento - Montes Claros          4594\n",
       "18º Departamento - Poços de Caldas        4410\n",
       "3º Departamento - Vespasiano              3711\n",
       "6º Departamento - Lavras                  3691\n",
       "5º Departamento - Uberaba                 3478\n",
       "13º Departamento - Barbacena              3460\n",
       "17º Departamento - Pouso Alegre           3285\n",
       "15º Departamento - Teófilo Otoni          3214\n",
       "14º Departamento - Curvelo                2975\n",
       "8º Departamento - Governador Valadares    2737\n",
       "9º Departamento - Uberlândia              2324\n",
       "10º Departamento - Patos de Minas         2230\n",
       "19º Departamento - Sete Lagoas            1786\n",
       "16º Departamento - Unaí                   1458\n",
       "1º Departamento - Belo Horizonte          1089\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Ocorrências por Departamento de Polícias\n",
    "df_pc[\"risp\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>municipio_cod</th>\n",
       "      <th>Município</th>\n",
       "      <th>data_fato</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "      <th>risp</th>\n",
       "      <th>rmbh</th>\n",
       "      <th>natureza_delito</th>\n",
       "      <th>tentado_consumado</th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "      <th>Ocorrências</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>310010</td>\n",
       "      <td>ABADIA DOS DOURADOS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>10º Departamento - Patos de Minas</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "      <td>2230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>310020</td>\n",
       "      <td>ABAETE</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>7º Departamento - Divinópolis</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "      <td>4667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "      <td>6611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>310030</td>\n",
       "      <td>ABRE CAMPO</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>12º Departamento - Ipatinga</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "      <td>6611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>310090</td>\n",
       "      <td>AGUAS FORMOSAS</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>2022</td>\n",
       "      <td>15º Departamento - Teófilo Otoni</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "      <td>3214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101866</th>\n",
       "      <td>317070</td>\n",
       "      <td>VARGINHA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>6º Departamento - Lavras</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "      <td>3691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101867</th>\n",
       "      <td>317090</td>\n",
       "      <td>VARZELANDIA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>11º Departamento - Montes Claros</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "      <td>4594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101869</th>\n",
       "      <td>317130</td>\n",
       "      <td>VICOSA</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>AMEACA</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>2</td>\n",
       "      <td>5013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101870</th>\n",
       "      <td>317200</td>\n",
       "      <td>VISCONDE DO RIO BRANCO</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>4º Departamento - Juiz de Fora</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>LESAO CORPORAL</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "      <td>5013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101871</th>\n",
       "      <td>317220</td>\n",
       "      <td>WENCESLAU BRAZ</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>17º Departamento - Pouso Alegre</td>\n",
       "      <td>Interior de MG</td>\n",
       "      <td>VIAS DE FATO / AGRESSAO</td>\n",
       "      <td>CONSUMADO</td>\n",
       "      <td>1</td>\n",
       "      <td>3285</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>65473 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        municipio_cod               Município   data_fato  mes   ano  \\\n",
       "0              310010     ABADIA DOS DOURADOS  2022-01-01    1  2022   \n",
       "1              310020                  ABAETE  2022-01-01    1  2022   \n",
       "2              310030              ABRE CAMPO  2022-01-01    1  2022   \n",
       "3              310030              ABRE CAMPO  2022-01-01    1  2022   \n",
       "4              310090          AGUAS FORMOSAS  2022-01-01    1  2022   \n",
       "...               ...                     ...         ...  ...   ...   \n",
       "101866         317070                VARGINHA  2022-12-31   12  2022   \n",
       "101867         317090             VARZELANDIA  2022-12-31   12  2022   \n",
       "101869         317130                  VICOSA  2022-12-31   12  2022   \n",
       "101870         317200  VISCONDE DO RIO BRANCO  2022-12-31   12  2022   \n",
       "101871         317220          WENCESLAU BRAZ  2022-12-31   12  2022   \n",
       "\n",
       "                                     risp            rmbh  \\\n",
       "0       10º Departamento - Patos de Minas  Interior de MG   \n",
       "1           7º Departamento - Divinópolis  Interior de MG   \n",
       "2             12º Departamento - Ipatinga  Interior de MG   \n",
       "3             12º Departamento - Ipatinga  Interior de MG   \n",
       "4        15º Departamento - Teófilo Otoni  Interior de MG   \n",
       "...                                   ...             ...   \n",
       "101866           6º Departamento - Lavras  Interior de MG   \n",
       "101867   11º Departamento - Montes Claros  Interior de MG   \n",
       "101869     4º Departamento - Juiz de Fora  Interior de MG   \n",
       "101870     4º Departamento - Juiz de Fora  Interior de MG   \n",
       "101871    17º Departamento - Pouso Alegre  Interior de MG   \n",
       "\n",
       "                natureza_delito tentado_consumado  Quantidade vítimas  \\\n",
       "0                LESAO CORPORAL         CONSUMADO                   1   \n",
       "1                        AMEACA         CONSUMADO                   1   \n",
       "2                LESAO CORPORAL         CONSUMADO                   1   \n",
       "3       VIAS DE FATO / AGRESSAO         CONSUMADO                   1   \n",
       "4                        AMEACA         CONSUMADO                   1   \n",
       "...                         ...               ...                 ...   \n",
       "101866  VIAS DE FATO / AGRESSAO         CONSUMADO                   1   \n",
       "101867           LESAO CORPORAL         CONSUMADO                   1   \n",
       "101869                   AMEACA         CONSUMADO                   2   \n",
       "101870           LESAO CORPORAL         CONSUMADO                   1   \n",
       "101871  VIAS DE FATO / AGRESSAO         CONSUMADO                   1   \n",
       "\n",
       "        Ocorrências  \n",
       "0              2230  \n",
       "1              4667  \n",
       "2              6611  \n",
       "3              6611  \n",
       "4              3214  \n",
       "...             ...  \n",
       "101866         3691  \n",
       "101867         4594  \n",
       "101869         5013  \n",
       "101870         5013  \n",
       "101871         3285  \n",
       "\n",
       "[65473 rows x 11 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Ocorrências no ano de 2022 sobre os departamentos\n",
    "departamento = df_pc.assign(Ocorrências=df_pc['risp'].map(df_pc['risp'].value_counts()))\n",
    "departamento"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Ocorrências', ylabel='risp'>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotagem de gráfico = Ocorrências por departamento\n",
    "sns.barplot(x=departamento[\"Ocorrências\"], y = departamento[\"risp\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65473"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Total de Ocorrências entre os Departamentos de Polícia\n",
    "df_pc[\"risp\"].value_counts().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "rmbh\n",
       "Interior de MG          56340\n",
       "Região Metropolitana     8044\n",
       "Belo Horizonte           1089\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Comparativo entre as regiões das ocorrências\n",
    "df_pc[\"rmbh\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Município\n",
       "BELO HORIZONTE             1089\n",
       "JUIZ DE FORA                993\n",
       "UBERLANDIA                  939\n",
       "CONTAGEM                    937\n",
       "MONTES CLAROS               871\n",
       "                           ... \n",
       "PEDRO TEIXEIRA                2\n",
       "SANTA RITA DE JACUTINGA       2\n",
       "PASSABEM                      1\n",
       "TOCOS DO MOJI                 1\n",
       "ALAGOA                        1\n",
       "Name: count, Length: 852, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Número de ocorrência por município, Belo Horizonte lidera o topo.\n",
    "df_pc[\"Município\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Município', ylabel='Count'>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Histograma - Ocorrência por cidades\n",
    "sns.histplot(x=df_pc[\"Município\"], binwidth=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Soma de vítimas para cada município \n",
    "df_pc = df_pc.groupby(['Município'])['Quantidade vítimas'].sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Município</th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>65</td>\n",
       "      <td>BELO HORIZONTE</td>\n",
       "      <td>10714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>418</td>\n",
       "      <td>JUIZ DE FORA</td>\n",
       "      <td>3217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>205</td>\n",
       "      <td>CONTAGEM</td>\n",
       "      <td>2693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>823</td>\n",
       "      <td>UBERLANDIA</td>\n",
       "      <td>2627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>500</td>\n",
       "      <td>MONTES CLAROS</td>\n",
       "      <td>2174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847</th>\n",
       "      <td>113</td>\n",
       "      <td>CAMACHO</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>209</td>\n",
       "      <td>CORDISLANDIA</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>849</th>\n",
       "      <td>558</td>\n",
       "      <td>PASSABEM</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>809</td>\n",
       "      <td>TOCOS DO MOJI</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>851</th>\n",
       "      <td>12</td>\n",
       "      <td>ALAGOA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>852 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index       Município  Quantidade vítimas\n",
       "0       65  BELO HORIZONTE               10714\n",
       "1      418    JUIZ DE FORA                3217\n",
       "2      205        CONTAGEM                2693\n",
       "3      823      UBERLANDIA                2627\n",
       "4      500   MONTES CLAROS                2174\n",
       "..     ...             ...                 ...\n",
       "847    113         CAMACHO                   2\n",
       "848    209    CORDISLANDIA                   2\n",
       "849    558        PASSABEM                   1\n",
       "850    809   TOCOS DO MOJI                   1\n",
       "851     12          ALAGOA                   1\n",
       "\n",
       "[852 rows x 3 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pc.sort_values(by='Quantidade vítimas', ascending=False).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>852.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>115.899061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>448.596856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>32.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>76.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>10714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Quantidade vítimas\n",
       "count          852.000000\n",
       "mean           115.899061\n",
       "std            448.596856\n",
       "min              1.000000\n",
       "25%             16.000000\n",
       "50%             32.000000\n",
       "75%             76.250000\n",
       "max          10714.000000"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Descrição da Coluna \" Quantidade vítimas\".\n",
    "#Podemos observar como destaque os quartis e a média\n",
    "df_pc.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tratamento de dados do IBGE "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Leitura do csv - Base do IBGE\n",
    "df_ibge = pd.read_excel('Municípios_MG.xlsx', engine='openpyxl', skiprows = 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Município</th>\n",
       "      <th>Área Territorial - km² [2022]</th>\n",
       "      <th>População residente - pessoas [2022]</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Abadia dos Dourados</td>\n",
       "      <td>880.461</td>\n",
       "      <td>6272</td>\n",
       "      <td>7.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Abaeté</td>\n",
       "      <td>1817.067</td>\n",
       "      <td>22675</td>\n",
       "      <td>12.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Abre Campo</td>\n",
       "      <td>470.551</td>\n",
       "      <td>13927</td>\n",
       "      <td>29.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Acaiaca</td>\n",
       "      <td>101.886</td>\n",
       "      <td>3909</td>\n",
       "      <td>38.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Açucena</td>\n",
       "      <td>815.422</td>\n",
       "      <td>8943</td>\n",
       "      <td>10.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>Virginópolis</td>\n",
       "      <td>439.878</td>\n",
       "      <td>10314</td>\n",
       "      <td>23.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>849</th>\n",
       "      <td>Virgolândia</td>\n",
       "      <td>281.022</td>\n",
       "      <td>4552</td>\n",
       "      <td>16.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>Visconde do Rio Branco</td>\n",
       "      <td>243.351</td>\n",
       "      <td>39160</td>\n",
       "      <td>160.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>851</th>\n",
       "      <td>Volta Grande</td>\n",
       "      <td>205.552</td>\n",
       "      <td>4443</td>\n",
       "      <td>21.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>852</th>\n",
       "      <td>Wenceslau Braz</td>\n",
       "      <td>102.487</td>\n",
       "      <td>2356</td>\n",
       "      <td>22.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>853 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Município  Área Territorial - km² [2022]  \\\n",
       "0       Abadia dos Dourados                        880.461   \n",
       "1                    Abaeté                       1817.067   \n",
       "2                Abre Campo                        470.551   \n",
       "3                   Acaiaca                        101.886   \n",
       "4                   Açucena                        815.422   \n",
       "..                      ...                            ...   \n",
       "848            Virginópolis                        439.878   \n",
       "849             Virgolândia                        281.022   \n",
       "850  Visconde do Rio Branco                        243.351   \n",
       "851            Volta Grande                        205.552   \n",
       "852          Wenceslau Braz                        102.487   \n",
       "\n",
       "     População residente - pessoas [2022]  \\\n",
       "0                                    6272   \n",
       "1                                   22675   \n",
       "2                                   13927   \n",
       "3                                    3909   \n",
       "4                                    8943   \n",
       "..                                    ...   \n",
       "848                                 10314   \n",
       "849                                  4552   \n",
       "850                                 39160   \n",
       "851                                  4443   \n",
       "852                                  2356   \n",
       "\n",
       "     Densidade demográfica - hab/km² [2022]  \n",
       "0                                      7.12  \n",
       "1                                     12.48  \n",
       "2                                     29.60  \n",
       "3                                     38.37  \n",
       "4                                     10.97  \n",
       "..                                      ...  \n",
       "848                                   23.45  \n",
       "849                                   16.20  \n",
       "850                                  160.92  \n",
       "851                                   21.61  \n",
       "852                                   22.99  \n",
       "\n",
       "[853 rows x 4 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ibge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Correção de nomes\n",
    "df_ibge['Município'] = df_ibge['Município'].str.upper().apply(corrigir_nome)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Município</th>\n",
       "      <th>Área Territorial - km² [2022]</th>\n",
       "      <th>População residente - pessoas [2022]</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABADIA DOS DOURADOS</td>\n",
       "      <td>880.461</td>\n",
       "      <td>6272</td>\n",
       "      <td>7.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ABAETE</td>\n",
       "      <td>1817.067</td>\n",
       "      <td>22675</td>\n",
       "      <td>12.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABRE CAMPO</td>\n",
       "      <td>470.551</td>\n",
       "      <td>13927</td>\n",
       "      <td>29.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACAIACA</td>\n",
       "      <td>101.886</td>\n",
       "      <td>3909</td>\n",
       "      <td>38.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ACUCENA</td>\n",
       "      <td>815.422</td>\n",
       "      <td>8943</td>\n",
       "      <td>10.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>VIRGINOPOLIS</td>\n",
       "      <td>439.878</td>\n",
       "      <td>10314</td>\n",
       "      <td>23.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>849</th>\n",
       "      <td>VIRGOLANDIA</td>\n",
       "      <td>281.022</td>\n",
       "      <td>4552</td>\n",
       "      <td>16.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>VISCONDE DO RIO BRANCO</td>\n",
       "      <td>243.351</td>\n",
       "      <td>39160</td>\n",
       "      <td>160.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>851</th>\n",
       "      <td>VOLTA GRANDE</td>\n",
       "      <td>205.552</td>\n",
       "      <td>4443</td>\n",
       "      <td>21.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>852</th>\n",
       "      <td>WENCESLAU BRAZ</td>\n",
       "      <td>102.487</td>\n",
       "      <td>2356</td>\n",
       "      <td>22.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>853 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Município  Área Territorial - km² [2022]  \\\n",
       "0       ABADIA DOS DOURADOS                        880.461   \n",
       "1                    ABAETE                       1817.067   \n",
       "2                ABRE CAMPO                        470.551   \n",
       "3                   ACAIACA                        101.886   \n",
       "4                   ACUCENA                        815.422   \n",
       "..                      ...                            ...   \n",
       "848            VIRGINOPOLIS                        439.878   \n",
       "849             VIRGOLANDIA                        281.022   \n",
       "850  VISCONDE DO RIO BRANCO                        243.351   \n",
       "851            VOLTA GRANDE                        205.552   \n",
       "852          WENCESLAU BRAZ                        102.487   \n",
       "\n",
       "     População residente - pessoas [2022]  \\\n",
       "0                                    6272   \n",
       "1                                   22675   \n",
       "2                                   13927   \n",
       "3                                    3909   \n",
       "4                                    8943   \n",
       "..                                    ...   \n",
       "848                                 10314   \n",
       "849                                  4552   \n",
       "850                                 39160   \n",
       "851                                  4443   \n",
       "852                                  2356   \n",
       "\n",
       "     Densidade demográfica - hab/km² [2022]  \n",
       "0                                      7.12  \n",
       "1                                     12.48  \n",
       "2                                     29.60  \n",
       "3                                     38.37  \n",
       "4                                     10.97  \n",
       "..                                      ...  \n",
       "848                                   23.45  \n",
       "849                                   16.20  \n",
       "850                                  160.92  \n",
       "851                                   21.61  \n",
       "852                                   22.99  \n",
       "\n",
       "[853 rows x 4 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Observa-se que a base de dados oriunda da PC MG possui um município a menos que a base do IBGE \n",
    "df_ibge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 853 entries, 0 to 852\n",
      "Data columns (total 4 columns):\n",
      " #   Column                                  Non-Null Count  Dtype  \n",
      "---  ------                                  --------------  -----  \n",
      " 0   Município                               853 non-null    object \n",
      " 1   Área Territorial - km² [2022]           853 non-null    float64\n",
      " 2   População residente - pessoas [2022]    853 non-null    int64  \n",
      " 3   Densidade demográfica - hab/km² [2022]  853 non-null    float64\n",
      "dtypes: float64(2), int64(1), object(1)\n",
      "memory usage: 26.8+ KB\n"
     ]
    }
   ],
   "source": [
    "#Verificação de campos nulos\n",
    "df_ibge.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Município                                 0\n",
       "Área Territorial - km² [2022]             0\n",
       "População residente - pessoas [2022]      0\n",
       "Densidade demográfica - hab/km² [2022]    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ibge.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Município             object\n",
       "Quantidade vítimas     int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pc.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Município                                  object\n",
       "Área Territorial - km² [2022]             float64\n",
       "População residente - pessoas [2022]        int64\n",
       "Densidade demográfica - hab/km² [2022]    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ibge.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Análise Exploratória de Dados IBGE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Município</th>\n",
       "      <th>Área Territorial - km² [2022]</th>\n",
       "      <th>População residente - pessoas [2022]</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABADIA DOS DOURADOS</td>\n",
       "      <td>880.461</td>\n",
       "      <td>6272</td>\n",
       "      <td>7.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ABAETE</td>\n",
       "      <td>1817.067</td>\n",
       "      <td>22675</td>\n",
       "      <td>12.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABRE CAMPO</td>\n",
       "      <td>470.551</td>\n",
       "      <td>13927</td>\n",
       "      <td>29.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACAIACA</td>\n",
       "      <td>101.886</td>\n",
       "      <td>3909</td>\n",
       "      <td>38.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ACUCENA</td>\n",
       "      <td>815.422</td>\n",
       "      <td>8943</td>\n",
       "      <td>10.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>VIRGINOPOLIS</td>\n",
       "      <td>439.878</td>\n",
       "      <td>10314</td>\n",
       "      <td>23.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>849</th>\n",
       "      <td>VIRGOLANDIA</td>\n",
       "      <td>281.022</td>\n",
       "      <td>4552</td>\n",
       "      <td>16.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>VISCONDE DO RIO BRANCO</td>\n",
       "      <td>243.351</td>\n",
       "      <td>39160</td>\n",
       "      <td>160.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>851</th>\n",
       "      <td>VOLTA GRANDE</td>\n",
       "      <td>205.552</td>\n",
       "      <td>4443</td>\n",
       "      <td>21.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>852</th>\n",
       "      <td>WENCESLAU BRAZ</td>\n",
       "      <td>102.487</td>\n",
       "      <td>2356</td>\n",
       "      <td>22.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>853 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Município  Área Territorial - km² [2022]  \\\n",
       "0       ABADIA DOS DOURADOS                        880.461   \n",
       "1                    ABAETE                       1817.067   \n",
       "2                ABRE CAMPO                        470.551   \n",
       "3                   ACAIACA                        101.886   \n",
       "4                   ACUCENA                        815.422   \n",
       "..                      ...                            ...   \n",
       "848            VIRGINOPOLIS                        439.878   \n",
       "849             VIRGOLANDIA                        281.022   \n",
       "850  VISCONDE DO RIO BRANCO                        243.351   \n",
       "851            VOLTA GRANDE                        205.552   \n",
       "852          WENCESLAU BRAZ                        102.487   \n",
       "\n",
       "     População residente - pessoas [2022]  \\\n",
       "0                                    6272   \n",
       "1                                   22675   \n",
       "2                                   13927   \n",
       "3                                    3909   \n",
       "4                                    8943   \n",
       "..                                    ...   \n",
       "848                                 10314   \n",
       "849                                  4552   \n",
       "850                                 39160   \n",
       "851                                  4443   \n",
       "852                                  2356   \n",
       "\n",
       "     Densidade demográfica - hab/km² [2022]  \n",
       "0                                      7.12  \n",
       "1                                     12.48  \n",
       "2                                     29.60  \n",
       "3                                     38.37  \n",
       "4                                     10.97  \n",
       "..                                      ...  \n",
       "848                                   23.45  \n",
       "849                                   16.20  \n",
       "850                                  160.92  \n",
       "851                                   21.61  \n",
       "852                                   22.99  \n",
       "\n",
       "[853 rows x 4 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ibge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Área Territorial - km² [2022]</th>\n",
       "      <th>População residente - pessoas [2022]</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>853.000000</td>\n",
       "      <td>8.530000e+02</td>\n",
       "      <td>853.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>687.589673</td>\n",
       "      <td>2.407822e+04</td>\n",
       "      <td>69.078441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>965.848936</td>\n",
       "      <td>9.435155e+04</td>\n",
       "      <td>314.398490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.565000</td>\n",
       "      <td>8.330000e+02</td>\n",
       "      <td>1.210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>196.735000</td>\n",
       "      <td>4.639000e+03</td>\n",
       "      <td>12.170000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>363.828000</td>\n",
       "      <td>8.048000e+03</td>\n",
       "      <td>22.090000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>727.894000</td>\n",
       "      <td>1.728500e+04</td>\n",
       "      <td>43.760000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>10727.097000</td>\n",
       "      <td>2.315560e+06</td>\n",
       "      <td>6988.180000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Área Territorial - km² [2022]  População residente - pessoas [2022]  \\\n",
       "count                     853.000000                          8.530000e+02   \n",
       "mean                      687.589673                          2.407822e+04   \n",
       "std                       965.848936                          9.435155e+04   \n",
       "min                         3.565000                          8.330000e+02   \n",
       "25%                       196.735000                          4.639000e+03   \n",
       "50%                       363.828000                          8.048000e+03   \n",
       "75%                       727.894000                          1.728500e+04   \n",
       "max                     10727.097000                          2.315560e+06   \n",
       "\n",
       "       Densidade demográfica - hab/km² [2022]  \n",
       "count                              853.000000  \n",
       "mean                                69.078441  \n",
       "std                                314.398490  \n",
       "min                                  1.210000  \n",
       "25%                                 12.170000  \n",
       "50%                                 22.090000  \n",
       "75%                                 43.760000  \n",
       "max                               6988.180000  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Descrição dos dados do IBGE\n",
    "df_ibge.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Município', ylabel='Área Territorial - km² [2022]'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Grafico de linha - Área Territorial\n",
    "sns.lineplot(x = df_ibge[\"Município\"], y = df_ibge[\"Área Territorial - km² [2022]\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Município', ylabel='Área Territorial - km² [2022]'>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAqAAAAGxCAYAAAC9XgRmAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACxnElEQVR4nOydeXxTVfr/P0mapE3bJN1LoYWWIlA2i6y2gAIKigvKd0YWR7ZxZVHRGWQURVERHTdAxA115qegM4yguA3bCAVkswJlLxQKlFJK26Rt2iZN7u+P5FzuzdYkTdOkfd6vV19K7s3Nufee5XOe8zzPkXAcx4EgCIIgCIIgAoS0tQtAEARBEARBtC9IgBIEQRAEQRABhQQoQRAEQRAEEVBIgBIEQRAEQRABhQQoQRAEQRAEEVBIgBIEQRAEQRABhQQoQRAEQRAEEVBIgBIEQRAEQRABJay1C9CWsFgsKCkpQXR0NCQSSWsXhyAIgiAID+A4DtXV1UhJSYFUSra5QEAC1I+UlJQgNTW1tYtBEARBEIQPnD9/Hp06dWrtYrQLSID6kejoaADWCqxWq1u5NARBEARBeIJer0dqaio/jhMtDwlQP8KW3dVqNQlQgiAIgggxyH0ucJCjA0EQBEEQBBFQSIASBEEQBEEQAYUEKEEQBEEQBBFQSIASBEEQBEEQAYUEKEEQBEEQBBFQSIASBEEQBEEQAYUEKEEQBEEQBBFQSIASBEEQBEEQAYUEKEEQBEEQBBFQaCckgiDaPTqDEeU1RujrTVBHyBEfqYBGpWjtYhEEQbRZSIASBNGuKamqw/x1h7DjVDn/2fBu8XhtQl+kaCNasWQEQRBtF1qCJwii3aIzGB3EJwBsP1WOZ9Ydgs5gbKWSEQRBtG1IgBIE0W4przE6iE/G9lPlKK8hAUoQBNESkAAlCKLdoq83uT1e3cRxgiAIwjdIgBIE0W5Rh8vdHo9u4jhBEAThGyRACYJot8RHKTC8W7zTY8O7xSM+iiLhCYIgWgISoARBtFs0KgVem9DXQYQO7xaPpRP6UiomgiCIFoLSMBEE0a5J0UZg+aRslNcYUV1vQnS4HPFRlAeUIAiiJSEBShBEu0ejIsFJEAQRSGgJniAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggorS5At2/fjjvvvBMpKSmQSCRYv3696DjHcXj++efRoUMHREREYPTo0Th16pTonIqKCkyZMgVqtRparRYzZ85ETU2N6JxDhw5h2LBhCA8PR2pqKl5//XWHsvzrX/9Cjx49EB4ejj59+uCHH37w+/0SBEEQBEG0d1pdgNbW1qJfv3547733nB5//fXXsWzZMqxatQp79uxBZGQkxowZg/r6ev6cKVOm4MiRI9i0aRM2btyI7du346GHHuKP6/V63HrrrejcuTMOHDiAN954A4sWLcKHH37In7Nr1y5MmjQJM2fORH5+PsaPH4/x48ejoKCg5W6eIAiCIAiiHSLhOI5r7UIwJBIJvvnmG4wfPx6A1fqZkpKCp556Ck8//TQAQKfTISkpCZ999hkmTpyIY8eOISsrC/v27cOAAQMAAD/99BNuv/12XLhwASkpKXj//ffx7LPPorS0FAqFAgDwzDPPYP369Th+/DgA4L777kNtbS02btzIl2fIkCG4/vrrsWrVKo/Kr9frodFooNPpoFar/fVYCIIgCIJoQWj8DjytbgF1R1FREUpLSzF69Gj+M41Gg8GDB2P37t0AgN27d0Or1fLiEwBGjx4NqVSKPXv28OcMHz6cF58AMGbMGJw4cQKVlZX8OcLfYeew33FGQ0MD9Hq96I8gCIIgCIJwT1AL0NLSUgBAUlKS6POkpCT+WGlpKRITE0XHw8LCEBsbKzrH2TWEv+HqHHbcGUuWLIFGo+H/UlNTvb1FgiAIgiCIdkdQC9BgZ8GCBdDpdPzf+fPnW7tIBEEQBEEQQU9QC9Dk5GQAwOXLl0WfX758mT+WnJyMsrIy0fHGxkZUVFSIznF2DeFvuDqHHXeGUqmEWq0W/REEQRAEQRDuCWoBmp6ejuTkZGzZsoX/TK/XY8+ePRg6dCgAYOjQoaiqqsKBAwf4c7Zu3QqLxYLBgwfz52zfvh0mk4k/Z9OmTejevTtiYmL4c4S/w85hv0MQBEEQBEH4h1YXoDU1Nfj999/x+++/A7AGHv3+++8oLi6GRCLBE088gZdffhnffvstDh8+jAceeAApKSl8pHzPnj0xduxYPPjgg9i7dy927tyJ2bNnY+LEiUhJSQEATJ48GQqFAjNnzsSRI0fw1Vdf4d1338W8efP4cjz++OP46aef8Oabb+L48eNYtGgR9u/fj9mzZwf6kRAEQRAEQbRtuFZm27ZtHACHv6lTp3Icx3EWi4VbuHAhl5SUxCmVSm7UqFHciRMnRNe4evUqN2nSJC4qKopTq9Xc9OnTuerqatE5Bw8e5HJzczmlUsl17NiRe+211xzK8vXXX3PXXXcdp1AouF69enHff/+9V/ei0+k4AJxOp/PuIRAEQRAE0WrQ+B14gioPaKhDecQIgiAIIvSg8TvwtPoSPEEQBEEQBNG+IAFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBBQSoARBEARBEERAIQFKEARBEARBBJSw1i4AQRAEQRDtA53BiPIaI/T1Jqgj5IiPVECjUrR2sYhWgAQoQRAEQRAtTklVHeavO4Qdp8r5z4Z3i8drE/oiRRvRiiUjWgNagicIgiAIokXRGYwO4hMAtp8qxzPrDkFnMLZSyYjWggQoQRAEQRAtSnmN0UF8MrafKkd5DQnQ9gYJUIIgCIIgWhR9vcnt8eomjhNtDxKgBEEQBEG0KOpwudvj0U0cJ9oeHgchffvtt15f/JZbbkFEBDkWEwRBEER7Jj5KgeHd4rHdyTL88G7xiI+iSPj2hoTjOM6TE6VS74ylEokEp06dQkZGhk8FC0X0ej00Gg10Oh3UanVrF4cgCMJvUPocormUVNXhmXWHRCJ0eLd4LJ3QFx1aOQqexu/A41UaptLSUiQmJnp0bnR0tE8FIgiCIIILSp9D+IMUbQSWT8pGeY0R1fUmRIfLER9FE5n2isdmzalTp3q1nH7//ffTLIIgCCLEofQ5hD/RqBTomhiF69Ni0DUxisRnO8ZjC+inn37q1YXff/99rwtDEARBBBeepM8hEUEQhLdQFDxBEAThEkqfQxBES+C1AD148CBefvllrFy5EuXl4lmxXq/HjBkz/FY4giAIonWh9DkEQbQEXgnQ//73vxg0aBDWrl2LpUuXokePHti2bRt/vK6uDp9//rnfC0kQBEG0Dix9jjMofQ5BEL7ilQBdtGgRnn76aRQUFODs2bP461//irvuugs//fRTS5UPZrMZCxcuRHp6OiIiItC1a1csXrwYwuxRHMfh+eefR4cOHRAREYHRo0fj1KlToutUVFRgypQpUKvV0Gq1mDlzJmpqakTnHDp0CMOGDUN4eDhSU1Px+uuvt9h9EQRBhAIalQKvTejrIEJZ+hzy/yQIwic4L1Cr1VxhYaHosy+++IKLjIzkvvvuO660tJSTSqXeXLJJXnnlFS4uLo7buHEjV1RUxP3rX//ioqKiuHfffZc/57XXXuM0Gg23fv167uDBg9xdd93Fpaenc3V1dfw5Y8eO5fr168f9+uuv3I4dO7jMzExu0qRJ/HGdTsclJSVxU6ZM4QoKCrg1a9ZwERER3AcffOBxWXU6HQeA0+l0/rl5giCIIKGqtoErvFzN5Z+r4AovV3NVtQ2tXSSC8Bs0fgcerwRoQkICt3//fofP16xZw6lUKu7999/3uwAdN24cN2PGDNFn9957LzdlyhSO4zjOYrFwycnJ3BtvvMEfr6qq4pRKJbdmzRqO4zju6NGjHABu3759/Dk//vgjJ5FIuIsXL3Icx3ErV67kYmJiuIaGa53q/Pnzue7du3tcVqrABEEQBBF60PgdeLxagr/++utFPp+MiRMn4uOPP8bcuXP9YZQVceONN2LLli04efIkAGsQVF5eHm677TYAQFFREUpLSzF69Gj+OxqNBoMHD8bu3bsBALt374ZWq8WAAQP4c0aPHg2pVIo9e/bw5wwfPhwKxbXlpDFjxuDEiROorKx0WraGhgbo9XrRH0EQBEEQBOEer3ZCevTRR7F9+3anxyZNmgSO4/DRRx/5pWCMZ555Bnq9Hj169IBMJoPZbMYrr7yCKVOmALDuzgQASUlJou8lJSXxx5zt4BQWFobY2FjROenp6Q7XYMdiYmIcyrZkyRK8+OKLfrhLgiAIgiCI9oNXFtB77rkHb7/9tsvjkydPdmohbQ5ff/01vvjiC3z55Zf47bff8Pnnn+Pvf/97UETbL1iwADqdjv87f/58axeJIAiCIAgi6PHKAtoa/OUvf8EzzzyDiRMnAgD69OmDc+fOYcmSJZg6dSqSk5MBAJcvX0aHDh34712+fBnXX389ACA5ORllZWWi6zY2NqKiooL/fnJyMi5fviw6h/2bnWOPUqmEUqls/k0SBEEQBEG0I7xORL9y5UqMHj0af/zjH7FlyxbRsfLycmRkZPitcABgMBgglYqLKZPJYLFYAADp6elITk4WlUWv12PPnj0YOnQoAGDo0KGoqqrCgQMH+HO2bt0Ki8WCwYMH8+ds374dJtO1XT02bdqE7t27O11+JwiCIAiCIHzDKwG6bNky/OUvf0GPHj2gVCpx++23Y8mSJfxxs9mMc+fO+bWAd955J1555RV8//33OHv2LL755hu89dZbuOeeewAAEokETzzxBF5++WV8++23OHz4MB544AGkpKRg/PjxAICePXti7NixePDBB7F3717s3LkTs2fPxsSJE5GSkgLA6j6gUCgwc+ZMHDlyBF999RXeffddzJs3z6/3QxAEQRAE0e7xJmQ+KyuL++KLL/h/79y5k0tISOAWLlzIcRzXInlA9Xo99/jjj3NpaWlceHg4l5GRwT377LOidEkWi4VbuHAhl5SUxCmVSm7UqFHciRMnRNe5evUqN2nSJC4qKopTq9Xc9OnTuerqatE5Bw8e5HJzczmlUsl17NiRe+2117wqK6VxIAiCIIjQg8bvwCPhOMGWQk2gUqlw9OhRdOnShf+soKAAo0ePxvTp0/HEE08gJSUFZrPZ/0o5BNDr9dBoNNDpdFCr1a1dHIIgCIIgPIDG78DjVRBSfHw8zp8/LxKgvXv3xtatWzFy5EiUlJT4u3wEQRAEQRBEG8MrH9Dc3Fz85z//cfg8KysLW7ZswY8//ui3ghEEQRAEQRBtE68soM8884woklxIr169sHXrVqxbt84vBSMIgiAIgiDaJl75gBLuIR8SgiAIggg9aPwOPD4lot+7dy92797Nb2OZnJyMoUOHYtCgQX4tHEEQBEEQBNH28EqAlpWV4d5778WuXbuQlpbG75V++fJlPPnkk8jJycG6desc9l0nCIIgCIIgCIZXQUiPPfYYLBYLjh07hrNnz2LPnj3Ys2cPzp49i2PHjsFisWDWrFktVVaCIAiCIAiiDeCVD2h0dDS2b9+O7Oxsp8cPHDiAm266CdXV1X4rYChBPiQEQRAEEXrQ+B14vLKAKpVK6PV6l8erq6uhVCqbXSiCIAiCIAii7eKVAL3vvvswdepUfPPNNyIhqtfr8c0332D69OmYNGmS3wtJEARBEARBtB28CkJ66623YLFYMHHiRDQ2NkKhUAAAjEYjwsLCMHPmTPz9739vkYISBEEQBEEQbQOf8oDq9XocOHBAlIbphhtuaPd+E+RDQhAEQRChB43fgcenPKBqtRo333yzv8tCEARBEARBtAO88gEFgLq6OuTl5eHo0aMOx+rr6/GPf/zDLwUj2jY6gxGny2qQX1yJ01dqoDMYW7tIBEEQBEEECK+W4E+ePIlbb70VxcXFkEgkyM3NxZo1a5CSkgLAmpA+JSUFZrO5xQoczJAJ3zNKquowf90h7DhVzn82vFs8XpvQFynaiFYsGUEQBNEeofE78HhlAZ0/fz569+6NsrIynDhxAtHR0cjNzUVxcXFLlY9oY+gMRgfxCQDbT5XjmXWHyBJKEARBEO0ArwTorl27sGTJEsTHxyMzMxPfffcdxowZg2HDhuHMmTMtVUaiDVFeY3QQn4ztp8pRXkMClCAIgiDaOl4J0Lq6OoSFXYtbkkgkeP/993HnnXdixIgROHnypN8LSLQt9PUmt8ermzhOEARBEETo41UUfI8ePbB//3707NlT9PmKFSsAAHfddZf/Ska0SdThcrfHo5s4ThAEQRBE6OOVBfSee+7BmjVrnB5bsWIFJk2aBB/SihLtiPgoBYZ3i3d6bHi3eMRHKQJcIoIgCIIgAo1PiegJ51AUnWeUVNXhmXWHsN0uCn7phL7oQFHwBEEQRICh8Tvw+JSIniCaQ4o2AssnZaO8xojqehOiw+WIj1JAoyLrJ0EQBEG0Bzxegr/33nuh1+s9vvCUKVNQVlbmU6GIto9GpUDXxChcnxaDrolRJD4JgiAIoh3h8RK8TCbDyZMnkZCQ0OS5HMchNTUVv//+OzIyMppdyFCBTPgEQRAEEXrQ+B14PF6C5zgO1113XUuWhSAIgiAIgmgHeCxAt23b5vXFO3bs6PV3CIIgCIIgiLaNxwJ0xIgRLVkOgiAIgiAIop3gVR5QgiAIgiAIgmguJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgOKVADWZTDhx4gT/7927d/u9QARBEC2BzmDE6bIa5BdX4vSVGugMxtYuEkEQRLvFq604p06div379+P//u//8Oqrr+Kpp57Crl27WqpsBEEQfqGkqg7z1x3CjlPl/GfDu8XjtQl9kaKNaMWSEQRBtE+8soAWFBTg5MmTkMvleO+991qqTARBEH5DZzA6iE8A2H6qHM+sO0SWUIIgiFbAKwHaoUMHAMCLL76InTt3oqioqEUKRRAE4S/Ka4wO4pOx/VQ5ymtIgBIEQQQarwRoTk4OGhsbAQCrVq3C4MGDW6RQBEEQ/kJfb3J7vLqJ4wRBEIT/8coH9Pnnn+f/X61WY/369f4uD0EQhF9Rh8vdHo9u4jhBEAThf7wSoEJKSkqQl5eHsrIyWCwW0bG5c+c2u2AEQRD+ID5KgeHd4rHdyTL88G7xiI9StEKpCIIg2jcSjuM4b7/02Wef4eGHH4ZCoUBcXBwkEsm1C0okOHPmjF8LGSro9XpoNBrodDqo1erWLg5BEDZKqurwzLpDIhE6vFs8lk7oiw4UBU8Q7R4avwOPTwI0NTUVjzzyCBYsWACplHLZM6gCE0TwojMYUV5jRHW9CdHhcsRHKaBRkfWTIAgav1sDn5bgDQYDJk6cSOKTIIiQQaMiwUkQBBEs+KQgZ86ciX/961/+LgtBEARBEATRDvBpCd5sNuOOO+5AXV0d+vTpA7lcHEX61ltv+a2AoQSZ8AmCIAgi9KDxO/D4tAS/ZMkS/Pzzz+jevTsAOAQhEQRBEARBEIQrfBKgb775JlavXo1p06b5uTgEQRAEQRBEW8cnH1ClUomcnBx/l4UgCIIgCIJoB/gkQB9//HEsX77c32UhCIIgCIIg2gE+LcHv3bsXW7duxcaNG9GrVy+HIKT//Oc/fikcQRAEQRAE0fbwSYBqtVrce++9/i4LQRAEQRAE0Q7wSYB++umn/i4HQRAEQRAE0U7wyQd0zZo1Lo/95S9/8bkwBEEQBEEQRNvHJwH66KOP4scff3T4/Mknn8T/+3//r9mFsufixYu4//77ERcXh4iICPTp0wf79+/nj3Mch+effx4dOnRAREQERo8ejVOnTomuUVFRgSlTpkCtVkOr1WLmzJmoqakRnXPo0CEMGzYM4eHhSE1Nxeuvv+73eyEIgiAIgmjv+CRAv/jiC0yaNAl5eXn8Z3PmzMHXX3+Nbdu2+a1wAFBZWYmcnBzI5XL8+OOPOHr0KN58803ExMTw57z++utYtmwZVq1ahT179iAyMhJjxoxBfX09f86UKVNw5MgRbNq0CRs3bsT27dvx0EMP8cf1ej1uvfVWdO7cGQcOHMAbb7yBRYsW4cMPP/Tr/RAEQRAEQbR7OB/54osvuJiYGG7//v3co48+yqWkpHAnTpzw9XIumT9/Ppebm+vyuMVi4ZKTk7k33niD/6yqqopTKpXcmjVrOI7juKNHj3IAuH379vHn/Pjjj5xEIuEuXrzIcRzHrVy5kouJieEaGhpEv929e3ePy6rT6TgAnE6n8/g7BEEQBEG0LjR+Bx6fLKAAMHnyZLz88svIycnBd999h19++QXXXXed34Qx49tvv8WAAQPwhz/8AYmJicjOzsZHH33EHy8qKkJpaSlGjx7Nf6bRaDB48GDs3r0bALB7925otVoMGDCAP2f06NGQSqXYs2cPf87w4cOhUCj4c8aMGYMTJ06gsrLS7/dFEARBEATRXvE4Cn7evHlOP09ISED//v2xcuVK/rO33nqr+SWzcebMGbz//vuYN28e/va3v2Hfvn2YO3cuFAoFpk6ditLSUgBAUlKS6HtJSUn8sdLSUiQmJoqOh4WFITY2VnROenq6wzXYMeGSP6OhoQENDQ38v/V6fTPvliAIgiAIou3jsQDNz893+nlmZib0ej1/XCKR+KdkNiwWCwYMGIBXX30VAJCdnY2CggKsWrUKU6dO9etvecuSJUvw4osvtmoZCIIgCIIgQg2PBai/g4s8pUOHDsjKyhJ91rNnT6xbtw4AkJycDAC4fPkyOnTowJ9z+fJlXH/99fw5ZWVloms0NjaioqKC/35ycjIuX74sOof9m51jz4IFC0SWYb1ej9TUVG9vkSAIgiAIol3hsw9ooMjJycGJEydEn508eRKdO3cGAKSnpyM5ORlbtmzhj+v1euzZswdDhw4FAAwdOhRVVVU4cOAAf87WrVthsVgwePBg/pzt27fDZDLx52zatAndu3d3uvwOAEqlEmq1WvRHEARBEARBuCfoBeiTTz6JX3/9Fa+++ioKCwvx5Zdf4sMPP8SsWbMAWJf8n3jiCbz88sv49ttvcfjwYTzwwANISUnB+PHjAVgtpmPHjsWDDz6IvXv3YufOnZg9ezYmTpyIlJQUANagKoVCgZkzZ+LIkSP46quv8O6777r0fSUIgiAIgiB8Q8JxHNfahWiKjRs3YsGCBTh16hTS09Mxb948PPjgg/xxjuPwwgsv4MMPP0RVVRVyc3OxcuVKUVR+RUUFZs+eje+++w5SqRQTJkzAsmXLEBUVxZ9z6NAhzJo1C/v27UN8fDzmzJmD+fPne1xOvV4PjUYDnU5H1lCCIAiCCBFo/A48ISFAQwWqwARBEAQRetD4HXiCfgmeIAiCIAiCaFs0W4Cq1WqcOXPGH2UhCIIgCIIg2gHNFqC0gk8QBEEQBEF4Ay3BEwRBEARBEAGl2QL0/vvvJ4ddgiAIgiAIwmM83gnJFe+//74/ykEQBEEQBEG0E2gJniAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgOJxEJJer/f4ohQVTxAEQRAEQbjCYwGq1WohkUjcnsNxHCQSCcxmc7MLRhAEQRAEQbRNPBag27Zta8lyEEGAzmBEeY0R+noT1BFyxEcqoFEpWrtYBEEQBEG0MTwWoCNGjGjJchCtTElVHeavO4Qdp8r5z4Z3i8drE/oiRRvRiiUjCIIgCKKt0axE9AaDAcXFxTAajaLP+/bt26xCEYFFZzA6iE8A2H6qHM+sO4Tlk7L9bgklaytBEARBtF98EqBXrlzB9OnT8eOPPzo9Tj6goUV5jdFBfDK2nypHeY3Rr+KQrK0EQRAE0b7xKQ3TE088gaqqKuzZswcRERH46aef8Pnnn6Nbt2749ttv/V1GooXR15vcHq9u4rg3NGVt1RmMLr5JEARBEERbwScL6NatW7FhwwYMGDAAUqkUnTt3xi233AK1Wo0lS5Zg3Lhx/i4n0YKow+Vuj0c3cdwbAm1tJQiCIAgi+PDJAlpbW4vExEQAQExMDK5cuQIA6NOnD3777Tf/lY4ICPFRCgzvFu/02PBu8YiP8p8gDKS1lSAIgiCI4MQnAdq9e3ecOHECANCvXz988MEHuHjxIlatWoUOHTr4tYBEy6NRKfDahL4OInR4t3gsndDXrxbJQFpbCYIgCIIITnxagn/88cdx6dIlAMALL7yAsWPH4osvvoBCocBnn33mz/IRASJFG4Hlk7JRXmNEdb0J0eFyxEf5PzKdWVu3O1mG97e1lSAIgiCI4ETCcRzX3IsYDAYcP34caWlpiI93vpTbHtDr9dBoNNDpdLQdqRtKqurwzLpDIhHKrK0dKAqeIAiCCDA0fgcevwhQwgpVYM9heUBb0tpKEARBEJ5A43fg8XgJft68eVi8eDEiIyMxb948t+e+9dZbzS4Y0bbRqEhwEgRBEER7xWMBmp+fD5PJGqH822+/QSKROD3P1ecEQRAEQRAEAdASvF8hEz5BEARBhB40fgcer9MwmUwmhIWFoaCgoCXKQxAEQRBNojMYcbqsBvnFlTh9pYZ2USOIEMPrNExyuRxpaWm03ztBEATRKpRU1Tls6Tu8Wzxem9AXKZRJgyBCAp8S0T/77LP429/+hoqKCn+XhyAIgiBcojMYHcQnYN3K95l1h8gSShAhgk+J6FesWIHCwkKkpKSgc+fOiIyMFB2n7TgJgiCIlqC8xuggPhnbT5WjvMZIGTYIIgTwSYCOHz/ez8UgCIIgiKbR15vcHq9u4jhBEMGBTwL0hRde8Hc5CIIgCKJJ1OFyt8ejmzhOEERw4JMAZRw4cADHjh0DAPTq1QvZ2dl+KRRBEARBOCM+SoHh3eJFW/kyhneLR3wULb8TRCjgkwAtKyvDxIkT8b///Q9arRYAUFVVhZtvvhlr165FQkKCP8tIEARBEACsu6i9NqEvnll3SCRCh3eLx9IJfcn/kyBCBJ8E6Jw5c1BdXY0jR46gZ8+eAICjR49i6tSpmDt3LtasWePXQhIEQRAEI0UbgeWTslFeY0R1vQnR4XLER9H2vgQRSvi0E5JGo8HmzZsxcOBA0ed79+7FrbfeiqqqKn+VL6SgnRQIgiAIIvSg8Tvw+GQBtVgskMsdHb3lcjksFkuzC0UQBEEQRNtCZzCivMYIfb0J6gg54iPJat2e8UmAjhw5Eo8//jjWrFmDlJQUAMDFixfx5JNPYtSoUX4tIEEQBEEQoQ3tXkXY49NOSCtWrIBer0eXLl3QtWtXdO3aFenp6dDr9Vi+fLm/y0gQBEEQRIhCu1cRzvDJApqamorffvsNmzdvxvHjxwEAPXv2xOjRo/1aOIIgCIIgQhvavYpwhk8C9B//+Afuu+8+3HLLLbjlllv4z41GI9auXYsHHnjAbwUkCIIgCCJ0od2rCGf4tAQ/ffp06HQ6h8+rq6sxffr0ZheKIAiCIIi2Ae1eRTjDJwHKcRwkEonD5xcuXIBGo2l2oQiCIAiCaBuw3aucQbtXtV+8WoLPzs6GRCKBRCLBqFGjEBZ27etmsxlFRUUYO3as3wtJEARBEERoQrtXEc7wSoCOHz8eAPD7779jzJgxiIqK4o8pFAp06dIFEyZM8GsBCYIgCIIIbWj3KsIerwToCy+8AADo0qUL7rvvPoSHh7dIoQiCIAiCaFtoVCQ4iWv4FAU/depUf5eDIAiCIAiCaCd4LEBjY2Nx8uRJxMfHIyYmxmkQEqOiosIvhSMIgiAIgiDaHh4L0LfffhvR0dEAgHfeeaelykMQBEEQBEG0cTwWoGzZvbGxERKJBGPGjEFSUlKLFYwgCIIgiLaDzmBEeY0R+noT1BFyxEeST2h7xmsf0LCwMDzyyCM4duxYS5SHIAiCIIg2RklVncN+8MO7xeO1CX2Roo1oxZIRrYVPiegHDRqE/Px8f5eFIAiCIIg2hs5gdBCfgHUf+GfWHYLOYGylkhGtiU8C9LHHHsNTTz2FFStWYPfu3Th06JDoryV57bXXIJFI8MQTT/Cf1dfXY9asWYiLi0NUVBQmTJiAy5cvi75XXFyMcePGQaVSITExEX/5y1/Q2NgoOud///sf+vfvD6VSiczMTHz22Wctei8EQRAE0dYprzE6iE/G9lPlKK8hAdoe8SkN08SJEwEAc+fO5T+TSCT8Fp1ms9k/pbNj3759+OCDD9C3b1/R508++SS+//57/Otf/4JGo8Hs2bNx7733YufOnQCsuzSNGzcOycnJ2LVrFy5duoQHHngAcrkcr776KgCgqKgI48aNwyOPPIIvvvgCW7ZswZ///Gd06NABY8aMaZH7IQiCIIi2jr7e5PZ4dRPHibaJTwK0qKjI3+VokpqaGkyZMgUfffQRXn75Zf5znU6HTz75BF9++SVGjhwJAPj000/Rs2dP/PrrrxgyZAj++9//4ujRo9i8eTOSkpJw/fXXY/HixZg/fz4WLVoEhUKBVatWIT09HW+++SYAoGfPnsjLy8Pbb79NAtRHyOGcIAiCUIfL3R6PbuI40TbxegneZDJh5MiRMBgM6Ny5s9O/lmDWrFkYN24cRo8eLfr8wIEDMJlMos979OiBtLQ07N69GwCwe/du9OnTRxS1P2bMGOj1ehw5coQ/x/7aY8aM4a/hjIaGBuj1etEfYaWkqg6z1+Rj1Fu/4J6VuzDqzV8wZ00+SqrqWrtoBEEQRACJj1JgeLd4p8eGd4tHfBQZJtojXgtQuVyO+vr6liiLS9auXYvffvsNS5YscThWWloKhUIBrVYr+jwpKQmlpaX8OfYpo9i/mzpHr9ejrs65aFqyZAk0Gg3/l5qa6tP9tTXI4dw/6AxGnC6rQX5xJU5fqQnK5xYKZSQIonXRqBR4bUJfBxE6vFs8lk7oSytj7RSfluBnzZqFpUuX4uOPP0ZYmE+X8Jjz58/j8ccfx6ZNm4Ju7/kFCxZg3rx5/L/1ej2JUHjmcE4djntCIWVJKJSRIIjgIEUbgeWTslFeY0R1vQnR4XLER5FbVnvGJ/W4b98+bNmyBf/973/Rp08fREZGio7/5z//8UvhAOsSe1lZGfr3789/ZjabsX37dqxYsQI///wzjEYjqqqqRFbQy5cvIzk5GQCQnJyMvXv3iq7LouSF59hHzl++fBlqtRoREc4HU6VSCaVS2ex7bGuQw3nzaMqCvHxSdqt32qFQRoIggguNigQncQ2fBKhWq8WECRP8XRanjBo1CocPHxZ9Nn36dPTo0QPz589Hamoq5HI5tmzZwpfpxIkTKC4uxtChQwEAQ4cOxSuvvIKysjIkJiYCADZt2gS1Wo2srCz+nB9++EH0O5s2beKvQXgOOZw3j1CwIIdCGQmCIIjgxScB+umnn/q7HC6Jjo5G7969RZ9FRkYiLi6O/3zmzJmYN28eYmNjoVarMWfOHAwdOhRDhgwBANx6663IysrCn/70J7z++usoLS3Fc889h1mzZvEWzEceeQQrVqzAX//6V8yYMQNbt27F119/je+//z5g99pWYA7n250IFHI4b5pQsCCHQhkJgiCI4MWnRPSAdU/4zZs344MPPkB1dTUAoKSkBDU1NX4rnKe8/fbbuOOOOzBhwgQMHz4cycnJIjcAmUyGjRs3QiaTYejQobj//vvxwAMP4KWXXuLPSU9Px/fff49NmzahX79+ePPNN/Hxxx9TCiYfIIfz5hEKFuRQKCNBEAQRvEg4juO8/dK5c+cwduxYFBcXo6GhASdPnkRGRgYef/xxNDQ0YNWqVS1R1qBHr9dDo9FAp9NBrVa3dnFaHZYHlBzOvUNnMGLOmnyXFuSW8q/0Jm9ra5WRIAiiJaDxO/D4tAT/+OOPY8CAATh48CDi4uL4z++55x48+OCDfiscEdr4w+G8PSazZxbkZ9YdEgm8lrQgexvR3hplJAiCINoOPllA4+LisGvXLnTv3h3R0dE4ePAgMjIycPbsWWRlZcFgMLREWYMemkH5l/ae5idQFmSdwYjZa/KdBhU1Zc0kKzdBEG0BGr8Dj08WUIvF4nS/9wsXLiA6OrrZhSIISvMTuJQlzYlop7QqrU97XCUgCCL08UmA3nrrrXjnnXfw4YcfAgAkEglqamrwwgsv4Pbbb/drAYn2CaX5CRwU0R66tPdVAoIgQhevouBlMhnKysrw5ptvYufOncjKykJ9fT0mT56MLl264OLFi1i6dGlLlZVoR5AoChztOaI9lLcSpS1vCYIIZbyygDJ30U6dOuHgwYNYu3YtDh06hJqaGsycORNTpkxxuWsQQXhDexZFgaa95m0NdeshrRJcg9wQCCL08Hkj97CwMNx///3+LAtB8LRXUdQatMeI9rbgY0yrBFZCfSJBEO0VrwXoxx9/jKioKLfnzJ071+cCEQTQPkVRa5KijcDySdntJqK9LVgPaZWgbUwkCKK94rUAXbVqFWQymcvjEomEBCjhF9qbKGpt2lNEe1uwHtIqQduYSBBEe8VrAbp//34kJia2RFkIwoH2JIqIwNEWrIe0StA2JhIE0V7xSoBKJJKWKgdBEETAaCvWw/a+StAWJhIE0V7xKQqeIAjP8TRClyJ5A0dbsh6251WCtjKRoLZPtEe8EqAvvPBCkwFIBEFcw9MIXYrkDTzt3XrYFmgLEwlq+0R7xae94Ann0F6ybYvmWiU83WO9OXuxEwRxra2G2kSirbT9tmDBpfE78PicB5QghARjB9ScMvnDKuFphC5F8oYmwVjn2yuh6obQFto+WXAJXyEBSjSbYOyAmlMmf+UW9DRClyJ5Q49grPOtBQlx3wn1tk95WInm4NVe8ARhTzDuR93cMnlilfAETyN0KZI3tAjGOt9alFTVYfaafIx66xfcs3IXRr35C+asyUdJVV1rFy0kCPW276++kmifkAAlmkUwdkDNLZO/rBIsQtcZwghdT88jgoNgrPOtQagLcZ3BiNNlNcgvrsTpKzWtUt5Qb/uhbsElWhefl+D//e9/4+uvv0ZxcTGMRnHD/e2335pdMCI0CMYOqLll8pdVwtMI3bYQydueCMY63xqEsv9iUy4UgXIrCPW2H+oWXKJ18UmALlu2DM8++yymTZuGDRs2YPr06Th9+jT27duHWbNm+buMRBATjB1Qc8vkz9yCnqb6oZRAoUMw1vnWIFSFuDvL7QsbCvDCnb2w4JvDAfPvDeW231bysBKtg09L8CtXrsSHH36I5cuXQ6FQ4K9//Ss2bdqEuXPnQqfT+buMRBATjEtIzS0Ts0rYX8NXq4RGpUDXxChcnxaDrolRLr/v6XlE6xKMdb41CFUh7s5y272DGgv+E3i3glBt+/7uK4n2hU8W0OLiYtx4440AgIiICFRXVwMA/vSnP2HIkCFYsWKF/0pIBDXBuITkjzKFslWCaFmCsc63BqFq/XJnuc1O1WLF1kKnx3x1K2jrWQKoryR8xScBmpycjIqKCnTu3BlpaWn49ddf0a9fPxQVFdF2ne2QYOyA/FGmUM0tSLQ8wVjnA02oCnF3ltuGRovb73rrVtBe0nVRX0n4gk8CdOTIkfj222+RnZ2N6dOn48knn8S///1v7N+/H/fee6+/y0iEAMHYAQVjmYi2A9Wv0BTi7iy32gjX4lSlkCFGpcDpshqPrJmUI5Mg3OOTAP3www9hsVhnirNmzUJcXBx27dqFu+66Cw8//LBfC0gQBEEEL0IRpa83ARLHz4MJd5bbznEqp+JUpZBh9bSBeG59AXYUembNDOUsAQQRCGgveD9Ce8kSBNHeCNVlZlf7x5dU1TmI0yX39sEPhy6JxCfD1Z7t+cWVuGflLpe/v/6xG3F9Woz/bohoFjR+Bx6f84Du2LEDH3zwAU6fPo1///vf6NixI/75z38iPT0dubm5/iwjQRAEEYSE8jKzKxcKZ24FFo7Dgv8cdnodV9bMUM0SQBCBwqc0TOvWrcOYMWMQERGB/Px8NDQ0AAB0Oh1effVVvxaQIAiCCE7a6q5Q9mmRahoa3Z7vLDiJ0nURhHt8EqAvv/wyVq1ahY8++ghy+bVZXE5ODu2CRBAhTjBsUUiEBqGajN5bfLFmUo5MgnCPT0vwJ06cwPDhwx0+12g0qKqqam6ZiBakreekI5pHsPvzUf0NLtrLMrOvOU9DMUsAQQQKn/OAFhYWokuXLqLP8/LykJGR4Y9yES1AsIsLonVpKX8+f4lGqr/BR6gmo/eW5uQ89TZdF02yiPaCTwL0wQcfxOOPP47Vq1dDIpGgpKQEu3fvxtNPP42FCxf6u4yEHwjlYAEiMLRE2hh/iUaqv8FJqCaj94VAWDPb0iSLhDTRFD4J0GeeeQYWiwWjRo2CwWDA8OHDoVQq8fTTT2POnDn+LiPhBygnHdEU/vbn86dobG79pcGw5WhPy8wtuflAW5pktSUhTbQcXgtQs9mMnTt3YtasWfjLX/6CwsJC1NTUICsrC1FRUS1RRsIPtJdgAcJ3/O3P589Jjzf1Vyg2NRFyKGRSLPjmcJsaDINNUNOuUM2nrRgJ2pKQJloWrwWoTCbDrbfeimPHjkGr1SIrK6slykX4mfYSLED4jr/9+fw56fG0/tpbXmaPzER+cSV2Fl4VnR/KgyFZl9ombcVI0FaENNHy+JSGqXfv3jhz5oy/y0K0IJSTLvCEWjojf6eN8eekx5P668zykp2qdRCfjFDMU9mUdSnY65ivhFpb8oW2YiRoK0KaaHl88gF9+eWX8fTTT2Px4sW44YYbEBkZKTpO21gFH60ZLBBsy4WBIFStVP705/OnRdWT+nu6rMZBmDU0WtxeN9QGw/ZoXQrVtuQtbSWjQFsR0kTL45MAvf322wEAd911FyQSCf85x3GQSCQwm83+KR3hV1ojWKC9DB5CQt0Hyl/+fP6e9DRVf51ZXpRh7hd5Qm0wbG/WpVBvS97QVjIKtBUhTbQ8PgnQbdu2+bscRIAIZLBAexo8hLRFK5WvVmx/T3rc1V9nlpf881XIyYxzugwfioNhqFuXvK1HbbEtucOf7aW1Vp7aipAmWh6fBOiIESNcHisoKPC5METbor0NHoy2ZqVqrhU7UJMeZ5aX1XlFWDYpGxIAeQIRGqqDYShbl3ypR22tLXmCP9pLa688tafUXITv+BSEZE91dTU+/PBDDBo0CP369fPHJYk2QHscPIDQt1IJCaWgF2dBVAajGV/tLcbSCX2xZd4IrH/sRmyZNwLLJ2WjQwi6gITq/uK+1qO21JYCRbC0WY1Kga6JUbg+LQZdE6OCtm4SrYdPFlDG9u3b8cknn2DdunVISUnBvffei/fee89fZSNCnPY6eISylcoeV1ZslUKGvqlaXNLV40x5bdAEl7UHy0so3qOvqyFtqS0Fiva68kSEHk0KUJ1OB41Gw/+7tLQUn332GT755BPo9Xr88Y9/RENDA9avX085QQkR7XXwaEs+UM6s2CqFDMsmZePTnUVYsbWQ/zxYgsvaQ1L0ULtHX1dD2lJbChTtdeWJCD2aFKBjx47F5s2bERkZiTvvvBPbt2/HuHHj8M4772Ds2LGQyWRYtWpVIMpKuCEYUx2158EjFK1UznBmxZ6Rm45Pdxa1qeTuRMvSnNWQttKWAkV7XXkiQo8mBegTTzyBVatW4amnnsKPP/6IuXPn4tFHH0W3bt0CUT7CA7xxOA+0UG3Pg0eoWamc4cyKnZ2qFVk+hdASH+GM5q6GtIW2FCja68oTEXo0GYR03333Ye7cuQCAvLw8VFdX44YbbsDgwYOxYsUKlJc79zUhAoM3DuclVXWYvSYfo976Bfes3IVRb/6COWvyUVJV16JlbI/O6G1l5xZnQS9tLbk70fKEavBUKBKqz7qt9JmE50g4juO8/VJtbS2++uorrF69Gnv37oXZbMZbb72FGTNmIDo6uiXKGRLo9XpoNBrodLqA7QZ1uqwGo976xeXxLfNGoGtiFHQGI2avyXfqnD68Wzwtm/qR1k6B0hIwy3l1vQnhchnGvrvD5bmszgUbweim0t4Q1qP2tBrSGoTSsw6GPrM1xu/2jk9pmCIjIzFjxgzk5eXh8OHDeOqpp/Daa68hMTERd911l7/LSLjBU4dzTyIjieYTLClQ/I3Qit1BE97kvuzBRmtZ/wkx7XE1pLUIlWfdVvtMommanQe0e/fueP3113HhwgWsWbPGH2UivMBTh3OKjAwM7UHoh9oSHw1wBBG8tIc+k3BOs/KACpHJZBg/fjzGjx/vr0sSHuCpwzlFRgaG9iL0Qym4rL3kRfTVxYBcE9omrfFevf1NncGIiiYmgG2lzyQc8ZsAJVoHT1MdUWSklZbulNuT0HcWmRyMYqY9TAp89aELBt87wv+0xnv19jfZ+dNu7OL2um2pzyTEkABtA3hijWrPOTkZgeiU27PQD1Yx09YnBU25GLgKMPT1e0Rw0xrv1dvfFJ7fL1WLnMw4h7zCQNvvM9s7ftkLvqVZsmQJBg4ciOjoaCQmJmL8+PE4ceKE6Jz6+nrMmjULcXFxiIqKwoQJE3D58mXROcXFxRg3bhxUKhUSExPxl7/8BY2NjaJz/ve//6F///5QKpXIzMzEZ5991tK35xc8cThnQrUt7IntLYHyAww1/0h/Ecx+lmxS4Iy2MMD56kNHvndtk9Z4r97+pvD81XlFmJ6TjpzMONE5bb3PJELEAvrLL79g1qxZGDhwIBobG/G3v/0Nt956K44ePYrIyEgAwJNPPonvv/8e//rXv6DRaDB79mzce++92LlzJwDAbDZj3LhxSE5Oxq5du3Dp0iU88MADkMvlePXVVwEARUVFGDduHB555BF88cUX2LJlC/785z+jQ4cOGDNmTKvdvz9prwmdA+kHGEr+kf4imP0sW9v639JuCb66GLQH14T2SGu8V29/U3i+wWjG3DX5mJGbjhk56WhotKBLnAodtRFtus8kQkSA/vTTT6J/f/bZZ0hMTMSBAwcwfPhw6HQ6fPLJJ/jyyy8xcuRIAMCnn36Knj174tdff8WQIUPw3//+F0ePHsXmzZuRlJSE66+/HosXL8b8+fOxaNEiKBQKrFq1Cunp6XjzzTcBAD179kReXh7efvvtNiNA2yuB7pTbm9APdjHTWpOCQOxS5quLQVt3TWirNFVPWuO9evub9ucbjGbR7mpb5o1oV/1neyUkluDt0el0AIDY2FgAwIEDB2AymTB69Gj+nB49eiAtLQ27d+8GAOzevRt9+vRBUlISf86YMWOg1+tx5MgR/hzhNdg57Br2NDQ0QK/Xi/6I4IQG25YlFJ5voPMiBmqXMl9dDNq6a0JbxJN60hrv1dvfdHa+SiHD7JGZ+PLPg6GrM9JuSO2AkBOgFosFTzzxBHJyctC7d28AQGlpKRQKBbRarejcpKQklJaW8ucIxSc7zo65O0ev16OuznEgWLJkCTQaDf+Xmprql3sk/E97HWwDtb1de32+7vDUL665/rO++h23V39lTwm2rSE9rSet8V69/U3781UKGZZNykZ+cSUmf7wH976/mzaLaAeExBK8kFmzZqGgoAB5eXmtXRQsWLAA8+bN4/+t1+tDXoT6y18t2NLxtLYfYGsQyKh0++erUsgwIzcdN2bEQRkmRXnttcGxveDPXcqaem6+uhi0R39lTwi2jA46gxGXdPUe15PWeK+ufhOwbhltPxYIz7dwHF767ohDJDxlZGjbhJQAnT17NjZu3Ijt27ejU6dO/OfJyckwGo2oqqoSWUEvX76M5ORk/py9e/eKrsei5IXn2EfOX758GWq1GhERjp2OUqmEUqn0y725I1Bizl+dbrB13oz2NNi2RioW9nyv1hrBAVi0oUDk1+VrHXBX/4NtoiOkubuUMRHf0GhGfnFlk/fnq99xe/NXbopgS0/F+tNJg9LcnmfvZ90a79X+N5saC9j5p8tqsMNJGiag9YMYiZYjJAQox3GYM2cOvvnmG/zvf/9Denq66PgNN9wAuVyOLVu2YMKECQCAEydOoLi4GEOHDgUADB06FK+88grKysqQmJgIANi0aRPUajWysrL4c3744QfRtTdt2sRfozUIlJjzV6cbbJ23Pe1lsG2tqHR2zdlr8h0GFF/qgKv6v3RCX3BAUE50GM3ZpYwtSX66s8gvIp7wnGDK6CDsT0MtYbs3Y0GwBzESLUNI+IDOmjUL/+///T98+eWXiI6ORmlpKUpLS3m/TI1Gg5kzZ2LevHnYtm0bDhw4gOnTp2Po0KEYMmQIAODWW29FVlYW/vSnP+HgwYP4+eef8dxzz2HWrFm8FfORRx7BmTNn8Ne//hXHjx/HypUr8fXXX+PJJ59slfsOZG5Ff+WOo9yCwUFLdOie+sT5qw64q///O3kF8/8dnHlHGZ76xTnzn52Rm45Pdxa5XJIMhvtrDQLhlxlMYkjYlvLPVznkymQEo5+1N/1AKAQxEv4nJCyg77//PgDgpptuEn3+6aefYtq0aQCAt99+G1KpFBMmTEBDQwPGjBmDlStX8ufKZDJs3LgRjz76KIYOHYrIyEhMnToVL730En9Oeno6vv/+ezz55JN499130alTJ3z88cetloIpkDNxf3W6wdR5tyTBvPQL+L9D98YS76864K7+J0YrsaMwOKxU7vB1l7LsVK3I8inEX/cX7HXYHl9Wg3y5x2ASQ8K2tDqvCMsmZQOAaGISrH7s3vQD7XkHufZMSAhQjuOaPCc8PBzvvfce3nvvPZfndO7c2WGJ3Z6bbroJ+fn5XpexJQikmPNXpxtMnXdLEaw+rkL82aF761bhrzrgrv43NFrcftebttHSQswTtw97oWqyuO/zmtv2Q6EOC/HFtcfXewwmMSRsS84StmfER6KDJjzoxCfgXT/QHoNEiRBZgm+vBFLM+SuNTltPxxPMW04K8WcqFm+X1P1VB9zVf2WYY9fF8gh+MnUATBbOoyXa5uTf9DfCPKWxTbyf5rT9UKnDQrytg825x2BKT2XflljC9pmf78favcVBKz4B7/uB9rxVdHslJCyg7ZVAzsT9NQP15DqhtvQnRDgQsijl7FQtGhotCJfLUGUwBc29+Cvq31tLvL/qkrv6X1bdIDrmS9BOMAfMtWTbD6YgG0/xtg429x6DJWNGKFsGfSl7ewkSJayQAA1iAt35+KvTFabjMVs4mC0cDMZG1JnMuFBhwIJvDofM0p89bCB0JXiG2d5NsNyLLx26/QQhSum+m3BmjfNHXXJX/2++LgEjrkvgjzUVtONMTAazEGvJtt/Srj0tMcH0djXIH/cYLGIoWMSwL3hb9lA2ThDeQwI0yAl05+OvTlejUqDWaBZZmGaPzER+cWVIJxtmA6ErwbMjhO4FEHf4mgg5FDKpwwRhyb19MKxbvFOx5s4a54+61FT9Z8caGs1eB+0Ee8BcS7X9lnTtaSnfUm8twm3NFz1YxLAveFr2UPNLJpoP+YCGAIHew9ofOFvezE7VOgg2RqikaGIDYVu4F+b/eOeKPGw5XoaahkYs+I/jkvTijUcx6+bMVvOJc1f/2TFfgpJCQaQ4u3dPUxG5Oq+l/LTt2zzzyZ16Yxccu6THqcvVPvuXeuuX2dZ90dsaoeiXTDQfsoASLYKz5U1/Ri63FmwgPHZJ73BM6BN6tdYIXKkJ2iUk1uEfOFfJuxJkp2qd7kZiMJox47N9+HHuMDRauKBcBvRFTHpqVQumZUFPrURNndcSy/v2/tH+TqTvjUU4lH0n2yPB7A5DtBwkQAmnNHfQdba86SxyWYg/LU4tKRpStBGobWgUfRZqO9ewDn/2yEzelWDK4M4uzzcYzag0GHF9WkwAS+k5vgTteCJSgmlZ0NOgKU/Oa4nlfWGb98Un1xO8WYoOZd9JZwTTRMjfBLs7DNEykAAlHPDHoOvMIsV28nC2dO3PZbFAiIbEaKVI8LTUgNtSsA5fmPA8kBOE5uBqIPbF4uVOpFzW12P+vw/6ZUtRf9yjp1YiT8/zt1+hsM0HIpG+J4Sy76SQYJoItQSh4A5D+B8SoIQIf6WmEVqk2NL0gLQY3Nm3A17eeEy0i40/l8UClVrHXvD4c8ANhKWDdfhCt4hATRCaQ1MDsTD7goXjIAGgqzfh0rk6aFQKp8/SmUgpqarD2fJapy4JQMuKKFf3OHdUN7ffY1ai1rImCdt8W3C3CRaCOV2Yvwim5P9E4CABGqK0lEjxly8OE2gvbCjAfYPS+KVpJkYfvakrlHIptBEKvy6LBdKXSGg9u1rr3kne0wE3UJYO1uELrZ7BvtWfpwNxrdGM5zcUYKKt3tnfS1PPkv3OpEFpbsvTEiLK3T0+MqIr/29nOWhjbO+ntaxJwklZsFvTQ2k5uz34R5LPbvuEBGgIoTNYhQ4HYNGGApF1xl8ixZ/WkxRtBF6+pw+e/vp3XgSwnTxWbC3E8G7xfp+9B8L64zB4eTA792TADaSlg3X4v5y8wls97bf6A4C0WBUSo5VBMQB4uhvO/HWH0C9V67NLBPudaTd2cVse+3fqD1Hj7h53nbmKYd3iRYFjzvyNA2lNcnbPyydlo8pg8il1V0vgSaqxYF7Obi/+kW3NZ5doGhKgIQKzjPVL1bZoLk1/W09q6hsDuozprPxCaxHbotFXi4crC+WSe/s0e9APtKUjRRuB23snY2hGHBZuKMCOU+X8BIFZHoJpGzxPB2ImHn11iWC/441Lgr8s1+7ucXVeEb6bk4u9RRVNiutAWJPc3XPn+EgsDQKLln0ZQzEXcWv6RwbaUtxWfHYJzyABGgIILWPNGVg9ISo8zK+WC3/N3j3tCO2tP/6MTndnoVz07RG8ek8f/O2bwz4PuK1h6WAd/oogtDz4siMTe4ZN+SDWNphc1ik24LtySRhm9079abl2JzYMRjMkAAZ0jsGC/xx2es7+c5WoMphg5jg8d0cWLBwHQ4MZmgjv3mlT7a21Iu29wVUuYn/3ny0t0lrLP7KtBz4RrQ8J0BBAaBkzmlvOub+kqg7PbyjA1Bu7wMJxfvED9Mfs3dOOUGcwoqLWiJfu7o3n1h9GXuFVv0anu7NQbjpWhgW392zWgNualo5gszywd37gXCVvvU6IVno8OXLng6hSyKCOUGD2mnyndUo44AtdEhotHFJjIhAmlaJUXw+DyexVdLonNCU24iIVOFNe6/K+lk3KxnPrDzt1z/G0DJ60N39H2reEiAtELuJAiLTW8I8Uind7f+NzV2sRJpVAGSYNGT9aIjghARoCCC1jCVFKt+dGNmElcoWww9l1+io/6DY0WqCNkKNrYhSS1OFuv++sM2ru7N1T65LQReFoiQ7Xp8Vgek46EqKVfrN4NGWh1NeZkJHg+05VFAlqxVmSfBbAtmxSNjiOQ56bydHwbvFul88X3pGFhesLRJkYANdL2Oy3V08biCU/HHfI4OBpdDq7N3eDtidiQx3uPODNH5MtT9ubP6313kwwvRE8LZ2LOJA+24G2JjPx7mwFibWF97YWOrQFso4S3kACNAQQWsYUYVKXA2tOZhwUMu92V2WdekOjme9ImR+gkC3zRiBJ7fwaLbnrijeBJ0IXha3HrwAAVk7p7/b63gyULW2hpEhQK86S5AMQBUk9dlMmwuUyh6VlYfaF6bZAKntLfv80rcslbFanuiZGiQb8GJUCz7kQrZ5Gp3sqtJoSG64mKv5YXvbUsumvtuDtBNMbS2NL5yIOtM92IFcpmHh3NqmZkZuO5VtPIb+4CrNHZorq+i8nr+D23skO7hpkKSWcQQI0BBAOOJd09U4H1pzMOEzPSYeuzggg0qPrCjt1X4VaS/uCeRN4AjgusfnT4hEIC2Vr+80FA86S5DOEWRS2zBuBrolRDt9P0Ubg73/oh6u1Riy6sxfMFg4G4zU/SFdL2AxWp4QD/umyGgfxyfAkOn3JvX3wzH8Oe2wtcyc27CcqTPQ25SPryWTL0/bmr7bg7QTT/rg7S6OzMjK/Xgng1oruCb5Ygd2JsWASaky8O2uD2ala/jna1/WczDgMzYjjy+1s4nBLz0QsuqsX6k2WoLhXovUgARoCCAecMKkEcwR+aQ2NFijDpMg/X4W5a/Lx3excj65pLxx9FWotveuKJ5YW4UBgfx/+tHgEykLp7bNq7sAVTAMf4DxJvjPcCSpW/vIaI2pMjdCohEFG7nO2OqvrzY1OP3fV4FdrmTDpPkvLlp2qdXouE6jhchkOnq+EVqWAsdGCmoZGh/ftqWXTX23B2wmmPe6enbMyGoxmfLW3GEsn9EW9yeIwyfOmLXhrBXZlxV06oS84OIrs1lzSZuLdWRtsaLS4dPfYWXgVCzcUYIUteM/+nlQKGe4blIa/rjvkdX5eou1BAjREYANOlcGEGzrHOF1qa47lwVeh1tKR295aWuzvg83UlWFSZKVo+OWiGJUcabEqr4VWsFkomxsE4Y8gCn8LWGdJ8p3hznrt7r68qVPs3tyVxZPo9Ko6cTuwX6o3NpqhM3gnQtm5s9fkY0fhVfRLi3Fow0IfPtYWXv/5hMvB35tn44+24O0E0xnuVmfqTWaPswF42xa8rUeurLj/O3kFPxy65NYnOdD9CxPvZ52sFijDpG7dPXYILNf29xtqWxYTLYt3DoNEq6JRKfj8esO7xYuONdfysDqvCNNz0pGTGefVdZvjC6YzGHG6rAb5xZU4faUGOoOjZYp1hO7ulw0Ezu7DYDTjmXWH8PSt3XGwuBIzP9+Px774DZM+2oMF/zmMkqo6t+V3Vt4z5bWABEiPj0TXRN+DjppLU+4Pzp6nP78PWAft2WvyMeqtX3DPyl0Y9eYvmLMm36vnag9752XVDQ71kSEc4O3r0WV9vdv7AtBknbK/tx8KSt2WJS5SgZqGRpf3JBSwTBTmC+rjbcvyfHpuwomkszYsHPCbGvyZAPbk2TA0KgW6Jkbh+rQYn9qCsO3aw96xL30Me3cj3/wFt769HWPf2YF3Np9EhELmtIy+tAVvnpW7laLEaKVL9w6hG0KgSdFGoGtiFIbZ3V/++aomv1tdb3I6cchO1To1cgDWe71aa/RoXCDaBmQBDUG8sTw0leuQYb8LjiZCjhhV09tk+uoL5o21oan7tV9qY/cx66ZMKOVSxEcqbQEkvs+6gzEnXnODIJr7fX9FATuro86S5DOEA7yz9/Llnwc3eV/2QUb2dcr+3jzZptTd0n7++So+hZS/otXtt4C1b8MNjRakx0fylipPg5SaY9n01hru6VK+N32ML/XS17bg6bNyZ8V152qiUshg4TicLqtpFReZJHW4w4YCq/OK8K+Hh7r9nivDQ1P3ygEu06PR8nzbgwRoiOKJn6C3y5DCXXA8FQ+++IL5MkA4u1822NU0WKOUX7q7FwxGMx9wwraQdBdAEkih5azszRlUmuv+0Nzv+yMKuClhr1G5TpLv6r3YL3e7ui93bcj+3jyZoLmbjJ24pMcS20YFzY1WFz6zT6YOEB2zz2Dxr0euCQVvfGp98dn2dZLm7QRTeG1nfYy39VJnMKLCZmVzlsXgt+JK1Da49zdu6lm5s+K6cu9glvKXvjvSItsue4qz9xMVHubRpMD+HHeuLDNy0x22mAZoeb4tQwK0jeKJaPJXQI23FhN/ChcWeezKr02jCg6h5azszZ3lNzcVTnO/r683uRywV+cVNflcPRX2rgZ4V+/FH5kPnNUZobhb/9iNfAS+cCL00t298fyGAoc29dLdvdHB1k5OltW4/N2mLF72z6wp321txLV79WdGCHuaO0lrSsR508d4095ZW5x2YxcHf1lWr7NTtVDKZV776ApxNzkpq25weizQ/pLuJsXO3o8n44f9Ofnnq5CbGSfKQMC4MSOuRXf5I4IPEqBtFE9EU1PLkN7gjcWkuYJQONjZ54pkCDtpfwit5pRXiD+tqe4GtVt6JiIqPMzt0l1zU+loIuQuU7Esm5QNdYT759pcYe/qvfgj84GndcZ+MqFSyLDwjiw8O64n6oxmp9a8WBf35InFy/6ZNeUaoFLI+Hfs6rmwMls4DvnFlT5Z5FsiJ6YzQeQs7ZY9nr47YVvsl6rFc+N64tOdRThRWo0vHxyCN38+3uztexnurLg3X5eAEdclOBwLpCDzZVLsyaTA/hx1hBwTB6Q63bK4qQlSS2xFTLQuJEBDAF+Waz0VTb6mR2oOzRWEwsHOk+XM5gotfyag9+dA7WpQu6VnIhbekYWn/3XQ7YDSnFQ6OoMRcqnEZSoWCYA3/3i96Hz7OtxcYe/qvTBRJpVIXPqONgWrM/sFW4EyC+9lfT3io5y7ABiMZiz4z2G3biyu6qMnFi/7Z2bvGhAdLkdcpNg1gL1jZ2JVuKuNMILfW7Hl72wYzVkl8LS92wdwffXwELz8/TGsfWgIlv503O+Wx6YEm71Qq2wi+MZfgqw5k2JPxg9n5zh7Ds6CrYQrLCYLh9NXalo9TRzhP0iABjmedMTOBvdA7ivurUBujiAU+msBnvm1dU2Mapa7gT8T0LOB2hdfM2e48s+yF5+A8wHFl4ATVien56S7jGjNK7yKmvpGJKld1+Fnx/Xk/+1uByFXuHovLNfj3//QDzX1jT5Z9zUqBZZO6ItzFQYs33pKtCSbGK3EZX0DJBI43SubvcurtZ7npwQ8s3g5a9dC14CtT41AnG1/+jPltXx7ZO+4tsGEV8f3gdFsQW1Do9sdnlhdAdBk+/Znf+OP5XxP2rtQNBuMZlyorMOM3HRU1ze6jdRujuXRnWATHiupqkODyX3f5q8+PNA7OgGun4OwPTvbBpSdQ0FJbQMSoEGMsCNmg9yAtBhoVHJU1hpxWV+HGJXSYV9rtvNKIPYV98VS4avlTeivxfDUr81boSUU1ZoIOV61BZB4E2gl/H6kMgw19Y1Qhklddqw5mXH4v/6d3N6P/bWdLU2eLqtxGFCEIulkWQ1iIxW8kPDGCi6sk5MGpbk9t7re5FZM3FZcheHd4nH0kh4fTx3o9ZKnu3r00t29kaQOd7l9rCeoFDK8t7UQ+cVVTt/XJ1MHuH2X92R3dHltZ/XRuouZa6rrTUiPj3TrdqGQSV1GETtbvnYXoLf/XCUqDSanWQjs34s/J2n+EESetHd70ayQWfNb6jwMYmspWJvpl6r12yYa7LrOJhItlcvZVR/obiLz0t29+fpGOUPbPiRAgxjWEbNB7ss953B9qhZ//6814Gb2yEzkF1c6baCLvj3CiybhMiIApMao/FK+5lgqfBGE8/99CDsKy0Udszf+fp4KLVfbxy25t4/T3VPcfV8oUNg7Y75mzpaun99Q4Pa5eSL47QcUf1oShOLAE/HvTkws3ngUP84dBoPJjJe/P+rTQOPPjQHsB2iLhcOOQtd+xoDrZfOdhVex6NsjWOHF8uVpN8FJgPV5uhPdi+7q5dV2n4D7pfMZuelYuP6wR1HJzXHnsMdfgqip9m4vmvPPV1kDjlowWAtoesWItRkWYAmI/XuH+fBM3fUbLbFa5q4PtP/9FG2EKKh0Rm46pt3YBYlqJQUltXFIgAYxrCNmg1x2WoyoEbvzf9x0rAwLbu+J5ZOyrVaM9Yc9Fh+ezlyba6nwxvJWqq/nLTVCXzZP8jN6gytRvelYGRoaLVg+KdttIIT99+0FCvM1+9s3BU6/7+65eSr47QeU5loShPWh0cLxn3si/t3tu24wmmE0W1BZa2zWkqc//JidDdAsxZGrdpZ/vgpD3Syb7/BykPTUiuhKdPuSfihCLnNZHm/TRflrMtBcQeSpS5C9aGZt8+cjl13W62HNXD1yFbTWP00Lg9EMdcQ1S7izvK7KMCnSYlXo4MWksal+440/9PPrallTfaCz3xeez+rcyin93f4OBSWFPiRAgxjWEbOBYEZOumhAaMr/UV9nQlykwrqk4aH48Gbm6sxSIVzqvVprBLx0Gnc2eADAhco60fXDJBI8fWt3hMmk0NUZsfiu3jBzHGobGn1KzM+wH8Tt/fsu6esBwOX92H/ffhBnvmbucNWxllU3eCQw7IWML3kndQajaJ/xA8VVmJGbjjG9kvhzmpucHQDMFs7jvJ0thasBmuGqna3OK0JuV+e7+ADeJxF3ZkUUChSrT6dR5DohxJ3YB5ynH3K3zNsUzt6LPyYDzVnO99YlyCFKO1yO45f0mJ6TDkBcr3Mz4/DaPX0AwKfE8Pb1TNi/CgPAvvzzYP7/7fO6AsCWeSOa/C0hTU1Mahsam2W9drpy4KYPtP/9ytqWS6dGBDckQIMY1hGzAdB+IGyqgaoj5B6LFsD7mevCO7JEnzd3qdfV0vfTY7q7vX5OZhxeGd8HGfHuU7R4u3zty/3Yi3Jn4kUh875jLamqQ3GFwe33hJkNhAOKNwnI2W8xcZJfXCnygQTACxZ7Cw0ApMWq+A0AgKbFhMHY2KyBxh8J/V0N0MzC66p8BqMZBpPZ6TFhSiUm3rNTtThbXovUGBWS1Eqn5RQKotoGE9QRCixcX+BRhLov6YdcLfMO7xaPTjHu22tLCQBh/fXEfYjVATPHYbFdCiugaUu/vWh+6e7eeGFDAQalx2L+2B4AgDqjGbGRiiZ36nFXH+3rmav+ddeZq6JcmcJJMABYOM6rnKRNuTTo60zISPAtJZ+7lQNW7kiFe5mhr290+rk/0qkRwQ0J0CCGdcRnbZYN+/2kAWBYZrzTIAIWkHCivNrtbwjFR1PWOyHbT5VDIZOKxIUnS73sd+w7aFdWqO4d1LhQWYf881XN8p10Zn1gnfqxS3rUNjQiMVopGsSF92NvCT13tRYyqQRJ6nDR79iLAPbOhN+PjVS4fG/uthYUBl85QygIhEKmodG5SHL2PeFzmnZjF6zYWijygWRiFAAvQtnuWUsn9HVYGmzKN9BgNGPriSs+LXn6K6G/qwGaWXjZnvTOyndZX+82pZKrACZ35WSCSGcwWsVOofs666nYd5Z+yNkyb0Z8JDpowvnvtXQgI8Pe9efvf+gHg9Hs1n3Iflcoe/HJ8MZnMEUbgb//oR/vusSu6c7n/oUNBXjhzl5Y8M1hl/XRvp656l9ZvZNIJPwEoTn+255OTLy1XrtbORBO3plwdlm+COcyxB/p1IjghgRokJOijYBMKsGwbvH8jJANal/sOYepOV1gAedgvWABCd6IFk+sd0J0dUaRuHAnWJuKqK0zmp12ZKzzcuU76S66W4hw0HVn2RRmD8hO1WJ1XhGevKUbbuvVAYs3HhGdz4IBhOmwwmzvSrhTzcgeCZg8uDP/e/FRCnw8dSAAOGQvcLe1oKdRsfZWmLgopcdCQhj4JrdZaoXv1Z1g8SRQqLbBBG2EAhZwqDQYIZVK3C55LrmnT7P8YT3B1QDN7vWnucNc7knfVBLxJ0Z3w2c++t96WmeF25Z6m36I3afwmusfu5E/99V7+jiIqlt6JmLRXb0cUj01RxA4m0wsubcPfjh0SSQqVQoZ+tosybUNJrz03VH+uLC/cpYay8Jd81/2BHvXJfv+zX5SueA/h9xaX1k9a8oyyOrdhlk5UMikeG794WZFgvszQ4EQdysHQmNBdlqMy37rlp6JiFKE8RZf+/cWrZRhqW18aG6QIRF8kAANAZLU4Vg6oS9e2FCA6TnpGNennm/cv56pEIkBbYQcmYlR0NWZvBItgGvrnRBRB2HmUG8y4w1bvsWrta79/ZqKqH1idDenvxOpCEPe6XJkp2kdfCe9WSIXDrruLLXC7AGNFs5qAdPX48WNRxzO3yEYBGqNZtHWoNZdZaogl0mwcFwWnttQwFtSX5vQF8u2nES/NC2m5XTh31vnOOfBBazsrnwuhVGxzoIcPps+EI/dlAkzd22i4sq3kG2vuWxSNmRSCQDHiYg7weIKZl25VFXH59Zkz2PZpGys2XMO2WkxonrcOU6Fji4yNvgzd6G7AXpAZ2vaMwB4+e7eqDU2wmA0QxMhF1kfnSURVylkGNUzEe9sPuVTOYV19qHhGQ5CVijGSnV1Vv9fQc5PVhYWRMh2OYpSuu/2hbs8LfruCPqlajHtRms9jVXJ0UEb4RBtL9x5yVuXCFeTicRopcj6+/CIDH4iyCakwv5EuNrgrF+wnzC6w1782wtGNolkqcM8sb7GRylwS89E3DcorUnLoMFohlQiQaOFa7ZV158ZCoS4WzkQGgtcbYCw8I4sDEmPxaJvCzAtJx2KMKlooi4sp6s0YkRoQwI0RGDLQldrjeikjeAbt70YUClk+GHuMN5f0BPRwmAdZPcOaqdLxe4E39IJfdFocV2dmlrO/9vt4qTkwuUbdg/2EbveRHcLxbWn2QMqao14bkMBZrhJuL79VDmqDCY8J7COzV2Tj4dHZOCFO3ph8cYj6NNRy39fWOatx6+I7nnhHVkY0DkGNQ2NosGbld1gNOOZdYewdEJfPHNbD9TUmxEVHgZteBg62PzP7AfyGbnpeHfLKeTb/BBn5KSj0cIhPS4SizcecfAtfHZcT1HWBXc+kAxPfQEv6+vxvxNl2Hj4Ev88hBbVGzPiEC6XQRNxzcrRUrkL7Zd7l9zTB9sLy5EYrRTteDTyugR+cuFMcAHi8qXHR6LWaEaDyYIZueko0zc4/LangXpCi5m9kG1q8sUG65KqOodNCZbc20dkpRfCJqXCtGebj5XxAvD2Ph3w3DeOE8n95ypxrsKA97YWOlj1m1oqthd7D4/IwM3dE1FvS8TO7lU4EZw9MtPh2R6+qMOwzDj0s8sWwtjhhdVQuGGE/VIy2z1KuFuSpxtiLLqrF/667lCTlkH2Hk5fcZ+ay9MAPbYKUWUwodbYiFqjGdoIOe/K5Q5XbdDdyoHQWGC/atJo4XBdYhSe33AEidFKbD5+BbvOVGD5pGyfVwuI0IQEaAjBrEj5xZVOj6sUMiyflI2F6w9jmm1JEwCOlOh4Z3qD0YwwqQQJ0Uqn/noL78jCgm+sPles8+XAIa/wqlvB97+TVwAOPkXUqhQyhMulGNYtHgfOVYo6ooFdYnFDmhZz1+Rj+aRskSBmQtKTnWiEVi5PsgdkJEShrLoBOwuvYsrgzm7PrzU2OmzHaDJz/GA5SfB9Z+JXaE1xFmwi3BbytQl9sdpFVgJnbgzC32P/nT0yE//Yfdbpe7ytuIpfPmauHpf19c0OBiipqsPZ8lokqsMdrsMmUavzivDj3GFotHA4e7UWGoPJ6SYLvuQuZINoTYMJGltgj3Bi9em0gfjh0CUcKL4W9JIYrYTBZMbzG444+Ou6Elxs2bhfmhZDM+JQbxek5I3Vnr33vqlaB7Hlqb+1M8vi4o1HsXraQEhs5wvL8PqEvgCAS4K0ZyqFDO9N7o9wuRRl+ganFrkZuem8VdtVeZqy9Ap/553NJ/HkLdeJ7nVGTjryi6swe2QmxvRKEj0TlUKGfp20GJweCwsHt5NdT6yGrH4JnzMTjNlpMQ67JXk6Sas3WUQp2VwFgL0xoS+q6xt5Ed7Udd1hn9FiR6HjKghLAWU/ESqpqsPzGwrQw2aUuKSrR5lKjrRYlduVA41duYSGktkjM/H/dp/FjsKrmDQ4jT8OwC8+vEToQAI0xBDm7hMKr0YLh/T4SFyptg4Q/dJiRL6Hb2+6Zj3JzYzDa/f2FV1TGEXKOnl23flje+JpjoNCJnEQfI0WDimaCEilwB9W7XbaoeZkxqGji4haNiC/vPEoZuSk47GbusLCWTui+CgFRvZIxJD0WCzfVog5a/Kty9s2n9eGRovDgM7KNjQjDpUGI85drYWx0QKDsREv3d0bz28ocBoYJBSu6ghr51nTYI3ObGpwqTU6BvkIhZ/w+0azeEBxZk1hCAfv1yb0xS8nr7gVHfZuDIBzy4w7C/DijUfxjxmDAFyzXAituTvsBkpP07TMX3fI7c5J7D0+Z3PTsA/4sA/A6ZoQKbLiuYsUFrolOAskmZGbjmVbTzkNGLIurToOsK4EV5I6HDsKy3GsVI/h3RKw+8xVkXj3xmovDEKssxOynqTWAuDUymkwmjHjs3282Bf61tUazfihoBSJ0UrRvV7S1eH7w5dcTsZ8SfXFEIo99jvZaTE4fEFnFXy2az8wtAv/frI6qHH0kp5/tjNy0/Fx3hnkF1dh1f03OP0dVkcaGs28O4IrFwEmroT3JVyJsd8tSeifb983cuBgtlhw4rIeesO1iG9n/tRd4lToqI1ATUMj5v/nkEdWUnfYZ7QQtidnKaDsI/qf31CAiTaXAWH/auGACLmU71PtJzKd41Si1TRh/5rT9Vru3HDBqpa32TqI0IcEaIigMxj5qEx7ccmCHf65+ywm2waItXuLsebBIVj0naPvYl7hVfztm8Mi30UWRXrARdRuTmYcnhx9najjWru3GB9PHYjXfzqGSYM7u0ycnH++CjKJxG208M7Cq+jdSYv9ZysweXBnkTCzXz6eP7YHLBygkEkcItVZ2dhg8damk/z3B6TF4Okx3RGtDMPonomijpWRmxmHiQNSAVwbGJtKB6KNcLRCCDtT4eBkn9rG072nuyZGYUDnGNFgIWT/uUqobL59QjGWIBASzsomhPd1U4Y55j/V1WNaTjqm52ZAHR6GGFu+UU8sEmyJ1V1AnDBq/MlbuuGWnsn8e3E2yXhvcn/bZIUTCUe2ZzsAFFcYkBEfKbJgOhNK7DNnOx6xZ2X/PFJjVQ7XUSlkUMllvJ9vo8XiYOVqKlCvymByWO4Ml0uxy07IOnuH9kv7EonLxw2D0YxKgxHXp8Xwn7nKtsBE/c7Cq3y6LXuaIx6EYk/4O2zCyeigCecnajNy0kXPVvhcTWbnz8abaHIm/o9d0vOfsf5t1f03OExKV+cV8dbbFdsK+bK9vfkEJg/ujC/3nMPkwZ0d3IjsXahYjs9zVw1Os06we3GVG1aIs4wWDE8mQuU1RvTooHbavwrb5sI7svDsuJ6oM5pFQULC1TRGbmYcbrougf9ufJSCD0CivJ/tDxKgIUBJVR1+OXkFGw+VYGfhVRworsLah4bwnbHQR2x6Tjo/AF6pafDKd7Gh0eJ2a8FZN1n4YIh8uzKwJX9niZMB4N7sjk4d4W8U7CTTp6MG72w+hRm5GQ7CzNk1f3n6JtH3hWVnYsKZVUulkGHdozfy2z/ai4vzlQbIw6T8wNhUwnWVQuYgroWdKfv+uD71vFVHuJuVp3tPM4usM2bkpiP/XKXDxGT2yEwH8ewquIw9J7lMgk+mDsCKbYUOk5A5I7uhW2KUT1sr5p+vQoom3KmYZ76+bBC/pLvmQ2ZfJx8anoFP8s7gN9vEYv7YHnjDNlFpyoLpTFCqbMElQhHDjqfGRjhMbGbkpiPWyf3PyE2HmeNEPrTZNvcRNoFSuYh8trcAM5hfrn0dDLcTMs5E+lcPD3E4R2TxV8hE+STZRGHSoDQcvaTHyB4JyErRIFIZhopaoyj1G3NVGJBmDdJSutlRCXAvHoRij70fo9nC+zz/Y4Y1Mbux8drydf75KtGzFQYIOZsw+rIbWIo2ArV2bc7qXmPh/U3ZuzIYzTh4oQr7z1Ygv7iKdyNi/qjZgv82ZdEsrzHymzM485905b9tL6SFvrX2EwRPLNb6epPoPGfP0GA0Y8F/DmN4t3jRM9QZjHh2fYFT48djN1n4672z+SSm5aSDg+uJPhO51smme8s1EVqQAA1yhFYJYeBGec217QuFwQ7CFBje+i4qw6QuOyaVQgZjowW39EzCO5tPYfbITJFAtO+QhQzvFo84W4dhn+yYbTsHgF9Sj49SYGhGXJPCTFdnhEIgpoRlt7dqCd0KGhotMFs4l7N6wBqk9fqEvrxotk+43ikmAsnqa6mH7NPV5J+v4mf2bBD5x4xBeGD1XpGQYFZi9ozduQTYp3ERnqcOD8MDq/eKJgWAcz8zYdkYwsFlYJdYrNxW6HQSIpVIsEJgleLfhZsE3KzcTGDOvjlTVB5hGdgSrNDS1j8tRiQMhQE5K7YWIjtVyy/bCwdIYSophjJM6vDOWeJsoThlx8Ok1iwG9pMZYQQzex9jeyXjpyOl/Pac16xXYkHsDHcC6bbiKgzoHMPXwQdzM9A5TiV6h8IoeeYLXiCY7DgT0cowKS5W1vGJ8dlEIVwuw9q9xfjiz0Ow9KdjGNMrCfVGGZ/6bUZuOh6Td8VHO87g+lQt/v7fE81aKtYZjKg3mdFRG4GLVdaJR0KU1XI/cVAafj9fiZzMOFypuebzea1eF/F1wPHYtTomrENCWCaBUn09Llc3wMJxMDQ08hkFVAqZQ1spKNFhaEas1d9U8Bt9Omrw4fYzWDYpG+FyGXbYJubCXexOlFbjiz8PweKNR0TXzM2Mw8vje0Ojsm5fK5wkCif1T4zuhq/3FaNfWgym2VaZWD/xwoYC/P0P/fjgvQqDkb9HoUuFs3ZhD9sV6pKunv/MXRoq+13inGURYG4JiepwDBO4Nxy6oMPSCX2RrFFi/PUd8eJ3R0TfXT1tIN7bWujRZgxEaEECNMgRWiWECIMbslO1kNjW21bnFeHrh4fib98UuFwuY9j7Luafr3JIDSJMf1JwsQpmWy49oeVOFAAA19H2Zfp61DY0or7RDLOFg1QKkUVIGSblZ8UPDeva5JJMpFKOSMG/mYAVWkT6p8XwA5JQZL5/v3WfYVcD/45T5Zhvs4wIc1hqIhQ260wjqupMuFLTAIlEgrd+Po5pN3bBX8d2R029GdqIMPzhhk5YuN7qH2UwmlFW3eBg0UiIVuK/Ry+LLJdMIGSnapGdqoXJbPVntE/jIvTJGpYZL5qY2Hf6z4ztySekj4tU4I8DUvHsN4dxwLbTzJheSQ6WaGc429+8qf2tYyMVvL/mrC9/w8MjMrDgth5QymUwmqyWrujwa/WAieBhmXE4UFwFlcC69tDwDIeAHCYchQMkC+wy2FmwDl/UYaHdhgbM8sKsisI6MSg9Fn07abDgm8MigcsEFxOZX+45h9yu8aLtOYXv+sHcDGhUckSHhzmNQG/KL/eHucPw/IYCflL11f5iLLT55f5WXMWLciY0w+UyLP7+GC/EBnaJxZo95zAoPZb357Vfin52nDUTBcdxeOqW6/DSxiO8L2ZGQiSWb7VOSvraXGWuF0SbO1sqBprOGWrvn8ss5IowKe//yZbihcvX9u1IWMfsj8kkEkSFi4c6Yb/2+k/HcH2q1qEfWHJvH2w5epm30LFjnC3I6YDANaih0YJIRRhfd6bY3IiY0GN1dOKgNCz96RiuT4vBdDs3pcUbj+Lvf+gHdbgcW46XOQh6lUKGW7IS0bujxqmL1PScdFTUGnm3qmk3duHrw8nL1cjJjMOJ0mqn7YJdn/UZJguHMJlE5F5kn2fVnUuDsywCrB9+9YejmGpz82CrdasFk6cZuel4ZIS1/0+IUuI5u0BEgCLj2wokQIMc1pDtxZjw340WDh00SuRmxuG34ip+qdZb30WWv43BBvFjJTq8vfkE5oy8Dpd0dQ4zaGEAgLBDVsllCFfIYDA14lx5LUp0dVix7Zpl6K3NJ0WWk/zzVbz16IGhXdyWX7hDDlv+VsnFKVNUChnfodlbxpgvprNlV6FlscpgQud4q8yVSSV4bv1h3k/29Z+tlp+jJTpMHtzZITp9VI8EvHpPHzQ0WlBdb+IFjn1E6NESHZ4YfR3v7yrssB8ekYEktRJXahpgMlvw7LgsPGtLTO0sRUy9yexycMjJjMPiu3tDKZfh+Q0FGNAlBgvHZWHxxiPI6qDmz/Mmobe7/a0XbzyK2SO74rZeHTDL5q+5s/AqPvjlDHqlaETvRGidFk5oispr+UkPs37aC1DWFoQWTOY/zITsDtvz6tfJGt2+QLChAbPMJqutbUhYJ3qnaFBcaXCoK+w7EQop3ttaiH5pMTBzHAxGM+oFO08ZjGaszivC9ZOslkL2fi2CnKzOsJ9AcByHl+7uBYPRDA7AjwXghcxfx/bgn4lQALEl7L//Xz90iAlH744alzltmaV1eLd4yCQS9O6kwQLbJHbOmnx8/fBQvs7lZsbz7j6uNihotHDonhgFTgI8s+6Qg1vBaxP6IlIh41M9WfsUCQZ2iUVGfCQqaoz85gTs2vZZMITt6JaeiVhiy9/LJnxsh64l9/bBuavXtrFldbSipgEvbTwiEtJCrCmCyrDrzFVRv5YaGyGywLNr/mPGIL6OPDSsqyiXLquj7LgwBZuQq7VGhMulOFaic9icYUZuOswWOJRVpZBhUHosUjThsHDA/H8ftAaipmr51bD84iq+jr/8wzEHi7UzF46HR2Tg7n4pTn00hT7bwrYbLpfhl5NXMKBzjOg8oVvUzkJr/uqvHh7i0Dez97ZiayGGdYvH83dkOQ0CZHWWIuNDGxKgQY6rQBjhvztownlfmtv71MNssQ7YrhIAv3hXLwzoHAOOg8gaYzCaseVYGW95YoP4g7kZeOymbrikq0NBiQ6fTB0ACwfsPVslilIFwHdes0d2xdheHfDCBmuS4cv6enxvy/8oXBYXWmSY9UilkCE2UuG0EwbEO+ToDEa8dHdvLNxQADPHiSxUi+7MQrQyzMG6NCM3nffFdLbsKjx3dM9EPH9HFnaevsr74Ao7UmZldrVl5/lKAzISotA1MQo6g1HkK8oG3WfG9sTV2gaHZ/Pe5P5QKaSorm/Ekh+ty+qrpw10GlHNhBazItsPDiwi12zhMP/fB3GguAqTBqXxke3CtF3eJPQW7pw0Izcdt2YlYdnmkxiUHotFd/ZCo9mC5zYUiCYnsZEKvPXfE3ZL5RJ+CVbo4/mPGYPwv5NXMLJHAqYM7owyfYNDW2DuH6zczH84v7gKf87N4C3z2Wkx+DjvDO4fInZNYf57/+9Cleg5ABC5SNj70Vmjm8E/v91nrmJkjwTERipEy7b2g6y9O0fnOBUsgksL03KtzivCisnZWLihgL/eyin9+Tr965kKPqgDuCZwZgh8wUt0dYiNUvCpjFwJX2ZpPX2lhs/j2NBotVCfrzTw9YGtfLjaoICdt/vMVWw6dlm0XBypCEOjxYLzFbXQRCh48cnq2Qe/nMHDIzJwa1YyJry/S5SRwT4LBmN4t3i8dHdvdBDsuCWM7C+vMYqCuGbkpuPLPefw5C3X4a/rDouEtDPfYHu/9pVT+ovuW2hlTFKHQ6WQISUmHIu+PcILPVZHmwoeMzZa8Or3RzHJFrgk3Jyhc6yKv3f2nQFpMUiJCUdFjRGv/HAMM3LSccDW7gekxSBJE87njD54oQqKLrFOLdaugjn/ufscPp46EOFhVsHNJgDC/MzOJro5XeMcsgjY76jGceANDs6eyYAuMR77xxOhCQnQIMdVIAy/XzCszvlbj1/Br2cq8M+Zg7BNsLe2vVUiMyESV6qNvCh4b3J/3NY7GUnqcH6AuDUrCQcv6Hgfz6dv7c6LWo4DVm4rxA1dYnFcIBAZLEI5Wa3EQtvuP3+9rQdfbgAOndcHv5zBjNx0TMtJR1R4GL8MP3lwZ6w7cB4zctL5xOvq8DBoIuToFKvic9T16aTBX8Z0h1wmFfk+fjs7B3uLKhz2a++fFoPZX/6GFZOzER4ms5U5G6vzHK0gPTqoseCbw6KBW9iRGs0WUT7SpgQb8yndL9jj+YNfzuCDP90guvbskZl8IM73gsTt9q4X7HeFFsOhGXH88/1yzznIZRJ+B5lptgFK6KcGiCc07P+zXViGhAm9dXVG/p1f0tUhTCrBxMGdUaavx76zFegcF+kQSCbcNUb4zDgO6KgJ5/2MAaCsuoH3RyyvaUC9ySxqC/nFVfy9n68wYJhtQqSrMzlY5pmbwczcDId2xtwOdp+p4EUPAH551D4h/4zcdHySV8SLWaPZGvG+9qEh/GRQESZFVopG5N4AiAVNfJQC6x65EXvPXcWwzDgcK63GmgeHYMmPx9AvLQbzx/bE0p+OifwFlWFSUQoyXZ2JLyMTOEJf8Bk56ZBIrO2PLQ0LA4jCZFJU1hphtnAwcxakxqhw3mb1ZVZ7hezaxIYJZ+HzEIooNsGYmZvhdAvaN38+jn5pMbzV3n6Xpw9+OYObuyeif5oW/zt5RTTZOFKiw7O394BKEYY6kwXVdSaoVXJIbZZGZ/uZnymvdYiYB8BbjV1NQoX+uswieHP3RIRJxatR7LmcKK3GP2YMxozcdFyx5RA+UVqN1dMGot5o5nOUCrH/zdXTBvKJ2YUTWWWYlN9pTvgdAEjRhfN9xNQbu4iux1yNAGsd19WZ+HcVJpHg6Vu745nbpJDgWvu0nzD9+fN9+HjqQKzYcpLf+tldwGp+cRX2FFXgxbt74cyVWv5ze/F9SVfvkC9UeH9l+nqRW5W9b/zqvCKKjA9x3DvZEa0OixBlQQiD0mPx7ewcfPXwEMREyPHy+N4Q9mmmRg6r84owPScdOZlx/GA38/P9uFrTgL1FFVi+zZrz8OERGegYE4Gtxy4j/3wVlGFS1BobUV1vQv+0az6eYTIJ6k1m5J+vwsAusThgG/RnDsvAl3vOQSNYyn9oeAZKdXWoMJj4jqmm3izqfOw7L2EZNx+7jBsz4rD1+BU8s+4QHh6Ric92FuHO5Tsx6aNfMW55HhZ8cxgXKw18jrq9RRW4a8VOFJXXQkiDyYKXvz+GRLXYAZ/5FEoggSJMgs+mD0RidLjDntNP3tINt/fuwAcLsc+FgU8JUUr+mDt/0mfWHYLOYOR3JPlx7jB8LjhXa9vuUejPmKQOR5Jd4nbhoM/OZRbDmZ/vx5WaBl4sfLnnHP40pAsGp8di8cYjOFBcBblASAitC8I6w/5/aIbrTQXY8pdKEYaHR2QgXC7F5mOXIYEEn+4s4svuzIIhrAtCa61EAgxMj0Wp/lrggzJMiomD0vDSxiO80GLRz9lpMVj70BCszjuDOWvy0aODGrNsAU4soE5Yv85X1CE+SoHUmAjkZsbx73P2yEzeZ9hgNPOiB7AKuaO2idbVmgYMs32enarl02oxlw7mg8vq7txR1+FgcaXDFrIMlcKaAP/FjUcQHx2OuaMy8fVDQ1Fe04DJgzsjv7gS9Y1mh8C+/PNV0ETI+WcnfH8a2+42cpkE/dNi+LpbWWvzybO5qRwt0aGR4/D3/57Ancvz8Mj/O4BDF6vAWYAD5yr4zQc4jkNuZhzvHrOz8KrNmhfPW/WYYMgvrsTMz/ejotaIHYVXoVHJ+fYQH6XAmgeH4O8/H8eOwqsYkBaDRLWSd6uwD4hjIp49+5E9ErBsUjaOX9JDJpXh2fUFmPD+LmwvLMfFyjoUXNThRKkeOlvgjc5gxOmyGuQXVyJCIeOX8XMy46COkIt83YWWc2e+wWyCNahLLJb+dBzbTlzGsMx4/vusLrw2oS8KLlo3cqgymHgL9PFLeizbegozP9+PepNZ9F17yyPLNCDsEx/74jfM/Hw/TGYLGi2c6Dusn2Dfz4iPFN2DQuAqZTRb+PefX1yJaZ/twz0rd+HO5Xm4bGtzKoUMN12XIGr3Ewel4Y2fj2Pz8St8u0uNjeDbl32dXjYpG+t/v4hxy/JEY4O9G1mYVAKDXX5b4TNJUodj/7kKfDJ1AI6W6Pgxqt5kxo1d47Du0Rt93seeCA7IAhoCMNHibDcLAPjyz9Y0JSwNjKt8nJoIuXUQt1nAyvT1eO3HY0733/1k6gDe+lFZa4JWJeeXyO0tS4owKUb3SED/LjEY2SMJFyvrRMIjKjwMBuM1p3dhtL1wdssByIyPxBXbTJ91fPb+Tv1StagymEQ56th1GTNy01HT0ChyK9hhW2piqXL++etZPDm6OwouViHRZiVllo7be3fA1ZoG3grJoqffm9xflIJHGSbjO1lngSTC+ztZVoO4SAUilWGoM5l5v8Rlk7Ihk0hEVjZXS3XAtTQ4idHXBvAPt1utyL1TNAiXW5+vXCZBuFwKswW81VMmlYiWaYX3nKJR4pXxvVFnsqC2wQRA4nAPwmVUo9kMiUSCW3om4RWbXxnzbWQZGJwFkrF6xQY7oTW8T0etw/2yVFszctJ5aygLohFGwC/96Thvhfqh4JJjQJ3c6hu65MdjDntPO4uiVoZJeReJdzefwMM3ZaJLnAq39emASGUY78rx3LievEsHs1AL6+7jo69z+hzTYlXQ15mQlaKx1cXrcElfD5VCxvtKC/1t2Xsa1SMR0eFyfvlSmO5p5eT+WD11IJZvO4XrkqL5d9BoM70xNxWhdVtocXrBthGFMFvBtJx0PsgKACQSYPbIrgDAW92Fy8Vs6TrMtiLBhPaVmgZeaGpUcv7ZMUskez7MYvyrzQoYJpHgmdt6YvF3Vgv+SxuP4ERpNb58cAi/FzuDucw8u76Adw1Z+9AQ5GbG4XhpNUb1SMbV2gYYzRYcKbEmsuct/nbtV+jnW3SlFhsPX8KJ0mq8cGcv9E+L4ZfDjeZrE+oTpdVYOeUGkSvMzNwM/r7t3Qjs0xyFh7lOZ5V/vgodtRH8e2eT4er6Rv77NfVmUX8pXNlIiFJCV2dyOklmz59Z1IV1LUwqtYt+lyI6PMzpNrP2Il5owXbmRuYsLRt7JlMGdwbHAZ/sOIM/DekiSs1Wb7Lg9+JKqLslkA9oCEMW0BBBo1IgLlKBRd8e4YXL7JGZ+GTqAEQqw/i0FmznFTaDnrMmH0cv6SGTSGDhxNbHZE0EsuyCQRgyiYRPEswGr+w0LQwms4NlacZn+/DX23ri5usScbGyziG1kHULv3remsAQWk7mrMlHYrQSu85c5RNJ28+w46MU+PLBIThYbN0GUXhcKM4A6zI7CwD4cPsZTLVZ99gzGpoRh6wUDfT1JiSqwyGRSPjyJEQpse9sBZZvu9bpsiXNS7o6HLxg7UjjoxRoaLRGcOdmxol2OWIW1PWP5eCgzTI0dfVenCmvxbyvf8eZ8lp+6f/znUU4X1knsLLFQxkm5f+Ez4qlwflk6gCcvFyN58b1xNVqo+g5llVbB4abuydixbZCfjn6051F2H1GPDiN7JGA9yb3x5D0WOjqGvHs+gLc9u4OPLB6H5Ryqegdzfx8P57fUACNSo41e87hYlU9KmuN4LhrSdbZMiErOxt0hM8lPkqBUTaLlrBsVmudmS8Xu1+pLcND/vkqzLvlOj745pOpA3jLJasLLG3P0RIdb2Fj7aRjTASq6xux1WbJmTK4M2+FZr85e2QmVk7uj6RoBZ6/oxf2F1Vg/MqduPeGVCzbfBI1RjO2HLuMSKUM2alavPz9MfTppMHL3x/jLZD2dVcZJuPvhz3Hx774DfUmM6rqrLkWrXWxEbo6E8JkEn6SGKG4JtaZFW7Jj8cx4f1dfCAgs34OyYgFBw7vbbPu0KS0iZn881Uo1dUhJzMOEomEf1fMR3jtQ0Pwuc3ixMp86GIVosPDECaTYu6afGSlaPhI8t4pGuw+U4HlNgtdj+Ro3mI7Z00+FGHWtlRny7Lx0PAMVNc3otF8LZhMESbln52wfh8t0fHWWta/TPtsH85XGLCj8CoS1Urk2/zT3/j5OO/v+MnUAVg5pT8eH3UdnrWlQ1MprOmoltmsqSsmZ2PpT8cQpQxDB3UE/9yOOnElYjA/X7aF7NIJffHid0cw8/P9GJQeix/m5iA9PlJkBW20WHiLcb5dFgdmHMi2q78qhQw3d0+AVApRexFytESHnIw4hEklosmwMMDpkv6aSGOW8Bfu6IVhtswCEQqZqM+cPTITn00biNRYFRbekYV1B84jRRvB9wnV9Y18aiyVQoZVU27AmF7JuKyrR7Jg0s6uc3vvZFGfvXZvMZ6/oxdG9UgQlYXV2w6aCMy+OVN0z2zyHS6XoU9HDfqkahEul+L7w5f4tjPjs33YePgSzlfV8VZvIvQgARpCCAM+2GA2f90hSCTArJusFgnWqY7skcALoOO25TaT2SoM+6fF8B0jGyiFA/XKKf3RKVbFL4OV6upw/JIes2/ORKnuWmfEzv/ogQE4cLYCFYZrEftMeMzITcdb/z2BG7rEYq7t/C/2nEOiWskvE7Ol1Jr6RiSpw7Hr9FWRPxv7PTboHCutRmpshIPv1r8PnMdTY7pjdI9EqOQy5BWW8+mJWKcfqQjD2r3FkMusVkJ9vQkNjRZwHMen5xEufbP7WJ1XhD6dNEhSh+Pl74/hz7kZ+OeMQVZB/9k+PD2mBzqoI0TlSYhS4kXb0veTt3TDhtk5vOCJVIThvcn9+aX/MKkEc9fkIzE6HLNu7ooqgxFl1Q38Uijzk9t6/AoOXqjCe9sK+QE8LkopylPJni9wLWk5e89r9xbzufPW7i3Ggtusovr0lVqsEOT+fGh4BgpsFirRMupDQ/DGz8fRg01cTl/lsy40NFp4i93hizqU6ev5wZ1NPpggeHz0dbz7hrAOdoqxCoMnRl+HT233y5bp2DvYevwKVucVoaBEB62KLTlfG4Rf/t5q1T9VWo3VUwfwwqih0cJb5g1Gq/WWrSSs3VuM+WN78kvThy/q8awtKTzbp7pHigaf5BWhZ4oGhy/o+OtcqKzjI85ZmiVh3awzNvL3ky8QTBbO2laYH7GuzgRlmBSVtddEOceBf/+ltiwSOwuv2va1b+TLwJb8lWEyfoLKJpBr9xajd0cN5tzcDZzt/TRaOL4PYdv3Cv1K9xZV4I7lO6GvM/FC8KcjpXy77NNRw+e4lUgk4sA5uQwLx/VEoy2yKjczHlV1JsREyvnrVxlM/LNjkzu2W1CYzHELJ/Y8a+rNoiAz4cTrVFk1ZFIJ397WP5YDlULGLx1Hh8uRlaLBO5tPIipcxluNs1I0CJNI0EEj9hVnfr66OhM/uUxUK/k20rejFlKJBPnnKvnzP91ZhF2nr+JoiQ4yiYRfcREiNA5Ehst4Mdlo5nBJV8+3FyEjeyRg3i3Xwcxx0KjkfM7cgxeq+ElrQ6OFX3IXvsfxK3eiX1oM6o1mSG2rGmwyX1RWDW2kAu9uOoHsNC0evSkTujqjqE9gPDQ8Awq5BHvOVGDZ1kJsOnYZo20Tq9O26wjzhgLWlYB3Np/AnFHX8ZO5fmkx+GzaQKx9aAg6aMMRH6XAy3f3xg9zc/HvR4YiIz6Sr7/AtYm0vZFkZ+FVLN96ClUGCkQKVUiAhgjCxMJCvzkWqT7j8/3QquSiwSjRJoB6pGjw5Z5zqDeZUaZv4JeHzBxn9Quys3I99sVvKK4w8JaiqjojBnaJhUwqQZhUgk4xEQ4+X4k2f7/881W4LBAeQzPi8GPBZUz+6FdEKuRYuc2agmTLsTLkdo3jLSds94+GRovIn43BBh2WyPlYiZ5PI8WE7IQbUrFsy0lMGpwGC8fhw+1nMD23C4YJLML1JjNvpWi0cOgUEwFlmBQyiQR9Oml5nzk24KzOK8LM3HTckKbFxcp6Pir44IUqVBhM2H3mKronR2PyR78iQiHlRTcTsmxQHtQlFlerjbw4SIkJxyVdHe/vyHwbLQBmr8lHv1QtMuJV6JYYhcdHZuKWnkn8Ml6fjhr8ZvPhbTBZIJNKRJGs7PnWGc2ijhywDgiHL1RhdI8EfrcsZ76muZnxWGwTuEwcfj59EK7oG3gLGguGY4EAKrk1e8GoHgno10mLjIRIPGjzEx6UHisSBDqDCZMHd8bJy9X8bzLRm52mFW208FtxJW/Vv1BZJxL4hy5U4ZOpA3hrN3s/c9fkIyZSgfdsA9eMXGsmBqFFWSVwBVg6oS9e3ngEWba2cl1StOh5NDRa+HvunxYj8i1WyKS8v987m09i6o1d+Lo7IzcdJguH8hqjg2BSKWQoKNEhLUYlygcZJpPwv7XtRBnm2t5/ot07Ys+Fvdc3fj7O76Dz0PAMvLv5JGbmZmD5pGy8s/kk9py9yk8+OmjC+YkFq+vhcseUZUILtrBdCieHbKmdiaI3/nsCvTtp+Ilko4WzugGYOV5ohsul/LNjE4u+nbRYs+ccopRhvI8ug723qHCZKMiM9YOrptyAW3omoUxfz9eN1346BolNcBmMZujrGpGdqsXW41dwprwW03PSkZ1mXe597MvfcElXL/LPZD60Kvm1tG019Wb+vV7S1aHexGGxrS4I28TkwZ1hAYfsVC32na3gryucuK95cAg/ybtSXY8oZRg/EWUW0g/+dAM2zsnBc+OyYGhoxO4zV2FstODGjDh+MpyVosZjN3eFViUXTfyFPvar84ogtflcssn8si0n8chN3fDmz8eRnhgNY6MF1fWNMBgtoj7h8EUdRvdIxKieiYhUhvGff7j9DObaJpKP3pSJN34+zrdDRnaqFl0To/GGzfeXlaWR4/DO5pPYeOgSiivqcKy0Gro6EzpowtFBE46Fd2Thnc0nRRNpeyPJ6mkDkZ0WA4PJ9Q5xRHBDAjQEKKmqw+w1+dDbBhfW0TFRxgYLuUxq3cvcNhixAWtg51hMHtwZX+w5hxRtOGIjFfxSdAd1hNPgGWG0dY9kNV7+/ih2n7mKHh3UCA+Tis5vaLTwAyhbVmHCg0XPl9cYcbm6nrc4fbj9DDQRCn4AUSlk/LItExBCh3026Cyd0BdLfzqGhOhwxEbK+ahn5krA8uvtOnMV2WlazP4yH/1snfnKKf2RGqvirRSpMRE4fEGHqzUNMHMcKg3Xlo/ZTiyANVjpzn4p6BKn4gdCFlHKBuXsNC3OVRhEwTvM3eGSrg7/2H2W75xZlKwwOn91XhH+nJuBSIUMEwel4bK+AbO+zLducSiR8EECgNV6ZV0is1oVmW+U0JIokYC3lLyz+ST/W/3TYrDou6OYa7PIVRlM/PsT0mjmeMEHAA+PyIBUKuEFDjvfYDRbgzK6xcMC66Dy+Ojr8HHeGUz/bD/2nq3AE6Ovwx19rAm/JZDYRLHVasuEHPNlXWxbyuYEViOhVT8hSikS+CW6eqzcVsi7nrD3YzCaYeHA1zfm4ykcoM0cx4tZlhFgQFoMJg/u7BA8JYw8V8llIt9iYcQ5m7SxusvaGSfYovNEaTXWPjQEEXIZOqjDceiCNaiIBTxFKa+55n/wyxmoFHKU2iKChQgDx9i7Z77Ko3omYovAWr71+BV88MsZmMwWq7uIbVtLZnVmwVn2gWf2AY1z1+TD2GjmJ3/CpXYWELP1+BVcrKzn63S0Mgz556tQbzKjX6oGkwd3xumyGgyzpSe6IU2LS7p6jOqZiJ42C+U0Oysg272L+R0Kg8weHpGBhGgFXvnhGL8akKQOR1aKRpRDVqO6JpxlkmtC74sZg/D93Fys2XMOU3O68NZ6NkExcxzv4xsVLhPdK99PcteEFzMCsPcokQCP3dxV5IYxf90hyGVSfpLXo4MaBy9YJ+9MFM9Zkw+ZVIJDF3TYf7YCZs6aEWPih79CKpXwk63yGiNmfr4fUcowPnUdW/5/8pZu2DgnBxvn5KLoSg0u6+rw3LieqK5vRL9ULaQSq3/4TdclQCKx5p2uN5lFfYJEAjx163Uo0zeIAkrZb2elaFDTYLVIdxQE+LF+wt6VihkMmPGBGT0mfbQHz28ogL7OhOttEwXhRNreSDLjs33IL66EQuZ+G1gieCEBGuQIE33bp1rpn3YtT5owclQogFQK6zZsn+4swq9nKmDhwA/uq/OKEBUucxrtzAJFHhqegU/zirDl+BW8vekU7lqxE6fLDQ6R2cx6k52mxawvf+OFR7xAyAkHUIPRDLMtYOXhEdcGKbbkzPL+sQGBCdxEtZIP2risb8BjtkAJYScntKKyznzm5/vx9L8Oot5k5q0UgIS3ICSrw/lI9PzzVkHMhMrHeWdQXFmH34or+fKx8rBBeVB6LNJiVJi7Jp8X3WyQTFKH4/9uSOUtTdm2IKqGRgv/TplVtdHC8WLbumvKcVTXN/LbcQJAiiYCV6rrsWLrKX55mN23cOltiyCjQFl1PUb1SODFE7Mw2vuaMlTKa+l3AOsymN62RMzujfHettP4c246kqKt4oNd22A04+1NpzDxw19RZ7Kgh00QzMhN54OVmJBbaAtGYc9TaP0WWvVPXa4W1e8+HTXYYXuf0235Zplwsc+8IIxoH5oRh91nrvLCkbUjFrltjzDynIka5lt8tETHW4pZeVndBaztjFnITtjSLBVc1OHAuQr0StFg8ffHEB1uFQ+TB3fG+/8rRAdNBH8ttgWl/Tuydy1h5RQG9rClckDcR+gEltLjJXr8c8YgLPnxGGQSx+XvIyU6zB/bA9/OzsE/ZwxCenwkYlTW5f0Zuen8UjsTLSqFDB1jwmEwmnH0kg7hchmOlugQqQyDxQJ8ueccEqLDMXtkJoZmxOKxmzPRSRuBMn0Db6EUWgFXTumPAWkxeHpMD/zntwtI0UYg/3wVX76buyeiwmANrmSrAUz4sInJjNx06OuMfL1ifdXavcVIiYnAc+sLRFHeax8awruTSCQS3se3tqERubb239BogUpptRq/vfkEb60TWsMT1Ur0TtFg5uf7eZ9jtnJ1SVcnmuS9/P0xkU+kcKLVo4NatAwdpQzjJxvhYdY2rTOY+PyhHMfxKy+HLujw8vdHER8djoyESPTrZHU9url7Iq5UN/C+2JW1JiREKR36hN4pGlyy1aeocJmoHtabzBiQFgMprO4G5dUNoskDm7gJERoM7MedvqlaXKiqQ6XNl/zD7WcQHS53aiQBrJbRRd8dIT/QEIUEqBPee+89dOnSBeHh4Rg8eDD27t3bamUR7qlrn2pFJb/WGQg7bqEAEg72TEyV6RuQqFbCYDTjTHmtw6Aj9B/LzYx3SANTb5c6w37ZPTtNy4vVHwou8TNi+7yBTDzd3D0RBy9YxYGwAxYOsJ1jVcg/X4XaejPfgX24w5p6yH5JUCgMhYPY2oeG8EveBqMZxRUG2xaZRmw6dpn3t1udV4Sa+kaRNZP5FrLyaSLkfDoag9EMk5nDb8WVyE7T8kFUbJBsaLQgUa3kB0MmXpnFmFmY+nTU8EFCQgtPQ6OF35pQpZBBJpUgIyEKOwqv4krNtcTswsjbnYVX8d6203x+RCkkeHz0dbx4Yu+QvTuhcGMII4QBIEIh4/8t/NxgtAYOsWdrXz9m5FoFjzAAjAUrAdZBprctGIVdT5gKCbi2xLz4+2siSTi4sfd9paaBD3QQ1jf2rCfbBmizheOXfpkQB6wpx4S+vwyrq0EYL1yF9TMrRYPaBvE9C4U0E9kyiQSrpw1Emc36vei7o6i2ZWqY8dk+zBl1HdbuKUbXxGhYLByGdYvnn6dwcmb/Oyu2FvJiid0TQ9guhH0E60NG9UzERV09Kg0mkb8tIPYjvGvFTty1Yie2nbyCZ9cX4E+r9+DpMT1wY0Ycv9TO6rRwo4dh3RJw4FwFHhyWgff/V4gwmTU36sd5Z0SBTKxeCt+nMA3RtM/2YfJHv+KJ0dchUiHD8Ut6UXo1tiQvzFrR0Gjhg2CGZsRh9pf5SNGEI1eQamzF5GyU6OpFk4cVWwtxpbqBT17f0Gjm3+dvxZVYPL43NBFyvs4MtU3ymEXc3hWGXRcAn4mjtqFR5MJhaLD+Bpu8zx/bwyEF3E7BROJoiQ5l+gY8N64nzByH+CgFwuUyvj4ma6wuPiu2FfLWYLYqUVVn5F0K2AYFgHVlRREm5fsD4WSb1cHahkY+oJQ9Z41KDjNnnThXGkyifjc2UuGw454zqyiD+XtGR1xLi7bthHUi7SolHNsemAg9SIDa8dVXX2HevHl44YUX8Ntvv6Ffv34YM2YMysrKWqU8esFOD8Kl6YXjsmDmOAerqFUMXRNAwsGeNfr9xZU4VqLHsMw4yCSOudiElhKzfeZkOFpi7JfdhaIvt2scXrmnD4Z3ixcN6kLLCQA+cOSfv57lO+BvZ+fg02kDcWffDoiPVuLEJT3UtmU0YST+/05eEVnMhFZF4SB2pVqcNkRuC3aoN5nx4fYzkEnBC+ga27Nm98+Wu9gAkahWoqM2Ao/d3JVfAmVWEtZxM8uXMkyKmnqzaALBBIUwp2WkIoz/jtDCowyT8sEJLBKfRRQzHzr2u0JrtsFo5gc+g8lq9bRfqmbvrmtCpCgadduJMsy+OZOfVLBlVvZvYXARYLW0uaof2alaqCPCeMu0TCLhMyuwcrJgFHt/Q/Zv4fs2CMSzvaX07U2n+ECHhGglL+KE+UOzUjSIiZSLrE/st1kEtv3vM5EofN7COlbrZG9toZD+cPsZdIq1RuHrbL7OwvdTXmPE5I9+RY8UNbJTtbioq8PCcVkY1i1e5NpiHzEMWDc66BynwvBu8Q7P0lneWFYuZint01HDu1YI/UqdWZ3Ye2DlbbRwovrH6iBrCxIJsOi7o6g3WTCsWwKq6xv5awgDmViZNRGuE4sbjGZIJRKkxUXipbt74/ilaqt/d4OZn7Ax2LXY3utmmx/uA6v34vk7euEGW17l6HC5y1y1zIUgLUbF//7rP53EH1bttqYhqm7A8Ut6hNll2xC2wQ+3n+GFpjDHb7hcxov0/PNVom162eT97FVrXmNlmFWgCt/BJX09MhJU6NfJOqlbMTkbRrOFr49VBhPvq2nfX0aHW1Ng1RnNvCsGy5RQUWPk+wPWJzCxvTqvCEYTh0EZsXw9zD9fBYVMKpo4C/vdKR/vQVS42KfXmVVUyM7Cq2g0c3w9FE6kXUE7IoUmJEDteOutt/Dggw9i+vTpyMrKwqpVq6BSqbB69epWKY/abqcHtrzXu5Mau89c5YWAMwFmP9izRr86rwgJ0eF47OZMXNbX8ylaGEJLSaTSMVWsvXVIKMyevrU7bu+dDE2EHN0So9Czgxqd4yKxfFI27s3uiJfu7s2njGKWEzb7Z+Kgd4oGFyrrbNG55ahtsEbHv3h3b9TUmxwsnsw6letCvLgqu3CQNhjN2HS0DGttAjo+SoEbBNZMoW/h25tO4e4VO9GjQzRmfr6fF4/2Vrgb0rTYcqwMZfp6qMPDRBOI4yV6XlAwN4Fa47W8pcdtaYRYOaOUYZi7Jp/P7ciWyIXCiiWhF8IEBUvgbL9Uzd7dr0UViA4Pw6K7euH7ObnIzYxHB004bslKRphEAk2EHNtOlPGTDBY5/PSt3fH9nFzehcLeOsrqXaOZ462BBpNZJHQAOBV2vI/enwcjOjzM4Z7s37uwPq7YWojlW05hiW3yY++S8fORy8jJjOOfFzvOIrCdWdCXTugLdUSY02MJ0Uo+vYyQ1XlFmDOyGwZ0trrLsEh3Vp+Ez0E4cD/8zwN44+fj+Psf+iEzIQo3dI4RWce+nZ2DtQ8NwfpZOfj7H/qhY4wKr03oi+Hd4h0mJUJrlbBczFIqTJvmzK9UiL0bjclsEdX7gV1irQnGbZ/VGa9Z9kp01hyn7BrCa7EyO3ufjOHd4vmAuhRtBG7NSsLi8X0QbrPMA+K+j1mstx6/wrfj85V11glKqhbLJ2Wjpr7Raa5a1iccvFCFQxfE9bm8xoiJH/6KZHU4OsepeF9Pds9mu8kVs4wKc/yGya4t6x8t0UEmlYgCoITvSyhQ2fd7p2gw/bP9qDAYsTqvCOoIBT+5BIArNQ3887UXfMZG6wYd0eFy3r2DTXASopV8fxCpDEOCWml1j6huQHaaFo98cQA/HylFglqJxXf1xrjeyaiz9Sts4mw/NrAsIez+3E00mNDWGUyivkDoauQM2hEpNCEBKsBoNOLAgQMYPXo0/5lUKsXo0aOxe/fuVikT24pTCLMYCJcUhQE7wsFWONgLRRQbzPp20mBoRhzm3NzNwXfOGsjBOQg5dv1cu47mwNlKxKgUyErRYECXWHRLiuaTBGtUCuue6AlRWDEpG+oIOX8d4ezffvePFVsL+c4lRRuB7knRSI2JcLB8CTs5oUD48s+Dse7RodgybwTSYlVOd/xhg/SH289gos0xfuKHv2Kq4JizjpWl32HikX0utMJd30mLG7rEIEIhQ67At3Xi4DQHa29HbQSGdYvny8Gs1Gww7Z+mRVm1dck9TCoR3QNze6i2s8QJ75EJQPulalbmO5bvxOLvjiI2UoEbOseiS3wUbu+djNRYFWRSCQ5f0KHeZMHonknITrXWrYpaozWIRnXtfdpbR5VhUugMJl5c/FZc6XCO/Q5Hn0wdgL//oR+yU7UorjAgRpBsWnjP9oMbg+0P3ilWheWTsvHd7FwkRinw6vg+2PTkcNzaMxGvjO+DsuoGkeCtM15rR/b18fNdZ6FVKXhLo/DYxA9/xayR3Rza6oDOMehiKwNLuyRcTnc1WWLlT1KHo3N8JJbadkNj1rG7VuzEym2FSIpW8gFmbMMKJljt37O924TQ6ihcNbD3KxViL9aE33t70ync/d5OkYhnOVyFqZxY2xVei71/d+9z6YS+oqTjGpUCXeIj0UETzi/J29cNlp7L/t7Zu1MpZQ5tW3h+n44aPjDOvv3/89ezSNFEQG1LvcU+N5nF1j1mGWXvnKXaEk66q2qNePHuXvx1WBmYu4BQoDJBabBZMJn/p7AuKWRSkYAV9pdXahr4pW22FSYbE8qq63GDrZ7dsXwnRr+5Hbct24FkdTg/WX79p5MY/eZ2jHzrF7z643F+cs0mzvbPqrzGiOVbTmLJvX2wZd4I3NozUbQbmRBWd/YXV4pW02JUcoc6IawbtCNSaCLhOM5xjbWdUlJSgo4dO2LXrl0YOnQo//lf//pX/PLLL9izZ4/o/IaGBjQ0XFvW1ev1SE1NhU6ng1qt9l+5qurwzLpD2G7zBQWsux9N/ngPv3vIgLQYdNCG4+WNx7CjsJz//PbeyXhr00lMHJSGMn29aF9xhkohw4t39cLALjEwGM3gAIxblgcAePKWbhjUJdYhD9vIHgn4y5geCJNKUNvQiOhwOeKjHPdhdsXpshqMeusXPhn76p1neV9XIcO6xWPFpGyH656vMGDBfw6JtvBj93xjRhzC5dYdioRl0hmMmLMmH/vPVfI70jRaOHTUhiNCEYZF3x7BAcExmUSCLnEqcBLgle+PYeKgNNGS5CdTB2Dm5/sBALNHZiK/uNKpn9ItPRPx6j19YDCa8ez6w8izRR/PyLUu1ynDpIhRKRAfpUCtLeBm/7lKPDwiw7aH+1EcK9Xj46kDYWhoxJ//sR9fPzwE1fWN/I45rMwJ0Uq88fMJ0bNku5rc3S8Fz60v4J+ZcGceAEiLVSExWunyHZZU1eGFDQXo3kHN7+ajjZDzViDhs722z7gEMokEBy/osP1kGR4ekYkVW05h4uA03pLK3kPX+Ei8uPGoqOxMeKgUMsxZk8+3AWHZZRIJusSrYDJzXtdFncGISoMJCzcUiHLsfrazSFS3WDk6aCOctsfh3eLx+oS+iFDIUF5jRHW9yaEcp8tq8M3vF3G0RIc/DemCcLnU4f0BQKeYCCSrwx3KrzMYXV7b2btiZWTPKrdrHBKiw7HouyPYcaocn0wdgDlr8rH2oSF4d/NJTLLtCuWsfjPs6zl7XsLvzR6Zid+LK5FXeBVPjO6GA2crsaPw2ntb+9AQvP7TcVyfFsNfS3gdT5+H/f3uLCzHt79fxAHB9xOjlbhzxU6n5QSAtQ8NwUfbTzvcu0ohwydTB8BgNFuFqt0uVmwicWvPRPRNjRE9b2d9AWuD43p3wL5zlegcp8Lkj8TjifA3NBFyxEYqoJBJ8bdvDuPoJT0+mTYQf//5BPqlajE0Iw5TPt7D/9Yzt/XAnct38te4NSsJRy7qsPHwJeQXV/HPPK/wKv9eVQoZvnpoCJbaPnf1PgFrH/biXb2sbcy2UqOJkCMx2rpKw9r+sknZonYt7CM62lwZGBcqDFhg2zSA8cb/9cW3B0twwHYt+9263LXL5qLX66HRaPw+fhOuIQEqwFsBumjRIrz44osO12mJCmw/+ESFh+Ev/zooGgRdCbBaoxkvbChA704am6A5Igossm/ETKixweu9yf1xSVeHJHU43/mWVTfg5usSkOxjw7f/jRWTs/FpXpHbctnjrANr6ju+igedwYirtUaYLRzMFmuKorhIBRZuKODvwVnHbV+ey3rr7kH6+kaow8MQE6kQpWNiv8XKoY6QI1IZhpr6RtQ2mBCjUuBv6wtw7JIeq6cNxJGLVssPey8VtUYMTo/Fc+sLHO7xjQl9YbJwXj8zV2Wzf0buni0H4FyFAR9uP221kNsEqkJmdQ3Q2gQ4AK+v748ByNUzdyX2vBGDwu88/a+DuG+QVXz3S9Xi5u6JAIA6oxlalbxJoeXrPQnLyD63cBxe2ngUxy5ZJzcrtpzifVAbGi3oEqfCkh+PO0xm7IWASiHDwjuy0D9NizqjGeoIOS+c9p+rdGjb8VEK/GPGIH5iLBQZrP9SyqXQRii8mtTaTyYAsRi2F5Fam5tQncmMF787gp4C0aSJkKNzTATqGi245e3tLn9zy7wR6JoYJXretQ0mqCMUeH6DYxtk/YyuzoS/fXNYJKaE5y0XTLqF19VEKGCyWCCXSfHsN4fxmy23bJRShhVbC0Xv5L3J/flJzonSanw8dSDe/PkE+qVpeYEcH6XgPxdOEoTv05P6zdqmcHIPND15cFZHhZNw4bVSYyOgiVC4bZfNgQRo4CEBKsBoNEKlUuHf//43xo8fz38+depUVFVVYcOGDaLzA2UBdYU3A7J9J2Y0W9xai5xZUHwdGDwpv6+/4asQ8PY7LXkPvv6mu87e3T368/7taep3qwwmBwuKN7/dkmUPBO6syPYWokCVx11dYmJA2Mfc0jMRi+7qhXqTxe17aKrPAeAwqbNftfAF+8kEE8Pu+klXE0PhRNkee6HorhzOnpEvE2gh7PsHzlVi9siuuK13Byy0W+F48c4sDOgSizqTGfUmM2IjFWi0cJBIJNZtnf3Yb/mzbbZGOycBGnhIgNoxePBgDBo0CMuXLwcAWCwWpKWlYfbs2XjmmWfcfrc1KnBriQl/EeqCAmide2gLz629EmzvrqnyBFt5faE59xAoy7svz1b4fU2EHEq5DPo6k9sVFn/9dluDBGjgIQFqx1dffYWpU6figw8+wKBBg/DOO+/g66+/xvHjx5GUlOT2u1SBCYIg2h4k1to+NH4HHscwx3bOfffdhytXruD5559HaWkprr/+evz0009Nik+CIAiibaJRkeAkCH9DFlA/QjMogiAIggg9aPwOPJQHlCAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggotBWnH2GbSun1+lYuCUEQBEEQnsLGbdocMnCQAPUj1dXVAIDU1NRWLglBEARBEN5SXV0NjUbT2sVoF9Be8H7EYrGgpKQE0dHRkEgkfr32xYsXkZWV5ddrEgRBEEQocv78eb/u2c5xHKqrq5GSkgKplLwTAwFZQP2IVCpFp06dWuTatKxPEARBEFbUarVfBSgAsnwGGJL5BEEQBEEQREAhAUoQBEEQBEEEFFqCDxHUajVycnLQ2NgIqVSKwYMHY8+ePbBYLE7Pp3Pa5znBWCY6h86hOk3n+OscqVSKESNGQKlUOv0OETpQEBJBEARBEAQRUGgJniAIgiAIgggoJEAJgiAIgiCIgEIClCAIgiAIgggoJEAJgiAIgiCIwMK1ILt27eKkUil3++23OxwrKiriAIj+unbtyi1evJizWCwcx3Hcjh07OABcTEwMd+zYMU4ul3O9evXiOI7junXr5vB9b/9kMlmzr0F/9Ed/9Ed/9Ed/9Bfov7S0NJ++p1KpuPvuu4+7cOECx3Ec17lzZ/6YRCLhAHByuZwbOHAgl5eX56DfPvvsM27AgAFcREQEFxUVxQ0fPpz77rvvvNaILWoB/eSTTzBnzhxs374dJSUlTs/p1KkTevXqBQCYPn06XnnlFaxevVp0jsFgwKOPPoo//vGP0Ov12LNnD65evYqMjAwA4LfNkslkGDNmDFJTUxEeHi66hlQqRVpamugzs9nsl/skCIIgCIJoLk8//TQUCgX/744dO2Lfvn0AAIlEAqlUipycHEilUhQXFwMAZs+ejZtvvhmvvvoqAKv2unTpEp566inI5XIAwE033YS//e1viI+PR3JyMq5evYo333wTAMBxHHr16gWNRoMlS5Zg7dq1uPPOO7Fv3z4MHz4c69evF5Xv4Ycfxn333YdDhw5h7969yM3Nxd13340VK1Z4d7NeS1YPqa6u5qKiorjjx49z9913H/fKK6+IjgstoD/88AOXmprK3XLLLdyoUaO4xx57jOO4axbQBx54gJNIJNzatWu5+fPnc9OmTeOkUik3YsQIkarv3LkzN3LkSC4pKYkDwPXv358/1qtXLw4Ap1QqW33WQn/0R3/0R3/0R3/t80+r1Tp8xlZkDx8+zL399tv85yqVitu5cycHWK2SALhXX32V02g0/DlVVVWcSqXiFi9ezAHgtm3bxnEcxz366KMcAO7//u//eO01b948LiYmhuM4jqusrOQ4juPi4+M5ANy3334r0mnPP/88X96amhpu9+7dHABu2bJlDppv3rx5nFwu54qLiz3WiS1mAf3666/Ro0cPdO/eHffffz9Wr14NzknK0fDwcNx2222YNm0atm7din379mHw4MGic1JTUyGTybB9+3bcf//9WLt2LZRKJa5evQrAavkEAJ1Oh/z8fFRUVECtVqOoqIi/hl6vh0QiQXR0NAAgLCwMERERLXX7BEEQBEEQDmRmZjp8xlZk//GPf+C3335DWFgY//lTTz0FwLpXfVhYGBITE9HQ0MB/d9OmTbjtttvw66+/iq5ZWFgIAIiJiUFDQwPOnj2Ln3/+mbewarVaAEBtbS0SEhJw5513ir7/+OOPAwCqqqqwadMmrFmzBlFRUXj44Ycdyv/UU0/BZDJh3bp1nj8Ij6Wql9x4443cO++8w3Ecx5lMJi4+Pp5X5Rx3zQIqlUq5yMhIXv0PGTKEP4dZQHNycrjx48dzcrmcKyws5FQqFafVarno6GiXM4zhw4e7nYFIpdJWnwXRH/3RH/3RH/3RX/v+CwsL8/hciUTC+2kKP1MoFPy/ma5ypXOefvppkV4LCwvjevfu7VTLJSQkcAC4pUuXcmPHjuX69evnUvep1Wru0Ucf9VgntogF9MSJE9i7dy8mTZoEwGptvO//t3fvMVFcbx/Av7PArssud7nJRQ2KgrrgrVFQazWCCgSQSrVqQFMv0VYoRgNqtaZalKpYqzamBa0m1VYDtiattmhpLLFKVRArtWqtaRSjeIlKQEW+7x9m52VhQUCl0t/zSZ6wO3N2zplhdvbZMzNn33gDOTk5apnCwkIAwMaNG1FSUoKysjL4+fnh+PHjSE9Pt1jesWPHsHTpUgwbNgwpKSmoqalBTU0N7t27BwAYMmQIAGDEiBFqD6eHhweAJ9dMmP8qiqL2lpqnCyGEEEL8W2pra9XHtra26Natm3rtZn0ajQYFBQVIS0uDoigICAiA0WiEo6MjMjIy1LO6GzZsQElJCYKDg9XXbN26FcOGDYOTkxPWr1+P7du3t6htbHDmuuHzZ9LiVLUVFi5cSODJNQ3m0Gg01Ov1vHPnDknSZDI1meFrNBpWV1erPaDmZUmvpYSEhISEhMR/ORr2cJpj9OjRJMmcnByLMg3Lm882R0REEACvXr2q5mfjx49naGgo/f391Wl6vZ7u7u6NcrnKykp1mfn5+Zw/fz6NRiMfPHjQqOyVK1cIgNnZ2S3OFZ97D2htbS127NiBdevWoaSkRI3S0lJ06dIFu3btQk1NDcrKygAA69atQ15enhoajQZ1dXV4+PChusyoqCiUlJTgxIkT0Gq16Nq1K4D/79V0cnICAIwZM8aiLb6+vo3aV//uMiGEEEKIl0lYWJjF88zMTACAyWQCAJw+fRokERAQAFtbWxQXF8PT0xOhoaEAgPv37wMAgoODoSgKsrKy1GUtXboUZ86cwb1793Dnzh0AgMFgwI0bN7B//36Lej/++GMAT64hHTNmDCZNmoT79+9j69atjdq8du1a2NnZISEhoeUr2uJUtYXy8/Op1WrVns76Fi1axEGDBjE9PV3NqgsKClhRUcF//vmH3333He3s7KjRaEiSubm5BMC0tDSeOnWK69evb9QTajQa6eXlRQB0dHRs8tuDVqu1uEZCQkJCQkJCQuJlioY9mz4+Puod75GRkayoqGBISAjt7Oz47rvvEgBPnjzJ9evXq9eSvvnmm7xy5Qrnzp1LrVZLRVEYGxvLXbt2cfPmzbSxsaGzszPT0tJIkv7+/gwKCqKzszOzsrK4e/duTpgwgcCTM9L5+flqHpeSkkKdTse1a9fywoULLC8v55IlS6jRaKzeHd+c556ARkdHWx14niSPHTtGAHR1daWrq6vFRrexsaGvr69689CePXvUDdBcGAwGXr161eq8hnVISEhISEhISHTkUBSF9vb2aiddS8J8o7eiKDQajbSxsWFxcTHJ1g9En5OTw4EDB7JTp040GAwcPnx4oyGcWuKF/hKSeHYVFRUEwO+//54AWFxczMTERIsdy8HBgYMHD+bevXvV1wGw+NZCPulR9vb2tviGNXDgQB48eJBubm7MysoiSVZXV3P58uXs3bu32iOt1+t59epVbtu2jU5OTlbrAMAZM2awa9eu6rSEhASLtup0Ojo6OjIoKIi1tbUkyczMTPbp04dZWVkEYDHCQcN1IJ+MoNDcCAgA6OTkxJiYGM6ZM8fqmGvm0Ov19PHxsajLZDJZvd44MTGR7u7ufOONN2hjY0O9Xt+ojPkb6KZNm0iSBw8ebHbsWWdnZ7q4uKi9+NeuXWNoaKjFwUBRFKalpfHAgQONXm8wGNijRw9evHiRS5YssRgbzt7entOnT6fBYLBat729PQ0GA0NCQrhq1Sp1fZq6/sgcu3btYnh4OPV6PW1sbOji4sL4+HiSZGRkJLt27Uo7Ozv269ePJOni4kLgyVkIcx0eHh7qdvHy8qKfnx/9/f3p7++v1m+ebzAY2K9fP9rZ2dHV1VXdD/z8/Ojm5saIiAgGBQXx+vXrJJ+Mbefm5katVsuzZ8+26f1WXFzMpKQkxsbGNlk2NjaWSUlJJMmkpCSr28poNJIkL168yJkzZ9JoNKrzfH19qSgKr127xujoaALg8ePH1YO7tf3q8uXLTE9P54ABAxr9X52cnLho0SIWFBQ0ep8DYM+ePRkbG8sHDx7Q2dmZiqK023X1Te2DgYGBLV7GrFmz1HEQm4vnvU4tqROw/GU9W1vbFp9x69WrFz09PWlnZ9fiX+cLDw9neHg4XVxcqNPpaDQauXz5cmo0Gvbp04d79+5Vj2vWts/Dhw/V9+u8efNYW1tr9Xhmvrtaq9WqxxoAXL16dZNts7e35+rVq9U6SHLv3r3UaDRMTExU31MNkx4HBwd26dKFERER3LdvH4cPH/7Uu8O/+OILpqSkqM+7d+/OMWPGqPu++Zhe/3FQUJBafsKECezbt6/F+3LQoEF8/PgxAXDcuHH8+++/mZSURE9PT3Xf6t27NysrK1vU4VZaWsrDhw8zISGBfn5+1Gq19PT05NixY3nkyJFWHZ/+ayQBfUnV1dXx0qVLnDt3Ljt37szZs2fTw8OD5eXlnDZtGvV6PT08PFhdXd2m5d+8eZOhoaEcMWIEq6qqGs2vqqriiRMnGBgYyJSUlGdcG+vaUod5u8ybN4+enp6srq7msmXLaDQaefTo0RfSzqdtq9TUVGq1WtrZ2bGioqLZZdXU1PD3339neHi41eTmr7/+4nvvvUcATE9Pb1U77969y59//pnu7u6cNWsWdTodP/nkE3X+rVu3uH//fup0OovEvv70KVOmcP78+bSxsWGnTp149OjRRm0y/98CAgIYExNDnU7HnTt3cv/+/dRqtZw4cSIBcPbs2Zw5c6bFB0ZUVJRFgqDRaNTLauoPL2L+EYkhQ4aoB3zzB0bD9aiurmZmZqbFF7Dbt28zMjKy0XAjTbG2Xz1vbanj7Nmz9PLyooODA+fPn9+mep+2/5JPBpy2t7eng4NDi7eZteVv2bKFGo1G3Xesqa6uVn8YJCcnh+fPn2d0dDS7d+9OrVbLlStX0t3dvdmbGR49esTz589zwoQJ6rAw9aeZTCaeP3+ecXFx9PDwYI8ePdR9y9fXl/Hx8QwMDGRYWJi6//Xu3ZtxcXHs1asXIyIi6OTkRJPJxAMHDtDNzU1NlMzJZv0yDdvS3DYy/w9OnjzJ5cuX88KFC1Zfs2zZMhoMBi5dupQAWFhYaPX92xb130OfffYZV61aRZ1O1+Txq/627dev3wv/bKivJfvv89TUcVI8f5KAvqRu375NrVbLvn370tbWliEhIeoHvKIoDAgIsBhXtS0qKyu5YsUKFhQUNJqXnZ1NFxcXTpw4kTdv3nymeprSljrM2yUkJMRi/XNzc5mdnc3Hjx+/kLY2t63c3Nzo6enJpKSkp9afn59Po9HIiIgIXr58udF8b29vajQahoWFtXpdUlNT1eSzurqahw8f5ooVK3jjxg2SZFxcHH18fLh48WLW1dWpr6s/vf7jnJwcZmdn08vLy6JN5v9bly5d6O3tzcWLFzM2NpY+Pj40GAxUFIVhYWHqL5KZw9xbU7/Xw9bWVh0po37vkZ+fHx0dHdXEFAB9fHxYW1vb5Ho8i6b2q+epLXVkZ2fTycmJwcHBPHToUJvrbm7/NcvNzeWCBQu4bNmyJpOiliw/Ly+PCQkJzMrKanIfrq6u5tSpUzlu3Djq9Xq6urrSw8ODgwcPttiHm3Lq1Cnq9XoOHTqUpaWljaZ99dVX1Ov1NJlM6lkXc++cVqulyWSy6F3z9/enTqejyWSiVqulRqNhSEgI16xZY7UH0dbWVi1jrqt+W562jVrK39+fLi4u3LBhw3Pd7+svy83NjYGBgfz666+bLF9/2y5cuPCFfzY01JZt11Yv4vgirFPI5zmokxBCCCGEEM17YT/FKYQQQgghhDWSgAohhBBCiHYlCagQQgghhGhXkoAKIYQQQoh2JQmoEEI8Z+fOnUNmZiYePHjwbzdFCCFeSpKACiFEMwoLC6Eoivq7yU9z7949xMfHo3v37tDpdC16jaIo2LdvX9sbKYQQHYwkoEKIDiU5ORmKomDOnDmN5s2bNw+KoiA5Ofm51RcWFoaKigo4OTm1qHxSUhLeeustTJo0qcV1VFRUYNy4cW1tohBCdDgyDqgQokNJTk7G4cOHcffuXVRUVECv1wMAampq4O3tDUdHR7z22mvYvn37v9tQIYQQTZIeUCFEhzNgwAD4+fkhLy9PnZaXlwd/f3/0799fndatWzds2LDB4rWhoaF4//331eeKouDzzz9HfHw87O3t0bNnT3z77bfqfGun4IuKijBy5EjY29vDxcUFkZGRuH37NgBg5MiRSE1NtWjDBx98gMmTJ8NgMMDHxwebN2+2aFPDU/BlZWUYNWoU9Ho93NzcMGvWLNy/f78NW0oIIV5OkoAKITqkGTNmYNu2berz3NxcTJ8+vU3LWrFiBRITE3H69GmMHz8eU6ZMwa1bt6yWLSkpwejRoxEcHIyjR4/il19+QUxMDB4/ftzk8j/66COEhITg1KlTSE9PR0pKCn788UerZauqqhAZGQkXFxcUFxdjz549KCgowNtvv92mdRNCiJeR7b/dACGEaIupU6ciIyMDly9fBvCkV3L37t0oLCxs9bKSk5MxefJkAMCHH36IjRs34vjx4xg7dmyjsllZWRg0aBC2bNmiTuvTp0+zyw8PD0d6ejoAIDAwEEVFRcjOzsaYMWMalf3yyy9RU1ODHTt2wGAwAAA2bdqEmJgYrFmzBp6enq1ePyGEeNlID6gQokNyd3dHVFQUtm/fjm3btiEqKgqdO3du07JMJpP62GAwwNHREdevX7da1twD2hpDhw5t9Ly8vNxq2fLycoSEhKjJJ/Akga2rq8O5c+daVa8QQryspAdUCNFhzZgxQz013fC6SgDQaDRoeJ/lo0ePGpWzs7OzeK4oCurq6qzWab7pSQghRNtJD6gQosMaO3YsHj58iEePHiEyMrLRfHd3d1RUVKjP7969i0uXLj1TnSaTCYcOHWrVa3799ddGz4OCgqyWDQoKQmlpKaqqqtRpRUVF0Gg06NWrV+sbLIQQLyFJQIUQHZaNjQ3Ky8tx9uxZ2NjYNJo/atQo7Ny5E0eOHEFZWRmSkpKslmuNjIwMFBcXY+7cuTh9+jT++OMPfPrpp6isrGzyNUVFRcjKysKff/6JzZs3Y8+ePUhJSbFadsqUKejUqROSkpJw5swZ/PTTT3jnnXcwbdo0uf5TCPGfIQmoEKJDc3R0hKOjo9V5GRkZePXVVxEdHY2oqCjExcUhICDgmeoLDAzEDz/8gNLSUrzyyisYOnQovvnmG9jaNn1F04IFC/Dbb7+hf//+WLlyJdavX2+1xxYA7O3tcfDgQdy6dQuDBw/G66+/jtGjR2PTpk3P1G4hhHiZyED0QgjxAnXr1g2pqakWY4MKIcT/OukBFUIIIYQQ7UoSUCGEEEII0a7kFLwQQgghhGhX0gMqhBBCCCHalSSgQgghhBCiXUkCKoQQQggh2pUkoEIIIYQQol1JAiqEEEIIIdqVJKBCCCGEEKJdSQIqhBBCCCHalSSgQgghhBCiXUkCKoQQQggh2tX/AUXo6kTZxIAkAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Grafico de pontos - Área Territorial\n",
    "sns.scatterplot(data =df_ibge, x = df_ibge[\"Município\"], y = df_ibge[\"Área Territorial - km² [2022]\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Município', ylabel='População residente - pessoas [2022]'>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Grafico de linha - População residente\n",
    "sns.lineplot(x = df_ibge[\"Município\"], y = df_ibge[\"População residente - pessoas [2022]\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Município', ylabel='População residente - pessoas [2022]'>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Grafico de pontos - População residente\n",
    "sns.scatterplot(data =df_ibge, x = df_ibge[\"Município\"], y = df_ibge[\"População residente - pessoas [2022]\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Município', ylabel='Densidade demográfica - hab/km² [2022]'>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Gráfico de linhas = Densidade demográfica\n",
    "sns.lineplot(x = df_ibge[\"Município\"], y = df_ibge[\"Densidade demográfica - hab/km² [2022]\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Município', ylabel='Densidade demográfica - hab/km² [2022]'>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Gráfico de linhas = Densidade demográfica\n",
    "sns.scatterplot(data =df_ibge, x = df_ibge[\"Município\"], y = df_ibge[\"Densidade demográfica - hab/km² [2022]\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sanando problema com MERGE entre as duas tabelas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Realização de comparativos relacionados a coluna \"Municípios\", pois houve conflito ao relizar o merge. Havendo a necessidade de compará-los ara eventual correção ortográfica para eventual correção ortográfica.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(df_pc,df_ibge, on = \"Município\", how = \"left\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.merge(df_ibge,df_pc, on = \"Município\", how = \"left\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Município                                  0\n",
       "Quantidade vítimas                         0\n",
       "Área Territorial - km² [2022]             11\n",
       "População residente - pessoas [2022]      11\n",
       "Densidade demográfica - hab/km² [2022]    11\n",
       "dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Município                                  0\n",
       "Área Territorial - km² [2022]              0\n",
       "População residente - pessoas [2022]       0\n",
       "Densidade demográfica - hab/km² [2022]     0\n",
       "Quantidade vítimas                        12\n",
       "dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Dataframe gerado pelos dados da PC-CIVIl\n",
    "\n",
    "df = df[df[\"Área Territorial - km² [2022]\"].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Município</th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "      <th>Área Territorial - km² [2022]</th>\n",
       "      <th>População residente - pessoas [2022]</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>AMPARO DA SERRA</td>\n",
       "      <td>32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>BARAO DO MONTE ALTO</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>BRASOPOLIS</td>\n",
       "      <td>32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>CAPITAO ENEIAS</td>\n",
       "      <td>110</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>DONA EUSEBIA</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>534</th>\n",
       "      <td>ONCA DO PITANGUI</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682</th>\n",
       "      <td>SANTA RITA DO IBITIPOCA</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>SAO JOAO BATISTA GLORIA</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>SAO SEB.DO RIO PRETO</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>756</th>\n",
       "      <td>SAO SEBAST. DO MARANHAO</td>\n",
       "      <td>34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>762</th>\n",
       "      <td>SAO SEBASTIAO PARAISO</td>\n",
       "      <td>367</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Município  Quantidade vítimas  \\\n",
       "27           AMPARO DA SERRA                  32   \n",
       "59       BARAO DO MONTE ALTO                  20   \n",
       "94                BRASOPOLIS                  32   \n",
       "139           CAPITAO ENEIAS                 110   \n",
       "256             DONA EUSEBIA                  19   \n",
       "534         ONCA DO PITANGUI                   6   \n",
       "682  SANTA RITA DO IBITIPOCA                  10   \n",
       "725  SAO JOAO BATISTA GLORIA                  31   \n",
       "755     SAO SEB.DO RIO PRETO                   5   \n",
       "756  SAO SEBAST. DO MARANHAO                  34   \n",
       "762    SAO SEBASTIAO PARAISO                 367   \n",
       "\n",
       "     Área Territorial - km² [2022]  População residente - pessoas [2022]  \\\n",
       "27                             NaN                                   NaN   \n",
       "59                             NaN                                   NaN   \n",
       "94                             NaN                                   NaN   \n",
       "139                            NaN                                   NaN   \n",
       "256                            NaN                                   NaN   \n",
       "534                            NaN                                   NaN   \n",
       "682                            NaN                                   NaN   \n",
       "725                            NaN                                   NaN   \n",
       "755                            NaN                                   NaN   \n",
       "756                            NaN                                   NaN   \n",
       "762                            NaN                                   NaN   \n",
       "\n",
       "     Densidade demográfica - hab/km² [2022]  \n",
       "27                                      NaN  \n",
       "59                                      NaN  \n",
       "94                                      NaN  \n",
       "139                                     NaN  \n",
       "256                                     NaN  \n",
       "534                                     NaN  \n",
       "682                                     NaN  \n",
       "725                                     NaN  \n",
       "755                                     NaN  \n",
       "756                                     NaN  \n",
       "762                                     NaN  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dataframe gerado pelos dados da IBGE\n",
    "df2 = df2[df2[\"Quantidade vítimas\"].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Município</th>\n",
       "      <th>Área Territorial - km² [2022]</th>\n",
       "      <th>População residente - pessoas [2022]</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>AMPARO DO SERRA</td>\n",
       "      <td>136.186</td>\n",
       "      <td>4541</td>\n",
       "      <td>33.34</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>BARAO DE MONTE ALTO</td>\n",
       "      <td>198.313</td>\n",
       "      <td>4964</td>\n",
       "      <td>25.03</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>BRAZOPOLIS</td>\n",
       "      <td>367.688</td>\n",
       "      <td>14246</td>\n",
       "      <td>38.74</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>CAPITAO ENEAS</td>\n",
       "      <td>971.576</td>\n",
       "      <td>14108</td>\n",
       "      <td>14.52</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>DONA EUZEBIA</td>\n",
       "      <td>70.231</td>\n",
       "      <td>6093</td>\n",
       "      <td>86.76</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533</th>\n",
       "      <td>ONCA DE PITANGUI</td>\n",
       "      <td>246.976</td>\n",
       "      <td>2969</td>\n",
       "      <td>12.02</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>692</th>\n",
       "      <td>SANTA RITA DE IBITIPOCA</td>\n",
       "      <td>324.234</td>\n",
       "      <td>3301</td>\n",
       "      <td>10.18</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>724</th>\n",
       "      <td>SAO JOAO BATISTA DO GLORIA</td>\n",
       "      <td>547.908</td>\n",
       "      <td>7652</td>\n",
       "      <td>13.97</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>757</th>\n",
       "      <td>SAO SEBASTIAO DO MARANHAO</td>\n",
       "      <td>517.830</td>\n",
       "      <td>10079</td>\n",
       "      <td>19.46</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>759</th>\n",
       "      <td>SAO SEBASTIAO DO PARAISO</td>\n",
       "      <td>814.925</td>\n",
       "      <td>71796</td>\n",
       "      <td>88.10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>760</th>\n",
       "      <td>SAO SEBASTIAO DO RIO PRETO</td>\n",
       "      <td>128.002</td>\n",
       "      <td>1259</td>\n",
       "      <td>9.84</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>782</th>\n",
       "      <td>SERRA DA SAUDADE</td>\n",
       "      <td>335.659</td>\n",
       "      <td>833</td>\n",
       "      <td>2.48</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Município  Área Territorial - km² [2022]  \\\n",
       "26              AMPARO DO SERRA                        136.186   \n",
       "59          BARAO DE MONTE ALTO                        198.313   \n",
       "95                   BRAZOPOLIS                        367.688   \n",
       "138               CAPITAO ENEAS                        971.576   \n",
       "255                DONA EUZEBIA                         70.231   \n",
       "533            ONCA DE PITANGUI                        246.976   \n",
       "692     SANTA RITA DE IBITIPOCA                        324.234   \n",
       "724  SAO JOAO BATISTA DO GLORIA                        547.908   \n",
       "757   SAO SEBASTIAO DO MARANHAO                        517.830   \n",
       "759    SAO SEBASTIAO DO PARAISO                        814.925   \n",
       "760  SAO SEBASTIAO DO RIO PRETO                        128.002   \n",
       "782            SERRA DA SAUDADE                        335.659   \n",
       "\n",
       "     População residente - pessoas [2022]  \\\n",
       "26                                   4541   \n",
       "59                                   4964   \n",
       "95                                  14246   \n",
       "138                                 14108   \n",
       "255                                  6093   \n",
       "533                                  2969   \n",
       "692                                  3301   \n",
       "724                                  7652   \n",
       "757                                 10079   \n",
       "759                                 71796   \n",
       "760                                  1259   \n",
       "782                                   833   \n",
       "\n",
       "     Densidade demográfica - hab/km² [2022]  Quantidade vítimas  \n",
       "26                                    33.34                 NaN  \n",
       "59                                    25.03                 NaN  \n",
       "95                                    38.74                 NaN  \n",
       "138                                   14.52                 NaN  \n",
       "255                                   86.76                 NaN  \n",
       "533                                   12.02                 NaN  \n",
       "692                                   10.18                 NaN  \n",
       "724                                   13.97                 NaN  \n",
       "757                                   19.46                 NaN  \n",
       "759                                   88.10                 NaN  \n",
       "760                                    9.84                 NaN  \n",
       "782                                    2.48                 NaN  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AMPARO DA SERRA',\n",
       " 'BARAO DO MONTE ALTO',\n",
       " 'BRASOPOLIS',\n",
       " 'CAPITAO ENEIAS',\n",
       " 'DONA EUSEBIA',\n",
       " 'ONCA DO PITANGUI',\n",
       " 'SANTA RITA DO IBITIPOCA',\n",
       " 'SAO JOAO BATISTA GLORIA',\n",
       " 'SAO SEB.DO RIO PRETO',\n",
       " 'SAO SEBAST. DO MARANHAO',\n",
       " 'SAO SEBASTIAO PARAISO']"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lista dos Municípios (contém erros ortográficos) \n",
    "df[\"Município\"].tolist()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Município</th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "      <th>Área Territorial - km² [2022]</th>\n",
       "      <th>População residente - pessoas [2022]</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>AMPARO DA SERRA</td>\n",
       "      <td>32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>BARAO DO MONTE ALTO</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>BRASOPOLIS</td>\n",
       "      <td>32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>CAPITAO ENEIAS</td>\n",
       "      <td>110</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>DONA EUSEBIA</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>534</th>\n",
       "      <td>ONCA DO PITANGUI</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682</th>\n",
       "      <td>SANTA RITA DO IBITIPOCA</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>SAO JOAO BATISTA GLORIA</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>SAO SEB.DO RIO PRETO</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>756</th>\n",
       "      <td>SAO SEBAST. DO MARANHAO</td>\n",
       "      <td>34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>762</th>\n",
       "      <td>SAO SEBASTIAO PARAISO</td>\n",
       "      <td>367</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Município  Quantidade vítimas  \\\n",
       "27           AMPARO DA SERRA                  32   \n",
       "59       BARAO DO MONTE ALTO                  20   \n",
       "94                BRASOPOLIS                  32   \n",
       "139           CAPITAO ENEIAS                 110   \n",
       "256             DONA EUSEBIA                  19   \n",
       "534         ONCA DO PITANGUI                   6   \n",
       "682  SANTA RITA DO IBITIPOCA                  10   \n",
       "725  SAO JOAO BATISTA GLORIA                  31   \n",
       "755     SAO SEB.DO RIO PRETO                   5   \n",
       "756  SAO SEBAST. DO MARANHAO                  34   \n",
       "762    SAO SEBASTIAO PARAISO                 367   \n",
       "\n",
       "     Área Territorial - km² [2022]  População residente - pessoas [2022]  \\\n",
       "27                             NaN                                   NaN   \n",
       "59                             NaN                                   NaN   \n",
       "94                             NaN                                   NaN   \n",
       "139                            NaN                                   NaN   \n",
       "256                            NaN                                   NaN   \n",
       "534                            NaN                                   NaN   \n",
       "682                            NaN                                   NaN   \n",
       "725                            NaN                                   NaN   \n",
       "755                            NaN                                   NaN   \n",
       "756                            NaN                                   NaN   \n",
       "762                            NaN                                   NaN   \n",
       "\n",
       "     Densidade demográfica - hab/km² [2022]  \n",
       "27                                      NaN  \n",
       "59                                      NaN  \n",
       "94                                      NaN  \n",
       "139                                     NaN  \n",
       "256                                     NaN  \n",
       "534                                     NaN  \n",
       "682                                     NaN  \n",
       "725                                     NaN  \n",
       "755                                     NaN  \n",
       "756                                     NaN  \n",
       "762                                     NaN  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AMPARO DO SERRA',\n",
       " 'BARAO DE MONTE ALTO',\n",
       " 'BRAZOPOLIS',\n",
       " 'CAPITAO ENEAS',\n",
       " 'DONA EUZEBIA',\n",
       " 'ONCA DE PITANGUI',\n",
       " 'SANTA RITA DE IBITIPOCA',\n",
       " 'SAO JOAO BATISTA DO GLORIA',\n",
       " 'SAO SEBASTIAO DO MARANHAO',\n",
       " 'SAO SEBASTIAO DO PARAISO',\n",
       " 'SAO SEBASTIAO DO RIO PRETO',\n",
       " 'SERRA DA SAUDADE']"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lista dos Municípios\n",
    "df2[\"Município\"].tolist()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Município</th>\n",
       "      <th>Área Territorial - km² [2022]</th>\n",
       "      <th>População residente - pessoas [2022]</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>AMPARO DO SERRA</td>\n",
       "      <td>136.186</td>\n",
       "      <td>4541</td>\n",
       "      <td>33.34</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>BARAO DE MONTE ALTO</td>\n",
       "      <td>198.313</td>\n",
       "      <td>4964</td>\n",
       "      <td>25.03</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>BRAZOPOLIS</td>\n",
       "      <td>367.688</td>\n",
       "      <td>14246</td>\n",
       "      <td>38.74</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>CAPITAO ENEAS</td>\n",
       "      <td>971.576</td>\n",
       "      <td>14108</td>\n",
       "      <td>14.52</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>DONA EUZEBIA</td>\n",
       "      <td>70.231</td>\n",
       "      <td>6093</td>\n",
       "      <td>86.76</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533</th>\n",
       "      <td>ONCA DE PITANGUI</td>\n",
       "      <td>246.976</td>\n",
       "      <td>2969</td>\n",
       "      <td>12.02</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>692</th>\n",
       "      <td>SANTA RITA DE IBITIPOCA</td>\n",
       "      <td>324.234</td>\n",
       "      <td>3301</td>\n",
       "      <td>10.18</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>724</th>\n",
       "      <td>SAO JOAO BATISTA DO GLORIA</td>\n",
       "      <td>547.908</td>\n",
       "      <td>7652</td>\n",
       "      <td>13.97</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>757</th>\n",
       "      <td>SAO SEBASTIAO DO MARANHAO</td>\n",
       "      <td>517.830</td>\n",
       "      <td>10079</td>\n",
       "      <td>19.46</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>759</th>\n",
       "      <td>SAO SEBASTIAO DO PARAISO</td>\n",
       "      <td>814.925</td>\n",
       "      <td>71796</td>\n",
       "      <td>88.10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>760</th>\n",
       "      <td>SAO SEBASTIAO DO RIO PRETO</td>\n",
       "      <td>128.002</td>\n",
       "      <td>1259</td>\n",
       "      <td>9.84</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>782</th>\n",
       "      <td>SERRA DA SAUDADE</td>\n",
       "      <td>335.659</td>\n",
       "      <td>833</td>\n",
       "      <td>2.48</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Município  Área Territorial - km² [2022]  \\\n",
       "26              AMPARO DO SERRA                        136.186   \n",
       "59          BARAO DE MONTE ALTO                        198.313   \n",
       "95                   BRAZOPOLIS                        367.688   \n",
       "138               CAPITAO ENEAS                        971.576   \n",
       "255                DONA EUZEBIA                         70.231   \n",
       "533            ONCA DE PITANGUI                        246.976   \n",
       "692     SANTA RITA DE IBITIPOCA                        324.234   \n",
       "724  SAO JOAO BATISTA DO GLORIA                        547.908   \n",
       "757   SAO SEBASTIAO DO MARANHAO                        517.830   \n",
       "759    SAO SEBASTIAO DO PARAISO                        814.925   \n",
       "760  SAO SEBASTIAO DO RIO PRETO                        128.002   \n",
       "782            SERRA DA SAUDADE                        335.659   \n",
       "\n",
       "     População residente - pessoas [2022]  \\\n",
       "26                                   4541   \n",
       "59                                   4964   \n",
       "95                                  14246   \n",
       "138                                 14108   \n",
       "255                                  6093   \n",
       "533                                  2969   \n",
       "692                                  3301   \n",
       "724                                  7652   \n",
       "757                                 10079   \n",
       "759                                 71796   \n",
       "760                                  1259   \n",
       "782                                   833   \n",
       "\n",
       "     Densidade demográfica - hab/km² [2022]  Quantidade vítimas  \n",
       "26                                    33.34                 NaN  \n",
       "59                                    25.03                 NaN  \n",
       "95                                    38.74                 NaN  \n",
       "138                                   14.52                 NaN  \n",
       "255                                   86.76                 NaN  \n",
       "533                                   12.02                 NaN  \n",
       "692                                   10.18                 NaN  \n",
       "724                                   13.97                 NaN  \n",
       "757                                   19.46                 NaN  \n",
       "759                                   88.10                 NaN  \n",
       "760                                    9.84                 NaN  \n",
       "782                                    2.48                 NaN  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "# O Município Serra da Saudade não se encontra na base da PC-MG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "#função para correção de nomes, utilizando a base do IBGE como referência\n",
    "def corrigir_nome2(nome):\n",
    "    nome = nome.replace('AMPARO DA SERRA', 'AMPARO DO SERRA').replace('BARAO DO MONTE ALTO','BARAO DE MONTE ALTO').replace('BRASOPOLIS','BRAZOPOLIS').replace('CAPITAO ENEIAS','CAPITAO ENEAS').replace('DONA EUSEBIA','DONA EUZEBIA').replace( 'ONCA DO PITANGUI','ONCA DE PITANGUI').replace('SANTA RITA DO IBITIPOCA','SANTA RITA DE IBITIPOCA').replace('SAO JOAO BATISTA GLORIA','SAO JOAO BATISTA DO GLORIA').replace('SAO SEB.DO RIO PRETO','SAO SEBASTIAO DO RIO PRETO').replace('SAO SEBAST. DO MARANHAO','SAO SEBASTIAO DO MARANHAO').replace('SAO SEBASTIAO PARAISO','SAO SEBASTIAO DO PARAISO')\n",
    "    return nome\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pc = df_pc.apply(corrigir_nome2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = pd.merge(df_pc,df_ibge, on = \"Município\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Município</th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "      <th>Área Territorial - km² [2022]</th>\n",
       "      <th>População residente - pessoas [2022]</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABADIA DOS DOURADOS</td>\n",
       "      <td>33</td>\n",
       "      <td>880.461</td>\n",
       "      <td>6272</td>\n",
       "      <td>7.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ABAETE</td>\n",
       "      <td>169</td>\n",
       "      <td>1817.067</td>\n",
       "      <td>22675</td>\n",
       "      <td>12.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABRE CAMPO</td>\n",
       "      <td>58</td>\n",
       "      <td>470.551</td>\n",
       "      <td>13927</td>\n",
       "      <td>29.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACAIACA</td>\n",
       "      <td>16</td>\n",
       "      <td>101.886</td>\n",
       "      <td>3909</td>\n",
       "      <td>38.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ACUCENA</td>\n",
       "      <td>26</td>\n",
       "      <td>815.422</td>\n",
       "      <td>8943</td>\n",
       "      <td>10.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847</th>\n",
       "      <td>VIRGINOPOLIS</td>\n",
       "      <td>45</td>\n",
       "      <td>439.878</td>\n",
       "      <td>10314</td>\n",
       "      <td>23.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>VIRGOLANDIA</td>\n",
       "      <td>3</td>\n",
       "      <td>281.022</td>\n",
       "      <td>4552</td>\n",
       "      <td>16.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>849</th>\n",
       "      <td>VISCONDE DO RIO BRANCO</td>\n",
       "      <td>218</td>\n",
       "      <td>243.351</td>\n",
       "      <td>39160</td>\n",
       "      <td>160.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>VOLTA GRANDE</td>\n",
       "      <td>18</td>\n",
       "      <td>205.552</td>\n",
       "      <td>4443</td>\n",
       "      <td>21.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>851</th>\n",
       "      <td>WENCESLAU BRAZ</td>\n",
       "      <td>11</td>\n",
       "      <td>102.487</td>\n",
       "      <td>2356</td>\n",
       "      <td>22.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>852 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Município  Quantidade vítimas  \\\n",
       "0       ABADIA DOS DOURADOS                  33   \n",
       "1                    ABAETE                 169   \n",
       "2                ABRE CAMPO                  58   \n",
       "3                   ACAIACA                  16   \n",
       "4                   ACUCENA                  26   \n",
       "..                      ...                 ...   \n",
       "847            VIRGINOPOLIS                  45   \n",
       "848             VIRGOLANDIA                   3   \n",
       "849  VISCONDE DO RIO BRANCO                 218   \n",
       "850            VOLTA GRANDE                  18   \n",
       "851          WENCESLAU BRAZ                  11   \n",
       "\n",
       "     Área Territorial - km² [2022]  População residente - pessoas [2022]  \\\n",
       "0                          880.461                                  6272   \n",
       "1                         1817.067                                 22675   \n",
       "2                          470.551                                 13927   \n",
       "3                          101.886                                  3909   \n",
       "4                          815.422                                  8943   \n",
       "..                             ...                                   ...   \n",
       "847                        439.878                                 10314   \n",
       "848                        281.022                                  4552   \n",
       "849                        243.351                                 39160   \n",
       "850                        205.552                                  4443   \n",
       "851                        102.487                                  2356   \n",
       "\n",
       "     Densidade demográfica - hab/km² [2022]  \n",
       "0                                      7.12  \n",
       "1                                     12.48  \n",
       "2                                     29.60  \n",
       "3                                     38.37  \n",
       "4                                     10.97  \n",
       "..                                      ...  \n",
       "847                                   23.45  \n",
       "848                                   16.20  \n",
       "849                                  160.92  \n",
       "850                                   21.61  \n",
       "851                                   22.99  \n",
       "\n",
       "[852 rows x 5 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Município                                 0\n",
       "Quantidade vítimas                        0\n",
       "Área Territorial - km² [2022]             0\n",
       "População residente - pessoas [2022]      0\n",
       "Densidade demográfica - hab/km² [2022]    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Machine Learning - Aplicação de Clustering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Preparação para Machine Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Quantidade vítimas</th>\n",
       "      <th>Densidade demográfica - hab/km² [2022]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>33</td>\n",
       "      <td>7.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>169</td>\n",
       "      <td>12.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>58</td>\n",
       "      <td>29.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16</td>\n",
       "      <td>38.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>26</td>\n",
       "      <td>10.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847</th>\n",
       "      <td>45</td>\n",
       "      <td>23.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>3</td>\n",
       "      <td>16.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>849</th>\n",
       "      <td>218</td>\n",
       "      <td>160.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>18</td>\n",
       "      <td>21.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>851</th>\n",
       "      <td>11</td>\n",
       "      <td>22.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>852 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Quantidade vítimas  Densidade demográfica - hab/km² [2022]\n",
       "0                    33                                    7.12\n",
       "1                   169                                   12.48\n",
       "2                    58                                   29.60\n",
       "3                    16                                   38.37\n",
       "4                    26                                   10.97\n",
       "..                  ...                                     ...\n",
       "847                  45                                   23.45\n",
       "848                   3                                   16.20\n",
       "849                 218                                  160.92\n",
       "850                  18                                   21.61\n",
       "851                  11                                   22.99\n",
       "\n",
       "[852 rows x 2 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Seleção de dados para padronização\n",
    "X_base = df_final.iloc[:,[1,4]]\n",
    "X_base"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Variável global \n",
    "#X_base"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Dados padronizados: Quantidade de vítimas e Densidade demográfica\n",
    "scaler_base = StandardScaler()\n",
    "X_base = scaler_base.fit_transform(X_base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.18490489, -0.19732361],\n",
       "       [ 0.11844071, -0.18027473],\n",
       "       [-0.12914283, -0.1258201 ],\n",
       "       ...,\n",
       "       [ 0.22773434,  0.29187739],\n",
       "       [-0.21836213, -0.15123438],\n",
       "       [-0.2339755 , -0.14684493]])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_base"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### K-MEANS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n"
     ]
    }
   ],
   "source": [
    "#Utilização do método Elbow (cotovelo) para definição de N° de Clusters a ser utilzaado no K-means\n",
    "wcss = []\n",
    "for i in range(1,11):\n",
    "    kmeans_base = KMeans(n_clusters = i, random_state=0)\n",
    "    kmeans_base.fit(X_base)\n",
    "    wcss.append(kmeans_base.inertia_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1704.0000000000002,\n",
       " 659.6363069140027,\n",
       " 307.2979369607416,\n",
       " 181.22061185540628,\n",
       " 119.52712839433552,\n",
       " 95.0547959207228,\n",
       " 75.76563471140892,\n",
       " 59.72429622749458,\n",
       " 46.43074555008118,\n",
       " 38.56547707123351]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wcss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "x=%{x}<br>y=%{y}<extra></extra>",
         "legendgroup": "",
         "line": {
          "color": "#636efa",
          "dash": "solid"
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          1,
          2,
          3,
          4,
          5,
          6,
          7,
          8,
          9,
          10
         ],
         "xaxis": "x",
         "y": [
          1704.0000000000002,
          659.6363069140027,
          307.2979369607416,
          181.22061185540628,
          119.52712839433552,
          95.0547959207228,
          75.76563471140892,
          59.72429622749458,
          46.43074555008118,
          38.56547707123351
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 60
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "fillpattern": {
             "fillmode": "overlay",
             "size": 10,
             "solidity": 0.2
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "x"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "y"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Gráfico para auxiliar na quantidade de clusters\n",
    "# Definição de 3 Clusters para aplicação do K-Means - Método Cotovelo\n",
    "grafico = px.line(x = range(1,11), y = wcss)\n",
    "grafico.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Pedro Henrique\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1412: FutureWarning:\n",
      "\n",
      "The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Aplicação do Modelo K-Means\n",
    "kmeans_base = KMeans(n_clusters=3, random_state=0)\n",
    "rotulos = kmeans_base.fit_predict(X_base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "x=%{x}<br>y=%{y}<br>color=%{marker.color}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": [
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           1,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           2,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0
          ],
          "coloraxis": "coloraxis",
          "symbol": "circle"
         },
         "mode": "markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          -0.18490489291461773,
          0.11844070742238616,
          -0.1291428340291391,
          -0.2228230929567432,
          -0.20051826940255177,
          -0.16706103407126457,
          -0.2272840576675815,
          -0.22505357531216236,
          -0.04215402216779238,
          -0.2072097164688092,
          0.10951877800070957,
          -0.2228230929567432,
          -0.25628032828803043,
          -0.2272840576675815,
          0.058217683826069205,
          0.8611913317769618,
          -0.18490489291461773,
          0.406172931271456,
          -0.1938268223362943,
          -0.0912246339870136,
          -0.12691235167371992,
          -0.21613164589048578,
          -0.21390116353506664,
          -0.15813910464958797,
          -0.2362059870892581,
          -0.16260006936042629,
          -0.2272840576675815,
          -0.18713537527003687,
          0.06044816618148835,
          -0.20051826940255177,
          -0.18490489291461773,
          -0.08899415163159445,
          -0.2072097164688092,
          -0.24735839886635383,
          -0.2406669518000964,
          -0.24958888122177297,
          0.11174926035612871,
          0.9481801436383085,
          -0.22059261060132407,
          -0.21836212824590492,
          -0.18936585762545602,
          -0.23397550473383896,
          -0.16929151642668372,
          1.516953144270191,
          -0.21836212824590492,
          0.16081987217534993,
          -0.12691235167371992,
          -0.23174502237841982,
          -0.20944019882422835,
          -0.04884546923404982,
          -0.19159633998087516,
          -0.16929151642668372,
          -0.20497923411339006,
          -0.07115029278824128,
          -0.13360379873997738,
          -0.01538823390276262,
          -0.2362059870892581,
          -0.2116706811796475,
          0.2031990369283137,
          -0.21390116353506664,
          1.6307077443965672,
          -0.2406669518000964,
          -0.031001610390696644,
          -0.1782134458483603,
          -0.25181936357719215,
          23.638877145317284,
          -0.046614986878630665,
          -0.2072097164688092,
          -0.21836212824590492,
          -0.2406669518000964,
          -0.2228230929567432,
          3.711747782002631,
          -0.2116706811796475,
          -0.1157599398966242,
          -0.22951454002300067,
          0.2165819310608286,
          -0.21836212824590492,
          0.3035707429221753,
          0.3370279782534625,
          -0.20497923411339006,
          -0.24735839886635383,
          -0.2072097164688092,
          -0.1603695870050071,
          -0.18713537527003687,
          -0.1291428340291391,
          -0.18044392820377944,
          -0.19159633998087516,
          -0.20497923411339006,
          -0.1603695870050071,
          -0.10460752811952848,
          -0.2027487517579709,
          -0.24512791651093468,
          -0.1157599398966242,
          0.04260430733813518,
          -0.18713537527003687,
          -0.2362059870892581,
          0.2210428957716669,
          -0.22505357531216236,
          -0.1202209046074625,
          -0.21390116353506664,
          0.08944443680193725,
          0.00245562494059055,
          -0.16483055171584543,
          -0.1603695870050071,
          -0.20497923411339006,
          -0.19605730469171348,
          -0.20944019882422835,
          -0.25181936357719215,
          -0.1447562105170731,
          0.16081987217534993,
          -0.2072097164688092,
          -0.2027487517579709,
          -0.13360379873997738,
          -0.25404984593261126,
          -0.01984919861360091,
          -0.0020053397702477424,
          -0.13360379873997738,
          -0.2272840576675815,
          -0.07338077514366043,
          -0.03992353981237323,
          -0.06445884572198383,
          -0.2362059870892581,
          0.5020836725544793,
          -0.17152199878210286,
          -0.173752481137522,
          -0.053306433944888106,
          -0.06445884572198383,
          -0.21390116353506664,
          -0.2406669518000964,
          -0.17152199878210286,
          -0.18044392820377944,
          -0.2362059870892581,
          -0.20497923411339006,
          -0.2406669518000964,
          0.2589610958137924,
          -0.18267441055919859,
          -0.1492171752279114,
          -0.10237704576410933,
          -0.20944019882422835,
          -0.013157751547343473,
          -0.18267441055919859,
          -0.18044392820377944,
          -0.12468186931830079,
          -0.24289743415551554,
          -0.10014656340869017,
          0.12736263684406274,
          0.9481801436383085,
          -0.21836212824590492,
          -0.19828778704713262,
          -0.03323209274611579,
          -0.24289743415551554,
          -0.1492171752279114,
          -0.17598296349294115,
          -0.12691235167371992,
          0.12736263684406274,
          0.18981614279579884,
          -0.046614986878630665,
          -0.15590862229416882,
          -0.18490489291461773,
          -0.19159633998087516,
          -0.24289743415551554,
          -0.23843646944467725,
          -0.25181936357719215,
          -0.24735839886635383,
          -0.046614986878630665,
          0.47085691957861125,
          -0.19828778704713262,
          -0.23397550473383896,
          -0.20051826940255177,
          -0.23174502237841982,
          -0.05553691630030725,
          -0.24289743415551554,
          -0.21613164589048578,
          -0.19605730469171348,
          -0.20051826940255177,
          -0.2272840576675815,
          -0.2027487517579709,
          -0.16706103407126457,
          -0.2406669518000964,
          -0.19605730469171348,
          -0.24289743415551554,
          -0.2027487517579709,
          0.0626786485369075,
          -0.22059261060132407,
          -0.20944019882422835,
          -0.2362059870892581,
          -0.22059261060132407,
          -0.173752481137522,
          -0.25404984593261126,
          0.09390540151277554,
          -0.24289743415551554,
          -0.23397550473383896,
          -0.03769305745695408,
          -0.20051826940255177,
          -0.09568559869785188,
          -0.2027487517579709,
          -0.22951454002300067,
          -0.18044392820377944,
          -0.12245138696288164,
          0.5310799431749282,
          -0.22505357531216236,
          -0.173752481137522,
          1.443347226541359,
          -0.024310163324439204,
          -0.24958888122177297,
          5.748178172500311,
          -0.14029524580623481,
          -0.01538823390276262,
          -0.17152199878210286,
          -0.25404984593261126,
          0.10505781328987128,
          -0.2072097164688092,
          0.053756719115230917,
          0.8745742259094768,
          -0.18936585762545602,
          -0.23843646944467725,
          -0.23843646944467725,
          -0.2272840576675815,
          -0.23843646944467725,
          -0.2406669518000964,
          -0.23397550473383896,
          -0.16929151642668372,
          -0.21390116353506664,
          -0.16929151642668372,
          -0.2027487517579709,
          -0.18936585762545602,
          -0.18713537527003687,
          -0.2027487517579709,
          -0.2272840576675815,
          -0.12691235167371992,
          -0.16929151642668372,
          -0.21836212824590492,
          0.8188121670239981,
          -0.18713537527003687,
          -0.2406669518000964,
          -0.18044392820377944,
          -0.11129897518578591,
          -0.21836212824590492,
          -0.2027487517579709,
          -0.2406669518000964,
          0.5712286255724728,
          -0.24512791651093468,
          -0.2116706811796475,
          -0.2072097164688092,
          -0.053306433944888106,
          -0.22059261060132407,
          -0.19159633998087516,
          2.507287310076292,
          -0.1938268223362943,
          -0.17598296349294115,
          -0.21390116353506664,
          -0.21836212824590492,
          -0.19605730469171348,
          -0.2027487517579709,
          -0.23397550473383896,
          -0.24289743415551554,
          -0.21613164589048578,
          -0.13806476345081567,
          -0.2228230929567432,
          -0.1291428340291391,
          -0.22059261060132407,
          -0.24958888122177297,
          -0.24958888122177297,
          -0.2116706811796475,
          -0.00869678683650518,
          -0.14029524580623481,
          -0.173752481137522,
          -0.2116706811796475,
          -0.10014656340869017,
          -0.08007222220991786,
          0.6849832256988493,
          -0.010927269191924327,
          -0.0577673986557264,
          -0.2272840576675815,
          -0.20944019882422835,
          -0.24512791651093468,
          -0.24289743415551554,
          -0.17598296349294115,
          -0.1202209046074625,
          -0.1782134458483603,
          0.267883025235469,
          -0.23174502237841982,
          -0.2362059870892581,
          -0.18490489291461773,
          -0.1938268223362943,
          -0.13360379873997738,
          -0.20944019882422835,
          -0.1603695870050071,
          -0.1447562105170731,
          -0.18267441055919859,
          0.5890724844158259,
          -0.21836212824590492,
          -0.2406669518000964,
          -0.21613164589048578,
          -0.2228230929567432,
          -0.21836212824590492,
          0.04483478969355433,
          -0.20051826940255177,
          -0.20944019882422835,
          -0.19159633998087516,
          -0.24289743415551554,
          0.029221413205620304,
          -0.2272840576675815,
          -0.2228230929567432,
          0.9258753200841171,
          -0.18490489291461773,
          -0.17152199878210286,
          -0.24512791651093468,
          -0.22951454002300067,
          -0.21836212824590492,
          -0.19605730469171348,
          -0.24958888122177297,
          -0.22059261060132407,
          -0.07115029278824128,
          3.5266177465028417,
          -0.1782134458483603,
          -0.24512791651093468,
          0.1251321544886436,
          -0.07561125749907957,
          -0.17152199878210286,
          -0.2228230929567432,
          -0.06668932807740298,
          -0.173752481137522,
          -0.23174502237841982,
          -0.20944019882422835,
          0.3972510018497794,
          -0.1938268223362943,
          -0.18713537527003687,
          -0.21390116353506664,
          -0.22951454002300067,
          -0.20944019882422835,
          -0.1202209046074625,
          -0.18936585762545602,
          0.07383106031400323,
          -0.2072097164688092,
          -0.21390116353506664,
          -0.13806476345081567,
          1.472343497161808,
          -0.2406669518000964,
          -0.24289743415551554,
          -0.19159633998087516,
          0.2611915781692115,
          -0.19605730469171348,
          -0.19828778704713262,
          -0.2272840576675815,
          -0.10906849283036676,
          -0.22059261060132407,
          -0.23174502237841982,
          -0.21836212824590492,
          -0.2027487517579709,
          -0.23174502237841982,
          -0.10460752811952848,
          -0.18044392820377944,
          -0.18713537527003687,
          -0.00869678683650518,
          -0.028771128035277496,
          2.59204563958222,
          -0.2072097164688092,
          -0.1447562105170731,
          -0.1492171752279114,
          1.166767414469385,
          -0.1603695870050071,
          0.2857268840788221,
          -0.2362059870892581,
          -0.09791608105327103,
          -0.0912246339870136,
          -0.14029524580623481,
          0.5801505549941494,
          -0.02207968096902006,
          -0.2272840576675815,
          0.10282733093445214,
          -0.24512791651093468,
          -0.20051826940255177,
          -0.1603695870050071,
          -0.15367813993874968,
          -0.10683801047494762,
          -0.017618716258181767,
          -0.1492171752279114,
          -0.11799042225204334,
          -0.14698669287249225,
          -0.10460752811952848,
          -0.0577673986557264,
          0.8232731317348363,
          -0.20944019882422835,
          -0.18490489291461773,
          -0.20497923411339006,
          0.6113773079700174,
          -0.20051826940255177,
          0.3035707429221753,
          -0.24735839886635383,
          -0.046614986878630665,
          -0.09568559869785188,
          -0.173752481137522,
          -0.082302704565337,
          -0.2272840576675815,
          0.16528083688618822,
          -0.21836212824590492,
          0.6158382726808558,
          0.41286437833771344,
          -0.22951454002300067,
          -0.21613164589048578,
          -0.17598296349294115,
          -0.2406669518000964,
          -0.1157599398966242,
          -0.16706103407126457,
          -0.18267441055919859,
          0.03145189556103945,
          -0.22951454002300067,
          -0.173752481137522,
          -0.24958888122177297,
          0.6693698492109152,
          0.19204662515121798,
          -0.21613164589048578,
          -0.18936585762545602,
          -0.2362059870892581,
          -0.20497923411339006,
          -0.2406669518000964,
          0.16305035453076908,
          6.916950926739944,
          -0.20051826940255177,
          -0.20051826940255177,
          -0.2272840576675815,
          -0.12245138696288164,
          -0.21836212824590492,
          0.4953922254882218,
          -0.21836212824590492,
          -0.1938268223362943,
          -0.082302704565337,
          -0.16260006936042629,
          0.3325670135426242,
          -0.03992353981237323,
          -0.08453318692075615,
          -0.2362059870892581,
          -0.20497923411339006,
          -0.18490489291461773,
          0.7585891434276811,
          -0.22059261060132407,
          -0.23397550473383896,
          0.314723154699271,
          -0.24289743415551554,
          -0.09791608105327103,
          -0.15813910464958797,
          -0.1938268223362943,
          -0.23174502237841982,
          -0.2027487517579709,
          -0.18936585762545602,
          -0.03769305745695408,
          -0.19828778704713262,
          0.14074553097657763,
          -0.19828778704713262,
          -0.01984919861360091,
          -0.23397550473383896,
          -0.03323209274611579,
          0.7496672140060046,
          -0.024310163324439204,
          0.047065272048973476,
          -0.11352945754120505,
          -0.17598296349294115,
          -0.18267441055919859,
          0.7050575668976216,
          -0.21390116353506664,
          -0.05107595158946896,
          -0.24512791651093468,
          -0.2228230929567432,
          -0.24512791651093468,
          -0.14698669287249225,
          -0.15813910464958797,
          -0.18936585762545602,
          -0.2272840576675815,
          0.2411172369704392,
          -0.2272840576675815,
          -0.0867636692761753,
          -0.1492171752279114,
          -0.04884546923404982,
          -0.13583428109539653,
          0.2031990369283137,
          -0.22505357531216236,
          -0.2406669518000964,
          -0.09791608105327103,
          -0.22059261060132407,
          -0.18490489291461773,
          -0.23397550473383896,
          -0.082302704565337,
          -0.19828778704713262,
          -0.1603695870050071,
          -0.17152199878210286,
          -0.12691235167371992,
          -0.25181936357719215,
          -0.1938268223362943,
          -0.16260006936042629,
          -0.23174502237841982,
          -0.1603695870050071,
          -0.1447562105170731,
          -0.07115029278824128,
          -0.06445884572198383,
          -0.17152199878210286,
          0.27234398994630726,
          -0.24958888122177297,
          -0.04438450452321152,
          -0.1157599398966242,
          4.590557830037775,
          -0.23174502237841982,
          -0.0912246339870136,
          -0.23397550473383896,
          -0.24289743415551554,
          -0.2027487517579709,
          0.8478084376444469,
          -0.10237704576410933,
          -0.05107595158946896,
          -0.25181936357719215,
          0.10728829564529042,
          -0.16483055171584543,
          -0.21836212824590492,
          -0.24958888122177297,
          -0.18713537527003687,
          0.04260430733813518,
          -0.18044392820377944,
          -0.2362059870892581,
          -0.053306433944888106,
          0.8522694023552853,
          -0.23174502237841982,
          -0.11129897518578591,
          -0.19828778704713262,
          -0.19159633998087516,
          0.9794068966141766,
          -0.20944019882422835,
          0.07160057795858409,
          -0.18267441055919859,
          -0.24289743415551554,
          -0.24958888122177297,
          -0.18267441055919859,
          -0.22505357531216236,
          0.09836636622361385,
          -0.24958888122177297,
          -0.24512791651093468,
          -0.21613164589048578,
          -0.19828778704713262,
          0.2411172369704392,
          0.00022514258517140383,
          0.7206709433855556,
          -0.1938268223362943,
          -0.23397550473383896,
          -0.06222836336656469,
          -0.21390116353506664,
          -0.22505357531216236,
          -0.19605730469171348,
          -0.24512791651093468,
          -0.2362059870892581,
          -0.2362059870892581,
          -0.035462575101534936,
          0.5979944138375026,
          0.7675110728493577,
          0.047065272048973476,
          -0.11352945754120505,
          0.18981614279579884,
          -0.18044392820377944,
          -0.23397550473383896,
          -0.25404984593261126,
          -0.25628032828803043,
          1.2559867086861507,
          -0.2362059870892581,
          2.0098897448178223,
          0.6403735785904664,
          -0.18713537527003687,
          -0.20497923411339006,
          -0.2228230929567432,
          -0.22059261060132407,
          -0.15590862229416882,
          -0.03323209274611579,
          -0.24735839886635383,
          -0.23397550473383896,
          -0.22951454002300067,
          -0.21613164589048578,
          -0.2072097164688092,
          -0.1447562105170731,
          -0.22505357531216236,
          0.3727156959401688,
          -0.25404984593261126,
          -0.22505357531216236,
          -0.21390116353506664,
          -0.1492171752279114,
          -0.06222836336656469,
          -0.03323209274611579,
          -0.15144765758333054,
          -0.2272840576675815,
          -0.21836212824590492,
          -0.173752481137522,
          -0.20944019882422835,
          -0.21613164589048578,
          -0.2272840576675815,
          -0.18490489291461773,
          -0.19605730469171348,
          -0.22505357531216236,
          -0.22059261060132407,
          -0.2027487517579709,
          -0.1603695870050071,
          -0.22951454002300067,
          -0.20051826940255177,
          -0.17598296349294115,
          0.42847775482564743,
          -0.12691235167371992,
          0.033682377916458596,
          0.13182360155490103,
          -0.046614986878630665,
          -0.12691235167371992,
          1.9295923800227328,
          -0.21390116353506664,
          0.15635890746451164,
          0.47531788428944954,
          -0.20497923411339006,
          -0.17598296349294115,
          0.00022514258517140383,
          -0.18044392820377944,
          -0.15367813993874968,
          1.6463211208845012,
          -0.2027487517579709,
          -0.2027487517579709,
          0.06490913089232665,
          -0.1782134458483603,
          -0.2406669518000964,
          -0.24735839886635383,
          -0.22505357531216236,
          -0.2116706811796475,
          -0.1492171752279114,
          -0.017618716258181767,
          -0.22059261060132407,
          -0.24512791651093468,
          -0.06668932807740298,
          -0.046614986878630665,
          -0.18713537527003687,
          -0.18713537527003687,
          -0.1782134458483603,
          -0.07561125749907957,
          -0.21836212824590492,
          -0.1782134458483603,
          -0.21613164589048578,
          3.4708556876173633,
          -0.23174502237841982,
          -0.09568559869785188,
          -0.08453318692075615,
          -0.24289743415551554,
          -0.23174502237841982,
          -0.22059261060132407,
          -0.19605730469171348,
          -0.12691235167371992,
          -0.06891981043282214,
          -0.13137331638455824,
          -0.13137331638455824,
          -0.08899415163159445,
          -0.2228230929567432,
          -0.15813910464958797,
          -0.22505357531216236,
          -0.22059261060132407,
          -0.1447562105170731,
          -0.22951454002300067,
          -0.23843646944467725,
          -0.21836212824590492,
          -0.17598296349294115,
          1.3162097322824677,
          -0.10460752811952848,
          0.10951877800070957,
          0.018069001428524575,
          -0.22059261060132407,
          0.16528083688618822,
          -0.21390116353506664,
          -0.2228230929567432,
          -0.22951454002300067,
          -0.18267441055919859,
          -0.22951454002300067,
          -0.23397550473383896,
          -0.21390116353506664,
          -0.24512791651093468,
          -0.24289743415551554,
          0.022529966139362867,
          2.395763192305335,
          -0.13806476345081567,
          -0.19159633998087516,
          -0.22951454002300067,
          -0.10683801047494762,
          -0.20944019882422835,
          -0.25404984593261126,
          -0.1492171752279114,
          -0.2362059870892581,
          -0.22059261060132407,
          0.17420276630786483,
          -0.22505357531216236,
          -0.07561125749907957,
          -0.21390116353506664,
          -0.21390116353506664,
          -0.21390116353506664,
          -0.22059261060132407,
          -0.2406669518000964,
          -0.2228230929567432,
          -0.18267441055919859,
          0.19873807221747541,
          -0.2072097164688092,
          -0.23397550473383896,
          -0.082302704565337,
          -0.2228230929567432,
          -0.20051826940255177,
          -0.21613164589048578,
          -0.15367813993874968,
          0.03814334262729689,
          -0.23174502237841982,
          -0.24958888122177297,
          -0.22951454002300067,
          0.3013402605667561,
          -0.1492171752279114,
          -0.1938268223362943,
          -0.21390116353506664,
          -0.10014656340869017,
          -0.24512791651093468,
          0.330336531187205,
          -0.2116706811796475,
          -0.18936585762545602,
          -0.20497923411339006,
          -0.18713537527003687,
          -0.24512791651093468,
          -0.21613164589048578,
          -0.17598296349294115,
          -0.1202209046074625,
          -0.13806476345081567,
          -0.21390116353506664,
          -0.03992353981237323,
          0.3481803900305582,
          -0.18936585762545602,
          -0.22505357531216236,
          -0.25181936357719215,
          -0.1447562105170731,
          -0.18044392820377944,
          0.7005966021867833,
          -0.18713537527003687,
          -0.22059261060132407,
          -0.16260006936042629,
          -0.22951454002300067,
          -0.15590862229416882,
          -0.10014656340869017,
          -0.024310163324439204,
          0.2321953075487626,
          -0.19159633998087516,
          0.06044816618148835,
          -0.2406669518000964,
          -0.19828778704713262,
          -0.2272840576675815,
          -0.24289743415551554,
          -0.2228230929567432,
          -0.20051826940255177,
          -0.2362059870892581,
          0.1697418015970265,
          -0.21836212824590492,
          -0.2072097164688092,
          -0.23174502237841982,
          -0.18044392820377944,
          -0.16929151642668372,
          -0.2072097164688092,
          -0.24735839886635383,
          -0.18267441055919859,
          -0.1938268223362943,
          -0.24289743415551554,
          -0.1938268223362943,
          -0.18044392820377944,
          -0.25404984593261126,
          0.5600762137953771,
          -0.20051826940255177,
          -0.18713537527003687,
          -0.16706103407126457,
          -0.18267441055919859,
          -0.22951454002300067,
          -0.20497923411339006,
          0.10282733093445214,
          -0.25181936357719215,
          -0.16483055171584543,
          -0.21836212824590492,
          -0.20497923411339006,
          -0.25181936357719215,
          -0.21613164589048578,
          -0.24289743415551554,
          -0.20944019882422835,
          -0.1938268223362943,
          -0.22059261060132407,
          -0.24735839886635383,
          -0.2228230929567432,
          -0.14252572816165396,
          -0.19828778704713262,
          -0.1782134458483603,
          -0.2228230929567432,
          -0.23843646944467725,
          -0.01984919861360091,
          3.1652796049249403,
          -0.15144765758333054,
          -0.23843646944467725,
          -0.20051826940255177,
          -0.22059261060132407,
          -0.10906849283036676,
          -0.18936585762545602,
          -0.21836212824590492,
          -0.23174502237841982,
          0.2121209663499903,
          -0.2272840576675815,
          -0.18267441055919859,
          -0.25404984593261126,
          -0.2272840576675815,
          -0.12691235167371992,
          -0.11799042225204334,
          1.3429755205474974,
          0.44186064895816235,
          -0.15590862229416882,
          -0.1603695870050071,
          -0.09345511634243274,
          -0.25628032828803043,
          -0.20497923411339006,
          -0.18267441055919859,
          1.1779198262464805,
          0.21881241341624774,
          0.4262472724702283,
          -0.18267441055919859,
          0.029221413205620304,
          -0.13583428109539653,
          -0.22951454002300067,
          0.6448345433013046,
          -0.18713537527003687,
          -0.13360379873997738,
          3.680521029026763,
          5.600966337042648,
          -0.23843646944467725,
          0.6626784021446578,
          -0.20497923411339006,
          -0.2362059870892581,
          -0.10906849283036676,
          -0.19159633998087516,
          -0.20497923411339006,
          -0.23397550473383896,
          -0.24735839886635383,
          1.673086909149531,
          -0.2072097164688092,
          0.12736263684406274,
          -0.07338077514366043,
          -0.09791608105327103,
          -0.1157599398966242,
          -0.22505357531216236,
          -0.23174502237841982,
          -0.23397550473383896,
          1.3697413088125272,
          0.4597045078015155,
          -0.22505357531216236,
          -0.19605730469171348,
          -0.20944019882422835,
          -0.15813910464958797,
          -0.25181936357719215,
          0.22773434283792432,
          -0.21836212824590492,
          -0.23397550473383896
         ],
         "xaxis": "x",
         "y": [
          -0.19732360523316692,
          -0.1802747278288778,
          -0.1258201044778648,
          -0.09792483305330968,
          -0.1850776765006085,
          -0.18965797192265632,
          -0.20635696564887232,
          -0.16026774296451615,
          -0.14840350551712836,
          -0.1844415243586574,
          -0.16039497339290634,
          -0.18946712628007098,
          -0.16577045899239304,
          -0.058483400252342305,
          -0.028488826759348582,
          0.07539481802126381,
          -0.051453919083782815,
          -0.16402104060202752,
          -0.08847797374533602,
          -0.09363080609513984,
          -0.09770217980362679,
          -0.0421979054183945,
          -0.04458347595071108,
          -0.15311103136756643,
          -0.174549358551318,
          -0.1400699124575691,
          -0.18460056239414518,
          -0.11392405942337948,
          0.0547834886220486,
          -0.18224679946892616,
          -0.08742832271111674,
          -0.15336549222434684,
          -0.18272391357538947,
          -0.1616036624626134,
          -0.1829783744321699,
          -0.1588364006451262,
          -0.17117775219897724,
          -0.08268898925358116,
          -0.1162778223485985,
          -0.13571227028520422,
          -0.1283329054385716,
          -0.1718457119480259,
          -0.10078751769208956,
          0.0852233686144081,
          -0.040766563099004546,
          0.03840257096680815,
          -0.06401792388731677,
          -0.16631118831305144,
          -0.15829567132446776,
          -0.20956953396572534,
          0.06305346646741275,
          -0.19617853137765495,
          -0.2084562677173109,
          -0.14213740691891016,
          -0.17712577472621993,
          -0.16853772080988025,
          -0.18879916653102236,
          0.1799782301580224,
          0.06785641513914342,
          -0.1403561809214471,
          0.3050775488727035,
          -0.17299078580353788,
          0.5582661013692358,
          0.0763172386270929,
          -0.19372934563114327,
          22.007757755212086,
          0.007294731225400026,
          -0.1449682839505925,
          -0.16672468720531966,
          -0.19261607938272887,
          -0.1868907101051691,
          3.5875589861261137,
          -0.18227860707602372,
          0.0974056821327714,
          -0.2034624734029949,
          -0.0727014006249491,
          -0.1861909427490229,
          -0.1723228260544892,
          -0.08437479242975152,
          -0.1676153002040512,
          -0.15167968904817647,
          -0.12839652065276672,
          -0.1419147536692273,
          -0.04493335962878417,
          -0.14258271341827594,
          -0.14162848520534932,
          -0.21046014696445686,
          -0.21173245124835902,
          -0.03612265246276163,
          -0.07880846118767951,
          -0.20823361446762806,
          -0.1593135147515895,
          -0.2009496724422881,
          -0.14719481644742133,
          -0.09674795159070015,
          -0.18262849075409682,
          -0.026389524690910007,
          -0.12251211333971915,
          -0.20177667022682452,
          -0.1403879885285447,
          -0.2053391222217506,
          -0.2094423035373351,
          -0.19958194533709328,
          -0.12139884709130477,
          -0.02858424958064125,
          -0.09573010816357841,
          -0.17830265618882943,
          -0.18370994939541366,
          0.013115523324252462,
          0.0073583464395951224,
          -0.06150512292660997,
          -0.06338177174536569,
          -0.15641902250571205,
          -0.17947953765143893,
          -0.06296827285309747,
          0.1641698494305379,
          -0.06099620121304911,
          -0.1989457931951422,
          -0.0689481029874377,
          -0.10603577286318602,
          -0.20428947118753132,
          -0.1966238378770207,
          0.0948292659578695,
          -0.08857339656662869,
          -0.1986595247312642,
          -0.16188993092649137,
          -0.11207921821172133,
          -0.14115137109888598,
          -0.13421731275161913,
          -0.1799884593649998,
          -0.15816844089607754,
          -0.13087751400637593,
          -0.09712964287587082,
          -0.09506214841452977,
          -0.08940039435116512,
          -0.14993027065781098,
          0.13579746389951944,
          -0.14487286112929984,
          -0.16771072302534384,
          -0.17378597598097673,
          -0.15670529096959004,
          -0.06853460409516948,
          -0.16993725552217262,
          -0.16163547006971096,
          -0.06452684560087764,
          0.06120862525575461,
          0.0008377869845964963,
          -0.2013631713345563,
          -0.10018317315723603,
          -0.20149040176294652,
          -0.1880039763535835,
          -0.14741746969710418,
          -0.12184415359067051,
          -0.08380225550199555,
          -0.0561296373271233,
          -0.1494213489442501,
          -0.15743686593283382,
          -0.07782242536765535,
          -0.20543454504304323,
          -0.20228559194038537,
          -0.08892328024470178,
          -0.17012810116475796,
          -0.17531274112165932,
          -0.19649660744863048,
          -0.13800241799622812,
          0.20860507654582133,
          -0.14744927730420174,
          -0.1501211163003963,
          -0.16666107199112454,
          -0.16758349259695363,
          0.44655778524262524,
          -0.20782011557535987,
          -0.12391164805201153,
          -0.11926773741576863,
          -0.15597371600634627,
          -0.12912809561601044,
          -0.180401958257268,
          -0.20788373078955497,
          -0.18475960042963296,
          -0.10431816207991809,
          -0.15489225736502946,
          -0.18832205242455902,
          -0.06786664434612083,
          -0.00816376582401137,
          -0.14547720566415337,
          -0.21150979799867614,
          -0.18762228506841283,
          -0.1263926414056208,
          -0.17849350183141477,
          -0.15260210965400553,
          -0.13370839103805826,
          -0.1647526155652713,
          -0.17712577472621993,
          -0.1511707673346156,
          -0.11207921821172133,
          -0.027948097438690176,
          -0.20568900589982372,
          0.3319867844772345,
          -0.0481141203385396,
          0.3332908963682342,
          -0.1820877614334384,
          -0.18552298299997427,
          0.9107898108314305,
          -0.17534454872875688,
          -0.16418007863751533,
          9.936866284511517,
          -0.12305284266037758,
          -0.18370994939541366,
          -0.19083485338526585,
          -0.1632894656387838,
          -0.19032593167170495,
          -0.15988605167934547,
          -0.19223438809755822,
          1.2857378832974007,
          -0.18797216874648592,
          -0.15317464658176153,
          -0.14131040913437373,
          -0.20565719829272613,
          -0.11007533896457543,
          -0.0270256768328611,
          -0.17543997155004953,
          -0.1921707728833631,
          -0.20263547561845846,
          -0.15823205611027266,
          -0.200599788764215,
          -0.10826230536001483,
          -0.1139876746375746,
          -0.1165640908124765,
          -0.16023593535741856,
          -0.12642444901271835,
          -0.16408465581622264,
          -0.17871615508109764,
          -0.14242367538278816,
          -0.16392561778073486,
          -0.15804121046768732,
          -0.200599788764215,
          0.10478504697940398,
          -0.14643143387708,
          -0.15543298668568786,
          -0.1530474161533713,
          -0.180974495185024,
          -0.1515842662268838,
          -0.15578287036376098,
          -0.10504973704316183,
          -0.024989989978617625,
          -0.18113353322051176,
          -0.06427238474409719,
          0.8180706361420597,
          -0.04929100180114913,
          -0.1341855051445216,
          -0.16325765803168624,
          -0.20559358307853104,
          0.04209225339012444,
          -0.1809108799708289,
          -0.13469442685808244,
          -0.1335493530025705,
          0.05599217769175569,
          0.034999157007369816,
          -0.17811181054624411,
          -0.18380537221670634,
          -0.1513616129772009,
          -0.18959435670846123,
          -0.2013631713345563,
          -0.10562227397091781,
          -0.052280916868319226,
          0.011652373397764938,
          -0.1867316720696813,
          -0.02705748443995865,
          -0.11729566577572025,
          -0.03974871967188283,
          0.079307153694263,
          0.021385501169616565,
          -0.1681560295247096,
          -0.14029256570725201,
          -0.06996594641455943,
          -0.1670427632762952,
          -0.2061025047920919,
          -0.1935066923814604,
          -0.10893026510906346,
          -0.10126463179855287,
          0.4755663229155946,
          -0.1246432230152553,
          -0.15858193978834575,
          -0.17432670530163513,
          -0.18536394496448647,
          -0.19137558270592425,
          -0.16157185485551587,
          -0.19194811963368022,
          -0.12709240876176697,
          -0.0882235128885556,
          -0.07543685483533877,
          -0.21310017835355385,
          -0.16942833380861178,
          -0.17044617723573352,
          -0.1692056805589289,
          -0.21087364585672505,
          -0.19277511741821665,
          -0.19764168130414247,
          -0.1913437750988267,
          -0.16424369385171042,
          -0.15556021711407808,
          0.01117525929130165,
          -0.1768713138694395,
          -0.200599788764215,
          -0.14318705795312947,
          -0.1453817828428607,
          -0.19248884895433865,
          -0.21115991432060305,
          -0.15613275404183408,
          -0.13991087442208136,
          -0.13517154096454578,
          -0.13956099074400827,
          -0.1405152189569349,
          -0.17836627140302455,
          0.1292450968374233,
          -0.20858349814570115,
          -0.19703733676928892,
          -0.1245796078010602,
          -0.1730862086248305,
          -0.13097293682766858,
          -0.1788115779023903,
          -0.01338021338801028,
          -0.12709240876176697,
          -0.10699000107611263,
          -0.20991941764379843,
          0.34544140227949993,
          -0.07674096672633848,
          -0.14646324148417755,
          -0.13571227028520422,
          -0.2110326838922128,
          -0.09324911480996917,
          -0.10775338364645394,
          -0.17222740323319655,
          -0.19382476845243593,
          -0.19710095198348404,
          -0.17423128248034248,
          -0.15800940286058976,
          7.266172362172467,
          -0.06328634892407302,
          -0.16392561778073486,
          -0.16567503617110035,
          1.0944787418198068,
          -0.062204890282756164,
          -0.18539575257158405,
          -0.008322803859499133,
          -0.11230187146140422,
          -0.1070218086832102,
          -0.06474949885056053,
          -0.19986821380097125,
          -0.19633756941314273,
          -0.19312500109628974,
          -0.1358395007135944,
          -0.13895664620915474,
          -0.1754717791571471,
          0.2613420891135663,
          -0.08399310114458088,
          4.173168840399186,
          -0.19420645973760658,
          -0.12254392094681672,
          -0.15587829318505364,
          0.067601954282363,
          -0.06230031310404883,
          0.0915530824268214,
          -0.21240041099740767,
          -0.17531274112165932,
          -0.11268356274657489,
          -0.15075726844234738,
          0.7841319193689692,
          -0.1816742625411702,
          -0.09585733859196863,
          -0.17279994016095254,
          -0.2020629386907025,
          -0.07941280572253306,
          -0.1110613747845996,
          0.11808062674618171,
          -0.14757650773259193,
          -0.1302731694715224,
          -0.1957968400924843,
          -0.15581467797085852,
          0.007676422510570648,
          -0.08023980350706947,
          0.07870280915940948,
          0.40667104594229203,
          -0.15683252139798026,
          -0.19347488477436284,
          -0.17744385079719546,
          -0.09483949516484688,
          -0.13008232382893706,
          -0.1332630845386925,
          -0.18390079503799897,
          -0.16176270049810118,
          -0.19477899666536255,
          -0.16173089289100362,
          0.013560829823618224,
          -0.15991785928644306,
          -0.17451755094422047,
          -0.19353849998855793,
          -0.11688216688345206,
          -0.18886278174521745,
          -0.13666649849813084,
          -0.15107534451332294,
          -0.1365392680697406,
          -0.15177511186946913,
          -0.14786277619646995,
          -0.20371693425977533,
          -0.17792096490365877,
          -0.198246025838996,
          -0.11373321378079417,
          -0.19341126956016771,
          -0.16093570271356478,
          2.352246949278397,
          -0.2061025047920919,
          -0.2044803168301166,
          -0.1600132821077357,
          -0.18685890249807155,
          -0.1449046687363974,
          -0.1986595247312642,
          0.7870582192219442,
          0.9780310922356602,
          -0.19220258049046066,
          -0.059978357785927375,
          -0.20266728322555605,
          -0.16720180131178297,
          -0.20565719829272613,
          0.1517012674482966,
          -0.2024128223687756,
          -0.13475804207227757,
          -0.14846712073132345,
          -0.1969101063408987,
          0.8219193566008637,
          -0.06653072484802355,
          0.08471444690084724,
          -0.13456719642969223,
          -0.1274104848327425,
          -0.21290933271096854,
          0.370060490173007,
          -0.1910575066349487,
          -0.1706688304854164,
          -0.047477968196588526,
          -0.1824376451115115,
          -0.15543298668568786,
          -0.19897760080223972,
          -0.11198379539042867,
          -0.06783483673902328,
          -0.17200474998351367,
          -0.1844415243586574,
          -0.1714322130557577,
          -0.15788217243219957,
          -0.015415900242253758,
          -0.1864772112129009,
          -0.14344151880990988,
          -0.15288837811788353,
          -0.189180857816193,
          0.24518382470800879,
          0.13843749528861649,
          -0.09677975919779772,
          -0.11109318239169716,
          -0.13081389879218083,
          0.003382395552400833,
          -0.0564795210051964,
          -0.1353623866071311,
          1.2134391923646597,
          -0.08068511000643523,
          -0.1932204239175824,
          -0.12562925883527948,
          -0.1778891572965612,
          0.01581916992754456,
          -0.09258115506092054,
          -0.17502647265778132,
          0.17940569323026645,
          -0.16389381017363733,
          0.06597976632038775,
          -0.20540273743594573,
          0.001060440234279355,
          -0.13889303099495964,
          0.25399453187403126,
          -0.17346789991000117,
          -0.2068658873624332,
          -0.17531274112165932,
          -0.1616036624626134,
          -0.12524756755010882,
          -0.16166727767680852,
          -0.17712577472621993,
          -0.16583407420658816,
          -0.15994966689354057,
          -0.12540660558559658,
          -0.08475648371492218,
          -0.19891398558804463,
          -0.11487828763630611,
          -0.10151909265533329,
          -0.20937868832314,
          -0.09747952655394392,
          -0.1902305088504123,
          -0.1952561107718259,
          -0.15540117907859033,
          -0.12146246230549987,
          -0.1070218086832102,
          -0.18383717982380388,
          -0.10823049775291725,
          0.042792020746270636,
          0.1470573568120537,
          -0.200599788764215,
          -0.20613431239918947,
          -0.20149040176294652,
          -0.19910483123062994,
          -0.0962390298771393,
          0.17345767070302376,
          -0.14970761740812807,
          -0.05011799958568553,
          -0.1864772112129009,
          -0.14655866430547024,
          -0.062332120711146376,
          -0.1960831085563623,
          -0.14089691024210554,
          -0.14379140248798297,
          -0.08335694900262978,
          -0.18959435670846123,
          -0.15167968904817647,
          -0.06672157049060888,
          0.6075996999775427,
          -0.18899001217360767,
          -0.1781754257604392,
          -0.04359744013068688,
          -0.08637867167689744,
          0.9685842329276867,
          -0.11077510632072161,
          -0.16958737184409953,
          -0.17668046822685415,
          -0.16643841874144166,
          -0.18526852214319384,
          -0.21179606646255414,
          -0.07120644309136404,
          -0.0807805328277279,
          -0.16195354614068652,
          -0.18173787775536532,
          -0.044360822701028195,
          0.0003606728781331635,
          0.2560938339424699,
          -0.02871148000903146,
          -0.028934133258714342,
          -0.11560986259954986,
          -0.18393260264509656,
          -0.11869520048801263,
          -0.1989457931951422,
          -0.19888217798094707,
          -0.15858193978834575,
          -0.13972002877949602,
          -0.16262150588973515,
          -0.17369055315968407,
          -0.13997448963627648,
          0.34054303078647663,
          -0.18364633418121853,
          -0.05711567314714747,
          -0.023654070480520338,
          -0.09741591133974879,
          -0.04194344456161407,
          -0.15718240507605338,
          -0.19115292945624138,
          -0.16592949702788082,
          0.04613181949151383,
          -0.18533213735738893,
          -0.061218854462731995,
          -0.12057184930676834,
          -0.0561296373271233,
          -0.11732747338281779,
          -0.15667348336249248,
          -0.17738023558300034,
          -0.16430730906590552,
          -0.17127317502026992,
          -0.08609240321301945,
          -0.15915447671610172,
          -0.18237402989731638,
          -0.09468045712935913,
          -0.06296827285309747,
          -0.19818241062480088,
          -0.19026231645750985,
          0.4597897497952077,
          -0.1690148349163436,
          -0.10263235890374771,
          -0.15517852582890743,
          -0.06344538695956078,
          -0.19770529651833757,
          0.0313412821911511,
          -0.1289054423663276,
          -0.18418706350187697,
          -0.17369055315968407,
          0.028128713874298095,
          -0.0689481029874377,
          -0.17461297376551313,
          -0.1584865169670531,
          -0.15431972043727346,
          0.004877353085985882,
          -0.20161763219133674,
          -0.14395044052347078,
          -0.16786976106083162,
          -0.13781157235364278,
          -0.12559745122818192,
          0.012479371182301366,
          -0.03520023185693254,
          0.10189055473352655,
          0.03595338522029644,
          -0.0709519822345836,
          -0.09286742352479853,
          -0.10832592057420992,
          -0.11004353135747785,
          0.7322537121928581,
          -0.18154703211277998,
          -0.18126076364890198,
          0.17049956324295124,
          -0.2001862898719468,
          -0.19140739031302179,
          -0.15190234229785934,
          -0.10193259154760151,
          -0.15043919237137185,
          0.6719782967429927,
          -0.14057883417113,
          -0.1109977595704045,
          -0.2013631713345563,
          -0.09592095380616375,
          -0.20177667022682452,
          -0.15482864215083433,
          -0.20413043315204352,
          -0.1683468751672949,
          -0.20292174408233646,
          0.07370901484509343,
          -0.20180847783392206,
          -0.18329645050314544,
          0.49690922727805364,
          -0.12238488291132894,
          -0.07053848334231541,
          -0.05558890800646487,
          -0.16220800699746696,
          -0.16933291098731912,
          -0.14096052545630064,
          -0.20727938625470144,
          -0.1987867551596544,
          6.54315364523796,
          0.0435235957095144,
          -0.07705904279731403,
          -0.11414671267306235,
          -0.18921266542329054,
          -0.14948496415844523,
          -0.14760831533968952,
          -0.14347332641700747,
          -0.0905136605995795,
          -0.18577744385675468,
          -0.19112112184914382,
          -0.09522118645001755,
          -0.00018005644252526532,
          -0.17299078580353788,
          -0.1792250767946585,
          -0.18072003432824355,
          -0.12820567501018137,
          0.159239670330417,
          -0.19353849998855793,
          -0.08450202285814173,
          -0.20371693425977533,
          -0.18603190471353512,
          1.1405679645041629,
          -0.1707324456996115,
          -0.19236161852594844,
          -0.15132980537010338,
          -0.19926386926611772,
          -0.07839496229541132,
          0.030514284406614668,
          -0.19640118462733785,
          -0.1511707673346156,
          7.0150194965301775,
          -0.19888217798094707,
          -0.1625260830684425,
          -0.12260753616101182,
          -0.21612190102782153,
          -0.1516478814410789,
          -0.1508208836565425,
          2.73899564397756,
          -0.016052052384204853,
          -0.1641164634233202,
          -0.1856502134283645,
          -0.1547968345437368,
          -0.16647022634853922,
          -0.18402802546638922,
          0.09613337784886922,
          -0.1875904774613153,
          -0.18176968536246285,
          0.14619855142041974,
          -0.1821513766476335,
          -0.1977371041254351,
          -0.09751133416104146,
          -0.1512343825488107,
          -0.20215836151199515,
          -0.15473321932954165,
          -0.18650901881999846,
          -0.09372622891643251,
          -0.13768434192525256,
          0.29620322649248587,
          -0.19500164991504543,
          -0.1638301949594422,
          -0.10749892278967352,
          -0.16061762664258925,
          -0.11665951363376917,
          -0.1792250767946585,
          -0.15476502693663924,
          -0.14283717427505635,
          -0.1935066923814604,
          -0.16637480352724657,
          -0.1999000214080688,
          -0.008354611466596704,
          -0.03351442868076218,
          -0.10463623815089364,
          0.074027090916069,
          -0.14560443609254362,
          -0.15734144311154113,
          -0.16923748816602643,
          -0.157850364825102,
          -0.20381235708106799,
          -0.1272196391901572,
          -0.04372467055907712,
          -0.1509481140849327,
          -0.1843779091444623,
          -0.2112553371418957,
          -0.07909472965155752,
          -0.11637324516989117,
          -0.18930808824458323,
          -0.07247874737526622,
          -0.06971148555777898,
          -0.17553539437134222,
          -0.20460754725850686,
          -0.14305982752473925,
          -0.17884338550948786,
          -0.1589000158593213,
          -0.02231815098242305,
          0.030005362693053813,
          -0.09703422005457815,
          -0.03275104611042087,
          -0.18959435670846123,
          -0.1804655734714631,
          -0.1180908559531591,
          -0.020377886949472238,
          1.3025322998449096,
          -0.13956099074400827,
          1.5064508689473302,
          -0.16338488846007646,
          -0.1497712326223232,
          -0.07190621044751025,
          -0.18644540360580333,
          -0.129446171686986,
          -0.16287596674651558,
          -0.059882934964634704,
          2.235990145336836,
          -0.08752374553240941,
          -0.16039497339290634,
          -0.16729722413307563,
          -0.16338488846007646,
          -0.20648419607726257,
          -0.2091560350734571,
          -0.18867193610263214,
          -0.15807301807478488,
          -0.09862460040945586,
          -0.08548805867816592,
          0.024407223843884236,
          -0.15126619015590825,
          -0.13943376031561805,
          0.06025439704282794,
          -0.1577867496109069,
          -0.14283717427505635,
          -0.16058581903549166,
          -0.16484803838656395,
          -0.14954857937264032,
          -0.10555865875672271,
          1.6661568641841504,
          -0.1761715465132933,
          -0.08933677913697,
          -0.14751289251839683,
          -0.07257417019655886,
          -0.14989846305071342,
          -0.20657961889855522,
          -0.11783639509637867,
          -0.19439730538019193,
          -0.08109860889870345,
          -0.07925376768704527,
          -0.169555564237002,
          -0.16478442317236883,
          -0.1909938914207536,
          -0.1165640908124765,
          -0.10412731643733275,
          -0.1946199586298748,
          -0.19026231645750985,
          -0.16262150588973515,
          1.126922501059312,
          -0.16096751032066234,
          -0.17305440101773298,
          -0.1570233670405656,
          -0.1508844988707376,
          -0.0908635442776526,
          -0.14096052545630064,
          -0.12928713365149822,
          -0.15947255278707728,
          -0.13380381385935092,
          -0.16418007863751533,
          -0.20886976660957915,
          -0.2068022721482381,
          -0.1791614615804634,
          -0.1560373312205414,
          0.013815290680398653,
          -0.08516998260719037,
          1.577254602346486,
          0.07663531469806843,
          -0.20797915361084762,
          0.07612639298450757,
          -0.11386044420918438,
          -0.0522173016541241,
          -0.12394345565910911,
          0.06998752481467957,
          -0.1856502134283645,
          0.03484011897188206,
          -0.18253306793280416,
          -0.17550358676424463,
          -0.1648162307794664,
          -0.1489442348377868,
          0.58695656297123,
          -0.1745811661584156,
          -0.0009434390128665527,
          0.017568588317910083,
          0.33131882472818586,
          -0.1989457931951422,
          -0.18733601660453486,
          -0.20934688071604243,
          -0.20250824519006827,
          0.022944073917396758,
          -0.19318861631048484,
          -0.0623957359253415,
          -0.20323982015331202,
          -0.18997604799363185,
          0.8778371298783642,
          -0.18593648189224246,
          -0.17162305869834302,
          -0.14643143387708,
          -0.1867634796767789,
          -0.2044485092230191,
          -0.19388838366663103,
          -0.2094423035373351,
          -0.08475648371492218,
          5.566914568199821,
          0.5919503572855459,
          -0.11554624738535477,
          -0.17677589104814684,
          -0.1331994693244974,
          -0.1453817828428607,
          -0.1684422979885876,
          0.29187739192721845,
          -0.1512343825488107,
          -0.14684493276934824
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "coloraxis": {
         "colorbar": {
          "title": {
           "text": "color"
          }
         },
         "colorscale": [
          [
           0,
           "#0d0887"
          ],
          [
           0.1111111111111111,
           "#46039f"
          ],
          [
           0.2222222222222222,
           "#7201a8"
          ],
          [
           0.3333333333333333,
           "#9c179e"
          ],
          [
           0.4444444444444444,
           "#bd3786"
          ],
          [
           0.5555555555555556,
           "#d8576b"
          ],
          [
           0.6666666666666666,
           "#ed7953"
          ],
          [
           0.7777777777777778,
           "#fb9f3a"
          ],
          [
           0.8888888888888888,
           "#fdca26"
          ],
          [
           1,
           "#f0f921"
          ]
         ]
        },
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 60
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "fillpattern": {
             "fillmode": "overlay",
             "size": 10,
             "solidity": 0.2
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "x"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "y"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotagem do gráfico - K-MEANS\n",
    "grafico_kmeans = px.scatter(x = X_base[:,0], y =X_base[:,1], color=rotulos)\n",
    "grafico_kmeans.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([['ABADIA DOS DOURADOS', 33, 880.461, 6272, 7.12, 0],\n",
       "       ['ABAETE', 169, 1817.067, 22675, 12.48, 0],\n",
       "       ['ABRE CAMPO', 58, 470.551, 13927, 29.6, 0],\n",
       "       ...,\n",
       "       ['VISCONDE DO RIO BRANCO', 218, 243.351, 39160, 160.92, 0],\n",
       "       ['VOLTA GRANDE', 18, 205.552, 4443, 21.61, 0],\n",
       "       ['WENCESLAU BRAZ', 11, 102.487, 2356, 22.99, 0]], dtype=object)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lista_municipios = np.column_stack((df_final,rotulos))\n",
    "lista_municipios"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Agrupamento Hierárquico"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.18490489, -0.19732361],\n",
       "       [ 0.11844071, -0.18027473],\n",
       "       [-0.12914283, -0.1258201 ],\n",
       "       ...,\n",
       "       [ 0.22773434,  0.29187739],\n",
       "       [-0.21836213, -0.15123438],\n",
       "       [-0.2339755 , -0.14684493]])"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_base"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiIAAAGcCAYAAADknMuyAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAABJlUlEQVR4nO3deXQUVaI/8G9v1Xt30lk6ZCUhQFhlCxBUdkVnZFBxdHRUVGYcfAyojM57zM/Reeo7eFRUdHAZ14cjOqIj7vgUFRUB2RQkGnZICEmA7AlJd9L390e8RXXTCQkEK5Dv55w+6fRSdevWrapvVd2qNgghBIiIiIh0YNS7AERERNR9MYgQERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHRj1rsAkUKhEIqLi+F2u2EwGPQuDhEREbWDEAI1NTVITk6G0dj+4xxdLogUFxcjLS1N72IQERHRSSgsLERqamq7P9/lgojb7QbQMiEej0fn0hAREVF7VFdXIy0tTd2Ot1eXCyLydIzH42EQISIiOsN0tFsFO6sSERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHTDIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemmy/36rlQfaII50KR3MYiIqJuyW0wd/iVZ6rguG0RG/s9KGK0OvYtBRETd1IiMWCyblccwcprx1AwREVEUG/ZV4GiwWe9inPW67BERANhw12Q4FJPexSAiom6kPtCMEfd/oncxuo0uHUQcigkOpUsXkYiIiE4BT80QERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHTDIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemGQYSIiIh0wyBCREREumEQISIiIt0wiBAREZFuGESIiIhINwwiREREpBsGESIiItINgwgRERHphkGEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHTDIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREenmlILIAw88AIPBgNtuu019raGhAbNnz0ZcXBxcLhemT5+O0tLSUy0nERERnYVOOoisX78ezzzzDAYPHhz2+u233453330Xy5Ytw6pVq1BcXIzLL7/8lAtKREREZ5+TCiK1tbX47W9/i2effRaxsbHq61VVVXj++efxyCOPYOLEiRg+fDhefPFFfP3111i7dm2nFZqIiIjODicVRGbPno1f/vKXmDx5ctjrGzduRDAYDHs9JycH6enpWLNmTdRhNTY2orq6OuxBRERE3YO5o1947bXXsGnTJqxfv/6490pKSqAoCmJiYsJe9/v9KCkpiTq8BQsW4L//+787WgwiIiI6C3ToiEhhYSFuvfVWvPLKK7DZbJ1SgPnz56Oqqkp9FBYWdspwiYiIqOvrUBDZuHEjysrKMGzYMJjNZpjNZqxatQqPP/44zGYz/H4/AoEAKisrw75XWlqKpKSkqMO0Wq3weDxhDyIiIuoeOnRqZtKkSdi6dWvYazfeeCNycnLwn//5n0hLS4PFYsHKlSsxffp0AEBBQQH279+PvLy8zis1ERERnRU6FETcbjcGDhwY9prT6URcXJz6+syZMzFv3jz4fD54PB7MmTMHeXl5GD16dOeVmoiIiM4KHe6seiKPPvoojEYjpk+fjsbGRkyZMgVPPvlkZ4+GiIiIzgKnHEQ+//zzsP9tNhsWL16MxYsXn+qgiYiI6CzH35ohIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemGQYSIiIh0wyBCREREumEQISIiIt0wiBAREZFuGESIiIhINwwiREREpBsGESIiItINgwgRERHphkGEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHTDIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemGQYSIiIh0wyBCREREumEQISIiIt0wiBAREZFuGESIiIhINwwiREREpBsGESIiItINgwgRERHphkGEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHTDIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemGQYSIiIh0wyBCREREumEQISIiIt0wiBAREZFuGESIiIhINwwiREREpBsGESIiItINgwgRERHphkGEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbjoURJ566ikMHjwYHo8HHo8HeXl5+PDDD9X3GxoaMHv2bMTFxcHlcmH69OkoLS3t9EITERHR2aFDQSQ1NRUPPPAANm7ciA0bNmDixImYNm0atm3bBgC4/fbb8e6772LZsmVYtWoViouLcfnll5+WghMREdGZz9yRD0+dOjXs///5n//BU089hbVr1yI1NRXPP/88li5diokTJwIAXnzxRfTr1w9r167F6NGjO6/UREREdFY46T4izc3NeO2111BXV4e8vDxs3LgRwWAQkydPVj+Tk5OD9PR0rFmzptXhNDY2orq6OuxBRERE3UOHg8jWrVvhcrlgtVoxa9YsvPXWW+jfvz9KSkqgKApiYmLCPu/3+1FSUtLq8BYsWACv16s+0tLSOjwRREREdGbqcBDp27cvvv32W6xbtw633HILZsyYgfz8/JMuwPz581FVVaU+CgsLT3pYREREdGbpUB8RAFAUBdnZ2QCA4cOHY/369Vi0aBGuuuoqBAIBVFZWhh0VKS0tRVJSUqvDs1qtsFqtHS85ERERnfFO+T4ioVAIjY2NGD58OCwWC1auXKm+V1BQgP379yMvL+9UR0NERERnoQ4dEZk/fz4uvvhipKeno6amBkuXLsXnn3+Ojz76CF6vFzNnzsS8efPg8/ng8XgwZ84c5OXl8YoZIiIiiqpDQaSsrAzXX389Dh48CK/Xi8GDB+Ojjz7CBRdcAAB49NFHYTQaMX36dDQ2NmLKlCl48sknT0vBiYiI6MzXoSDy/PPPt/m+zWbD4sWLsXjx4lMqFBEREXUP/K0ZIiIi0g2DCBEREemGQYSIiIh0wyBCREREumEQISIiIt0wiBAREZFuGESIiIhINwwiREREpBsGESIiItINgwgRERHphkGEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6casdwGIiEgHQgDBer1L0TUFmjXP6wGYdCtKl2ZxAAbDKQ+GQYSIqLsRAnhhClC4Tu+SdE3CCuDFlucPZQOGRl2L02WljQZuWnHKYYRBhIiouwnWM4S0wWFoxF7bNXoXo+srXNvSlhTnKQ2GQYSIqDu7YyegOPQuBZ1JAvXAw9mdNjgGESKi7kxxnPIeLdGp4FUzREREpBsGESIiItINgwgRERHphkGEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHTDIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemGQYSIiIh0wyBCREREumEQISIiIt0wiBAREZFuGESIiIhINwwiREREpBsGESIiItINgwgRERHphkGEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHTDIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemmQ0FkwYIFyM3NhdvtRmJiIi699FIUFBSEfaahoQGzZ89GXFwcXC4Xpk+fjtLS0k4tNBEREZ0dOhREVq1ahdmzZ2Pt2rX4+OOPEQwGceGFF6Kurk79zO233453330Xy5Ytw6pVq1BcXIzLL7+80wtOREREZz5zRz68YsWKsP9feuklJCYmYuPGjRg7diyqqqrw/PPPY+nSpZg4cSIA4MUXX0S/fv2wdu1ajB49uvNKTkRERGe8U+ojUlVVBQDw+XwAgI0bNyIYDGLy5MnqZ3JycpCeno41a9ZEHUZjYyOqq6vDHkRERNQ9nHQQCYVCuO2223Duuedi4MCBAICSkhIoioKYmJiwz/r9fpSUlEQdzoIFC+D1etVHWlrayRaJiIiIzjAnHURmz56N77//Hq+99topFWD+/PmoqqpSH4WFhac0PCIiIjpzdKiPiPTHP/4R7733Hr744gukpqaqryclJSEQCKCysjLsqEhpaSmSkpKiDstqtcJqtZ5MMYiIiOgM16EjIkII/PGPf8Rbb72FTz/9FJmZmWHvDx8+HBaLBStXrlRfKygowP79+5GXl9c5JSYiIqKzRoeOiMyePRtLly7F22+/Dbfbrfb78Hq9sNvt8Hq9mDlzJubNmwefzwePx4M5c+YgLy+PV8wQERHRcToURJ566ikAwPjx48Nef/HFF3HDDTcAAB599FEYjUZMnz4djY2NmDJlCp588slOKSwRERGdXToURIQQJ/yMzWbD4sWLsXjx4pMuFBEREXUP/K0ZIiIi0g2DCBEREemGQYSIiIh0wyBCREREumEQISIiIt0wiBAREZFuGESIiIhINwwiREREpBsGESIiItINgwgRERHphkGEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHTDIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemGQYSIiIh0wyBCRERE7SfEseeB+vD/TwKDCBEREbWPEMCSacf+fzgbeOGiUwojDCJERETUPsF64MCG8NcK17a8fpIYRIiIiKjjbv2uUwbDIEJEREQdZ3F2ymAYRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemGQYSIiIh0wyBCREREumEQISIiIt0wiBAREZFuGESIiIhINwwiREREpBsGESIiItINgwgRERHphkGEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbhhEiIiISDcMIkRERKQbBhEiIiLSDYMIERER6YZBhIiIiHTDIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3Zr0LQERnCCGAYL3epaDOEKiP/pzOXBYHYDDoXYqTwiBCRCcmBPDCFKBwnd4loc72cLbeJaDOkDYauGnFGRlGeGqGiE4sWM8QQtSVFa49Y49Y8ogIEXXMHTsBxaF3KYgIaDm1doYf1WIQIaKOURyA4tS7FER0luCpGSIiItINgwgRERHphkGEiIiIdMMgQkRERLrpcBD54osvMHXqVCQnJ8NgMGD58uVh7wshcPfdd6NHjx6w2+2YPHkyduzY0VnlJSIiorNIh4NIXV0dzjnnHCxevDjq+w8++CAef/xxPP3001i3bh2cTiemTJmChoaGUy4sERERnV06fPnuxRdfjIsvvjjqe0IIPPbYY7jrrrswbdo0AMCSJUvg9/uxfPly/OY3vzm10hIREdFZpVP7iOzZswclJSWYPHmy+prX68WoUaOwZs2aqN9pbGxEdXV12IOIiIi6h04NIiUlJQAAv98f9rrf71ffi7RgwQJ4vV71kZaW1plFIiIioi5M96tm5s+fj6qqKvVRWFiod5GIiIjoZ9KpQSQpKQkAUFpaGvZ6aWmp+l4kq9UKj8cT9iAiIqLuoVODSGZmJpKSkrBy5Ur1terqaqxbtw55eXmdOSoiIiI6C3T4qpna2lrs3LlT/X/Pnj349ttv4fP5kJ6ejttuuw33338/evfujczMTPz1r39FcnIyLr300s4sNxEREZ0FOhxENmzYgAkTJqj/z5s3DwAwY8YMvPTSS/jzn/+Muro63HzzzaisrMR5552HFStWwGazdV6piYiI6KzQ4SAyfvx4CCFafd9gMODee+/Fvffee0oFIyIiorOf7lfNEBERUffFIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemGQYSIiIhOgubmpm3c6PREGESIiIio45Zedez5kktPOowwiBAREVHHFW869vzAeiBYf1KDYRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0g2DCBEREemGQYSIiIh0wyBCREREumEQISIiolPHO6sSERGRbl695qS+xiBCREREp+7gphN/JgoGESIiItINgwgRERHphkGEiIiIdMMgQkRERLox610AIiIi0hACCNa377OB+ujPT8TiAAyGjpXrNGEQISIi6iqEAF6YAhSu6/h3H85u/2fTRgM3regSYYSnZoiIiLqKYP3JhZCOKlzb/qMupxmPiBAREXVFd+wEFEfnDjNQ37EjJz8DBhEiIqKuSHEAilPvUpx2PDVDREREumEQISIiovY5yR+2awuDCBEREZ2YEMCSaZ0+WAYRIiIiOrFgPXBgQ6cPlp1ViYiIzgbtuRFaR2+A9jPc+IxBhIiI6Ex3MjdCa89lvD/Djc94aoaIiOhMd7puhPYz3PiMR0SIiIjOJp1xI7Sf8cZnDCJERERnkzPsRmg8NUNERES64RGR7qQjPy1NpHWyPzVOFKkL/fw8dQ0MIt3Fqfy0NJFWF/vBLDrDdKGfn6eugadmuouf66eliYja0oV+fp66Bh4R6Y5Ox09LExG1pQv+/Dx1DQwi3dEZ1qOaiIjOXjw1Q0RERLphECEiIiLdMIgQERGRbhhEiIiISDfsrEpEdDbrKjcy7Go3xeON1VonRPg8EuK0jo5BhIjobNVVb2TYFS7j5Y3VoovWZpZcCvzu49M2SgYRIqKzFW9k2Dp5Y7Uz8VYG0Y5yneiIU3uPAEVrMwfWn9ajagwiRETdAW9k2KKr31hNexokUH98gGjPUa5o03cyR4Bu/Q5YdE77P3+SGESIiLqDM/lGhqern0tn9lXpjD4nQgBLph37/+Hs4wPEyR7lOpkjQJafp70wiBARUdd1Ovu5dOaRkc7ocxKsBw5sCH+trQDRnqNcnXkE6DR1WuXlu0RE1HWdKf1cOvvH/G797sSfkUe52nx00um4yKM1nYhHRIiI6MzQFfu5nK4+J6d6WkSezmqtE2tHTyUFjx5/tKaTdN8g0lWurf+5dLVr+H9uvGcA0ZnvTO7n8nNq7XSWNjC161SS5lTMabyXSPcMIl312vqfS1fuMX668J4BRHQqWtt57azLZjtTe05ntafz6tKroj/vZN0ziJwp5xyp85zJ9wwgIn21d+e1sy6bbRlp+PhPVuTprI6cSiredOz5wU2tf+4Udc8gotUVzzlS5+nq9wwgOhUnOsXckVOyPH3ZulPZeT3ZnSDtEQh5Z9OTmT8dPZ11mm/nHg2DSHc959jd+sgA3advDDco3UNHTzGfKJCf7tOXJ7vO6az+bZ21XLR35/VUd4K0RyPknU1PZVvVWudVbb2cxitj2sIg0h111z4y3eXICPvDdA+dfYq5cC1Qdzh8I9tZG+/OWuecyjLcWcuFnjuvkT9GJ59Hu/uq9nlbnVe19RLtPiY/AwaR7oh9ZM5u0TYoZzoe5QkXuUG6dUtLHVnsrdeT3Ntta0MTuaHvrI13V1jnnO5+YpFHfDq7E2sodHyYkPMrNRe46f8Ao/H4oxpLLgWuX956/ReuBQJ1gNXV/rJ0sjMviHTGKYXOvJS1q60g21M/0VZgJ9LWCu5M054V8pnubDv6k5oLXLf8522DXW3ZlqLt3S4a3PK3reAQqOt4m5eh1hnfvrpoz5Ulba1zTnY9I0TLfS6iCdYfq59AffTPnupRoBMd8Ym2PMo2rTiPjS8Uan0cwaOtD79oPfDcJOB3K48/qnFgfXj937EDePXq8M/IPig69A8BTmMQWbx4MR566CGUlJTgnHPOwRNPPIGRI0d2bCBCtCw82v9fngYUdeIG5FRX2B1dQZ7OldvJHP6UC+iJ6HG4/3T1YzmNN+ah06RoPbAg5ecd56mEn9O1nAvREgza2ruNDA7R+ga0dgQlWkh/ODv6RjNa2dqz/mlrnXMy65mOrPfas74/URkiT3vIuu3oER/ZprV129TQ+ueXXnns+a1bjq/H4k3AcxcA0Yr9yq81Zcbx678D64HGWuDlSzs2DZ3EIETnR6B//etfuP766/H0009j1KhReOyxx7Bs2TIUFBQgMTGxze9WV1fD6/Ui7bbX8WPOc3AcXNvZxdNXtJWbNqFb7MeeK47oKzTtBlo9R/jT907nnvDcLdEP92vLLLV3D6O1sHE6QufPLXkYcPW/ok97W3twkqzDE+3BSSfam2xtnIF6ABHvafdY5XAD9cDj7Qyu3V3KcOA3r4Uv19p509q8VRzhr8nPyfkRbYNrcQLBuvDX5HrGbAdevLD15Sg1F7hqact4DIaWcbcV+FJzgStfAWyulmE3/VTOxrqWMndG+5i7peWvrDO5fpF/5XoROBYCOnu9d8tawJvaEgyc8S07xLJekocDM95pGe9rV7e+U5M8DLjixZaAIQSwsHfb40zJBX71BPDU6BOXb863wBNDOjJFxyQOAsq2tjz3DwZKf6rvpHOAknbcVr4N1Y0C3gdqUFVVBY/H0+7vnZYgMmrUKOTm5uLvf/87ACAUCiEtLQ1z5szBf/3Xf7X53bAg4pkNh6GxcwvXYwhwzbKWxvy/lwDFmzt3+J2tx1DgipcA60/nNS32U99AywXEGf/z1IFc2RkMLfUuw1PFfuCDecDBb0/v+LuLHkOBa14H6o8AsenH6tmVABzZC7w1s2sHux5DgGlPtay4648AMWktrwfqf2o3dcAbN3T9ZfZ0SBkOXPUq8Eifjn0vWkhpS9IQoOTb9n1WcQGB2vYPO3kEEAqe8sYOAJAyAhCh8CtL2tJjSMs674mhx7+XNLTlKMLBVtrVydZ92Dg0G3mzA2g6O6/g6zJBJBAIwOFw4I033sCll16qvj5jxgxUVlbi7bffDvt8Y2MjGhuPhY2qqiqkp6cj5ZaXsMHzJzgMgc4s3jF/KgAW9j09wz5TdJc66C7T2Zr5RcCCVL1LcWbq7m2HqAOqGwXSHq1FZWUlvF5v+78oOtmBAwcEAPH111+HvX7nnXeKkSNHHvf5e+65R6DlrBUffPDBBx988HGGPwoLCzuUG3S/amb+/PmYN2+e+n8oFEJ5eTni4uJg6Io91omIiOg4QgjU1NQgOTm5Q9/r9CASHx8Pk8mE0tLSsNdLS0uRlJR03OetViusVmvYazExMZ1dLCIiIjrNOnRK5ifGzi6EoigYPnw4Vq5cqb4WCoWwcuVK5OXldfboiIiI6Ax2Wk7NzJs3DzNmzMCIESMwcuRIPPbYY6irq8ONN954OkZHREREZ6jTEkSuuuoqHDp0CHfffTdKSkowZMgQrFixAn6//3SMjoiIiM5Qp+U+IkRERETt0el9RIiIiIjai0GEiIiIdMMgQkRERLphECEiIiLdMIgQERGRbnS/xbtWcXEx3nzzTQwcOBBbt27Feeedh2HDhuHzzz9HTU0NLrroIlgsFnzzzTcYOXIk9u3bh4yMDPX7paWl8Pl8+Oc//4na2lpcc801aGxsxHvvvYfExESMGTMG1157Lc455xxMnjwZeXl5ePvtt3HRRRchISHhuPI8/fTTWLlyJXJzc/G///u/SE1NxbRp0zBjxgw4nU58/vnnGD9+PEpKShATE4OHH34Y+fn5GDFiBD7//HOMGTMG/fr1w7Rp09pdB5999hnKysqQmpqKc889N+w9IQSKi4vhdDrR0NCAUCiExMREHDlyBJs3b8bixYtx1113YdSoUfjHP/6Bm2++Wa3Xxx57DPfcc09YuSPJeo20dOlSvP7667Db7dizZw9ycnKwcOFCxMXFqZ/54osvkJqairvvvhvV1dW44447MHbsWPX9r7/+GoWFhdi2bRu+++477Ny5E3a7Hb/5zW+wevVq/P73v8ewYcPUety6dSsWLFiArKyssPLKur711ltRUVGBzMxM9O3bF9OmTcMLL7yA2bNnw+FwRE5Ch9XXH/t1zGeeeQZutxu9evXCk08+CbPZjLi4ODz00EN48803ceDAAaSmpuLyyy+H3W7Htm3bMGDAALWszz77LGprazFy5EiMHTsW//znP3HgwAHMnDkTPXr0UNv3xIkT1flTU1OD8ePHY/HixSgqKsKFF16IX/3qV2qZVqxYgYsuuiiszNFek7RlqaiowHXXXQe/349nnnkGf/jDH8Lq7OjRo1GnC4A6bQBQWVmJnTt3oqmpCR988AGuuOIKDB7c8jPwxcXF6m2etfWxf/9+jBw5Eueddx5mzJiBa665Bk6nEzt27EDv3m3/THpxcTE2bNiASZMm4amnnkJmZiZGjRqF++67D7feeitWrlyJrVu34r777oPb7UZDQwOWL1+Ot956C9dffz1+/etft3f2h43zueeew7x58/DCCy9gwoQJGDRokPp+Q0ODWleBQAClpaUwm82YMGFC2PzS+v7771FbW4vRo1t+7v3jjz/G5MmTT/iTFtu2bUNmZiaAlnXdnXfeicTERDQ1NeGuu+7C8uXLYbPZ8Pvf/z5sWHv37sUHH3yAN998E4cPH8ZNN92Ea6655rh1Xn19PXbu3Amfz4eXXnoJF198Mf7xj39g2LBhCAQCat1qb8NQWVmJ5cuXY+PGjfjtb3+L0aNH4/PPP8e6devw7bff4qKLLsJ7772HjIwM3HnnnYiLi8PSpUtx5ZVXwmaztav+169fj/79++PDDz/EhAkTEBcXp7YtWf979+7FkSNHkJSUhJycHPzqV7/C6tWrUVRUFLYuLS0thc1mw6uvvori4mL88MMPePLJJ5GQkNDqelGud1NSUtQytecW5sXFxfjss89w4YUXIhgM4o033kBdXR0SEhIwfvx4rFq1CocOHUJdXR3mzp0bdRvUGm2biWxPWpHrschlXaupqQlFRUVYtWoV1qxZg1GjRuE3v/kNtBfWtjUM7bqhw07yt+063Z133ikcDodITk4WRqNRuN1uYTAYhMViEYmJicf9qI7FYhFGo1GYTCZhMBiEwWAIe261Wk/4wzxWq1WYzWZhMBjU10wmkzAajVE/C0D9rPY78nty3NHeVxRFfW40GoXdblfHY7FY1M/L5waDQSiKIsxmszCZTMJmswmn0ykURREGg0G4XC51PFarVRiNxrBxms1m9bn2davVKhITE1udTrvdLmJiYoTH4wmbHjl8k8kU9lmDwSCMRqMwm83CZrOp35fDlnVss9mOm97IOjKbzcJutwuz2azWl9VqFQaDQdhsNnUeyLLYbLawupfD8fl8wmw2C6/XK2w2m1oXFotFxMfHC7fbrX5XO+6MjAzRt29fMXXq1LDxGI1Gta0piiIsFkvYdx0Ox3HzXVtP2nkR2Ra8Xq/o37+/MBqNwuFwhM0z+VpkWbXtSDseWV45PoPBINLS0kTfvn2Pax/acRiNRmGz2USvXr3E4MGDhdVqFU6nM2w+xsTECKfTGXX6Iocp27bD4VDndbTPR2sDsl0mJSUJr9erjl/+jfx8ZH3I9ULkZ2Wda8vR1rC0bS/aMiuHE9n2tPNBtrlo0y6nUzt8r9crzGbzceWX45B/I+e7fB7ZLlubPrnstDZPtH9lW3I4HGHLkdlsFg6H47h1iHZeR85f+T3t8OX3XS6X+nk5HdrhyM/KdY3FYgmbH9GmwWQyCbvdrrYJWd/R2l20+ROtrUZbjkwm03HtKiEhQS2jdjplWzQYDMLpdIa9p10vyOFYLBa1/HK+yTbV2jpc2w6jDVe2Ze1r2rajKIq6LpLDkGXVzofIeeN0OsUNN9xwUtv/LhNEZs2aJbxerxgzZkxY5UbO9GgBQzZubUPT/q9tPJENQzuTooUIbYVHa5yRM1h+RgacyGHK8rTV6KM1yMgFQjsO+Z7H42m1UUaOVztOr9fb6oIZ2UBbW+hbK+uJFvDIjXRkvbc1Pm3Z2mozrYXD1l6LVo7IlZdcycn/o4WFaAE3so229pD1Em2lLv/KMBpt2lsLCjExMW3Oj7bmQ7T2Htnu2/PQbpwj53O0epTzWRvULBZL1GU3WtuIrFNtm5M7OR6PJyzERJue1sJQZNiKnCaLxaJOl9ywnGiYkRvstpbPyB0QbSCVG225oWhtmYwMNrKMbW3o5Pgi17nR5klb6wk5bpfL1eb4WqsDWVdy29DWejDaQ9vmou3MaXeAtPNNG0KjTat2p6Cth7Zda7dPkW0jcrumrT/tfIjcKdaOQztfI+s6Nja2zTanbbfRtstyR23atGlizZo1Hdr+d5k+Ivv27YPRaERZWRni4+NhMBjgcDhgMpkAQP1rNLYU2W63w2AwwGAwQFEUGAwGDB06FKIlXKmfkeT3AoEAAMDhcKjfNxgMMJlM6vfMZrP6utPpBAAIIWA0GhETE6P+SJ/RaITBYIDZbFbL2NzcDKDlMJf8jvy+/KzFYgEA9fCpPMUhX1cUJaz8Fosl6mHb5uZmuFwutczNzc1qmUwmU9j0GwwGJCQkqMOR5ZTTKcuamJgYNg5ZFoPBgKamJvV1q9UKo9Gozhez2QyTyaQO32g0qodeZR2YTCa1DLLO5DxOS0sL+6zH4wFw/A8gyvFop8tsNqvTqp2niqLAaDSq8zUrKyus7uV8tlgsMBqNMJvNcDqdMJlM6rTJ8rjdbrWugZbfT9IeWm5sbAybdjkOo9EIo9GIUCgEg8GAUCiktlFZF9qHrBc5L2X9CyFgtVrV94FjbVm2j8g2IqdH2+aOHj0Kg8Gglj0UCqnDsNlsap1JNptNrVuj0QiLxaLWvxyfyWSCyWRSyxYbGwsA8Pv9MJlMmDVrVli55LKhLbvJZIKiKAgGg+q45HIm26q2/puamtDc3KyWweFwqMuqnF+yPJHLt6Ioan2Ul5er9SLnjaxLbT3IeQC0/KiXHCYABINBdd5qyymXRaDlFIKcFu2yIcfn9XrD1iey7NoyKIqCnj17hi0Dsi3JeST/1y7Tsv3V1dWp49LOu+bmZrXs2vqV5ZHzXc57bZlkOWW7kYfsI9tjamoqzGZz2LIBQG1z2jrSLg+SnB45fO0Ppcr2IduOtl1o25Eso3YZkrTrFG355DRGtn0hBJqbm8O2GfK9+Ph49TWDwaC2BznM2NhYuN1u9bXm5ma1jNp1rHbdK6cFaFlmtD8sZ7FYYDab1bLIthm5fdMKhULqPJfr3urq6rDlRK4nZNvSbjO09WQwGNC/f3+43W7ExMQgMzMTK1asOK6O29Jl7qy6ZMkSLFu2DOvXr4fD4UBFRQXcbjd8Ph9cLhfWrVsHv9+PiooKNDY24tZbb1Un1mQyYceOHUhOTobP50NVVRUsFgsOHjyIYDCIUCiElJQUHDlyBLW1tfD5fEhISMCgQYOwa9cuFBcXIzs7G9u2bQPQEgwaGhpQXl6OtLQ0XHDBBXjhhRfgdDqRkJCApqYmbN++HSaTCcnJybjyyisxbdo03HTTTTh48CCampoQCAQQCoVgMpnQs2dPAC3n60aMGIHKykoUFBSgqqoK6enpiI+PR01NDSoqKhAIBFBfX4/GxkYMGTIEdXV16NOnD8rKylBSUoKioiK43W4cPXoUJpMJbrcb1dXVSE5ORt++ffHll1/i+uuvx7p167B9+3ZUV1fDYrGgubkZGRkZuPrqq/HKK6+gsbERtbW1qKqqUjckDocDf/rTn/D5559j48aNSE9PR319PbZv346srCzU1dUBAA4dOoRx48YhPz8ftbW1cLlcMJvNUBQF1dXVcLvdqK2tRWJiIqZMmYKXXnoJ9fX1GDZsGA4ePAiz2Yy6ujqUl5cjNTUVycnJMBqNiIuLw/bt21FUVIScnBzExMQgISEB2dnZWLRoEQYOHIgtW7agV69e2LlzJ+rr69UFSoaoX/ziFxBC4P3338fvf/97PPvss2qd5uTk4IILLsBHH30Ev9+PzZs3w2KxoLq6Gk6nE3l5efjtb38LAPjwww+RmpqKDz74AFlZWXC73XjrrbdgNpuRlpaGqqoq7NmzBxaLRT1nLufVDz/8gEWLFuGBBx6A2+3Gnj17UFVVhUAgAIfDgZycHBw4cACjR49GVVUVysvLYTQaEQgEsHv3bgQCAdhsNgQCAcTGxqKqqkrdeFssFuTm5mL79u1QFAVNTU3w+/3Ys2cPUlNTYTAYsHv3boRCIYwcORIzZsxAVVUV1q5di/z8fOzYsQMGgwFTp07FoUOHUF9fj/LycpxzzjmYMGECmpqa8M477+D7779HQ0MDgsEgFEWB1+tFSUkJ7HY7fD4fMjIysHnzZtTV1cHhcKChoQF+vx9Dhw7Fp59+qm5wte0iFAohNjYWNTU1AFpWtNnZ2aitrUUwGERZWRmEEAiFQpg4cSIOHjyorqD9fj++/PJLDBo0CF988YW6gY2Pj4eiKJg3bx5ef/11DB8+HMuXL0dzczOCwSBiYmLUFbXX68WmTZvQv39/FBUV4ejRo2pQCwaDqKurQygUQnNzMxRFQWxsLOLi4rB161bY7XZUV1fDYDDA7/fD6XSqP11RX18Pm82GhoYGdaXv9XqRnJyMAQMGID8/Hzt37lSDQEJCAtxuN6xWK8rLy1FXV4f+/ftjx44daGhoUPu9HThwADU1NXA6neq653e/+x0eeugh9O7dG5WVldi2bRt8Ph/sdjsOHTqkLo99+vRBc3Mztm/fDrPZrNZ7TU0NrFYrxo0bhx9++AGHDx9GXV2duvyPGDECX3zxBZqbmzFhwgSMHDkSn332Gerq6pCVlYWBAwdi9erV2LVrF3r16oX169cjLi4OBoNBXddUV1ejubkZWVlZqK+vR2FhITweDywWC8rLy+FyudCzZ0/Y7Xbs3bsXdrsdzc3NaG5uRm1tLbKyspCcnIyqqip89913MBgMqKmpgc1mg9vtxtChQ1FXV4dzzjkHS5YsQTAYRFJSEsrKymA2m5GQkICysjI0NTVh8ODBKCsrQ3FxMQYMGIB9+/bhsccew6xZs5CcnIzDhw/DarXCYrEgPT0d+/fvR3l5ORRFgdPpRHx8PPLz85Geno7m5maUlJTA7/cjGAyioqICZrMZc+bMQWFhIf7v//4P9fX18Hg8MBqNqKmpgcPhgMPhQH19Pfr164dt27ahT58+qKiowLhx4/DUU0+pbTMUCqG+vh6BQACKosDtduOXv/wlNm3ahCNHjqCmpgZNTU1ITEyEEAKVlZWora1FU1NTWMiSO4lJSUnweDzo378/du/ejfr6ehw6dAg1NTUwGo0oLi6G1+vFsGHDkJ+fjwEDBuCbb76B3+/H/v374XK5MGzYMBQXF+Pcc8/Fv//9b7jdbhgMBhw5cgRNTU2IiYlBZWUlBg0ahOuuuw47duzAokWLOrz97zJBZO7cuVi5ciXmzp2Le++9F36/Hz/++CNiY2PhcrnUlX5ubi5Wr16NrKws7NmzB8OHD8d5552H+fPnY8KECYiNjUVRURHsdjv279+P3r1748CBAxgwYAC2bt0KIYTaqLOyslBeXo7Gxkacf/75yMrKwqZNm9Q99KamJrz77ruor69HZmYmDh06hKamJjVgWK1WjB49Gtu3b0dFRQXKy8vh9XpRW1sLk8mEQCCAhIQENDc3Y9KkSVi9ejXi4uLg8Xjgdrtht9vx/vvvY+rUqSgtLcUnn3yCHj164OKLL8Znn32G3r17o3fv3sjMzMSuXbvw3HPPYeLEiVi9ejUWLlyI22+/HVarFbm5udi3bx+8Xi8OHz6MsWPHomfPnliyZAkGDRqEL7/8EomJiSgqKsLkyZOxf/9+XHvttXj99ddhMBhQUlKCcePGoaGhAWvWrMHSpUuxfPlypKWl4bzzzsPMmTNRVFSESZMmYdu2bRg1ahTWr1+Pa665BsuWLUNjYyN8Ph8effRRfPHFF3j44YcxatQoVFZWYseOHaipqcGgQYOwc+dO3HjjjXj66afxhz/8Ac8++yxuueUW7N27F0IIrF27FjabDdu3b0djYyP8fj9uu+02PPHEE1iyZAlSUlLw61//Go2NjSgqKsKwYcPw5ZdfYsyYMdi4cSM8Hg+8Xi8uvPBCfPPNN3C73Zg/fz5CoRAWLVqEPXv2YMCAARg6dCh27NiBLVu24ODBg/jb3/6Gd955B3369EFtbS2MRiNee+01dY+moaFBDSpXXnkl7r//fvUIR3NzM/bu3QuPx6MumKWlpRgxYgS+//57BAIBpKenY8eOHTCbzfD7/SgvL4fZbIbb7cbUqVOxYcMGVFRUYN++fUhISMC9996LJ598EgcPHkR9fT1mzJiBTZs2Yd26dRg4cCCqqqowefJkfPbZZ0hLS8P27dtx/vnnY9euXdixYwcuueQSNfA5nU6183R5eTlCoRBKSkpQX1+PjIwMHDlyBFarFVOnTkVBQQEGDx6MZcuWYc2aNZg0aRJSU1PVleD48ePx/vvvw+12Y/jw4XjzzTfx61//Gv/617/Qu3dv5Ofnw+fzoaamBsFgELGxsXA6nSgqKkK/fv1QU1ODtLQ07Nu3Dz169EBFRQX8fj/69euHl19+GaNGjUJqaio+/vhjNDc3IzU1FR6PBw0NDaitrQUAJCQkoH///vjiiy9QVlYGk8mEI0eOwGQyqWEtNjZWXalbLBZ15yMvLw+jR49GZWUlDh06hPT0dJSUlKCiogLnn38+VqxYoY53y5YtSExMxKFDh1BdXY0jR45g4MCBqKurw+HDhzFq1CgcPHgQP/74I+666y787W9/g6Io6NGjBywWC4qKilBRUYGXX34Zd999N5qammC1WmGz2ZCfn4+8vDxs3rwZXq8X5eXlsNlseOWVV/D4449jw4YNGDFiBHbs2IGrrroK//jHPzB27Fh88MEHAFqOIoRCIZSXlyMYDKo7X/K97OxslJeXY8CAAXC5XPjwww/VoyM2mw0VFRXo2bMncnNz0aNHD2zatAlutxsff/wx7Ha7uvdcXl4Oi8WCYDAIIQQ8Hg/69euHo0ePorCwEA6HA4cPH0Z8fLw6fpfLBYPBgN69eyMrKwvnn38+HnnkETidTnz//fd4+OGHsWzZMmzduhV//vOf8cknn6BXr15qZ9ejR4+iuLgYI0aMwOuvv46ioiLU1NQgJiYGPp8P33zzDQCgV69eqKysRCAQQFxcHLZt24bk5GSUlJQgLi4OpaWlWLhwId544w3069cPa9euxYgRI7Bt2zb88MMP6NGjB6qrq3H48GHExsaisbERXq8XeXl5GDhwIHw+H9577z3U1taqO4l33HEHqqqq8OqrrwJoObIRCATQr18/td0cOXIEP/zwA+rr6yGEgNfrRUFBgbpeEUIgLi4OZWVlMBqN8Hg8SEhIQEFBAebPn4+VK1ciIyMDlZWVCAaDSElJwaFDhxAMBlFdXY3KykpcddVV+Oijj3Dw4EEUFRUhLS0NFRUVCIVCuPDCC3HgwAHMmjUL69atw5o1a3D06FGUlZUhOTkZwWAQw4cPVy966Nu3LwYMGIBnnnkG27dvRygUgtlsRlNTE2JjY9WzAk1NTejTpw8uv/xyvPDCC9i/fz/sdjsuvvhifPLJJ1AUBenp6bDb7RgwYABuvvnmsIsZTqhjPTlOn//3//6fcDqdakdKRDkvBbTepwBo6evQ2nuRHZ9ae0R7/0Tfifb5aOeo2ztOeX6vI+PVnqOO9tCexz/RcLXnmFs79xltXsjPt9a5UvvQdgRs6/xxe+urrc9rO/lppzHaZ+U0yD4dkZ2M5bRF+35rnfQi20XkudZoHeDaM79bq79o8zLaeW4gel+K1sbT2vvaDpYnaletla8j0x5tmrWd6drTJk40vPZMS2vfaatOT9R2T1SP8n2LxdLqPJXzRHYO1fah07bvE41PWzbt8qp9nGhZj/xOZN+X9s4LbX+kjraVEz0URYna36M9/dQiX+toO4pcx57M40TlbM/wo31G9itpz/ZIlsHj8YiLLrpIzJgxo0Pb/y7TR+S+++7DsGHD4PV6w86dR56nlaxWKzIzM9VzvUDLeV7g2HkreW6rR48e6vkweUhX9iEAoF6OJ88nynOBsv+A0+mEoihISkoKK4M8JQG0HGaeMmWKeo5NnkcbMmSIethMDl87Tdp+FnKPRWj6uWjPq8pDzPI78jyzPG+r7Wsi9+a1/V0kbfm0deJ0OtXzyUKIsHP58lClHB9w7JyhrEf5uiyXz+dTyyXPy8tD24qiqKc0ZH8QeS5VjlN7jl07DYaf+g9p++rccMMNx02nrDd5Ltfn86nfF5r+O9o+DxaLRa1/2e9G2zYaGhrC5oc8baHtHyOHo60bp9MJl8ulnnu32WzqPJRHV5KTk487N63tH5SZmQlFUdQ2pu2bBLT0KZJ9aiL7DDQ2NgLAcX0BtP0oABy3FxMbGxvWn0NOpzxnLqfD5XLBZDIhJSUFeXl56nSbzWaMHDlS/Y6iKGF9VmT7lIeVtX2OZDuSw+rRo4daLvHTHrost1z2ZZmj9QuQ7VyOUzvdcpnQtgWfz6eWzWAwoE+fPup7sg3IvVr5XTkObXtwu93q510uV1i7lvWoLYekbQvys3L+NTc3o6mpSe0v4HQ6w/o6NTU1IRgMorm5Wa1ro9GoLmOR7QBoaUdJSUlqXzjZL0Rb51J2djYMBgNycnLU6dX2IfH5fFAURa1XWQeyf4p8aOe5tj+dJNcN8v3MzExYrdaw/nupqalh69E+ffrA6XSG9T0CjrVt+X35ED/194gk54usg8j+Mdr1unZ5k/NBO/9km5HtctiwYer0ybZit9vDhi/Xx9q6MGj6d/Xq1QtGoxG9evWCzWZTPxvZr06OX7u+1L4uX1MURa0boGV5k/UT+T1FUdT+OnL5t9lsuP7669G7d++O30Lh1I5jdK6lS5eKwYMHq5eFud1uNZFlZmaKX/7yl8Jut6uXkmn39uLj48X48eOF0WgUffv2VYdhNBrFmDFj1CsM/H6/yMnJER6PR+3lG9lr2uv1qnsb8hIsn88nXC5XWI9sg8EQdmmx2WwWLpdL5OXlCUVRol7y63A4wq6gsNvtIjY2Vt3zluWRCVR7iZb28jn5GWhSqby0NDK9yl7w8jW5Vy4vDZafs9vtwmq1iqysLAFA5ObmipSUFGE2m0VMTIx6ua7cy9L2KjebzWLatGlRL42V5ZeX0i5dulTk5OSodSHLKy9D1n5P1pmsZ+2RGofDoZY1JSUlbLxms1kkJSWJmJgYtR1pv68tn8/nE0DLFRQejyesF7t8OJ1Ocdddd6l1aLPZRE5OjjpM7WV10fYgZH1r56XX61UvzdbOK7fbLUwmk0hJSTnu0s24uDj1ffl5WU/aeRk5D+SVUb169VLHn5CQoJbR7XaHtR+32y0SExPFtddeq15KryiKSEpKUqc5LS1NKIoi4uLi1Gk0GAxqfco6GDhwoBg9enTYESM5D9xut1on8jJj7XRpp0G7rPl8PhEfHx+2fLa2l28wGNTLwrVtXtZbamqqesWGtg5lu7bb7SI5OVmdvri4uLAjBHLey1sPyCuToi2jsjxyPmuPrMTHx6v1KF+Xl6Jr24bT6VSXHZPJJIYNGyays7PV9Y08OjR69Ghhs9mEz+cTDodDnH/++SI9PT3scn+fzyeMRqO6fkxKShJWq1UMGjRIOJ1OdViyjNr2KOvQ5/OJHj16hNWd3+8Pm19JSUkiKytL9OnTR13XJCQkhNVjTEyMevWFdr2vbSvyclztUQz5vrws1maziZiYGOFwOMLWq9rl0mw2C6fTKTIzM4+7bF67njP8dBTTZrOJhISEqO1L1ot2+rXLrJwn8jJ/t9st/H6/ur6QV8pMmzZNLFy48Lgjq3IY2vVtYmJi2OsxMTHq/z6fT92+RVsWtNOgfd8QcXRWlsP80+0XkpOTw4Yhy68oirjkkkuEw+EQPp9P9O7dWyxbtqxD2/4uFUTGjBkjevXqJebOnSuuu+46kZKSooaC5ORkkZOTIyZOnCjcbrcwm80iNTVV9OzZU6Smpqr3vXA6nepKOPLSMrkhkGFCvi7vfaEoikhISAi754VsxCaTSbhcLpGamir8fv9xM9doNAqr1are90Fu0M4//3xht9vFZZddJnJyco6774Ddbhf9+vUTfr9fKIoi7Ha72oDkSlOuIOV7sky9e/cWGRkZ6rDkfR969uyprkQHDx4ctqGMbJAylMgVm/Y9p9OpBiar1SpGjhwp4uPjhcPhUFciMuRYLBYRGxsrnE6niIuLCwtziqIIo9EoevfuLex2u+jZs6cYNmyYsFgs6gZQGz7kMCMXbG35TSaTSEhIUDeokde5y792u10dvhyGrNvIw+uRAUWulLSB0u/3C5/Pp25E5AoqNzc3LJzJR1paWlhYkN9xuVzqvRMiV1wmkynsHg2KoojLLrtMZGdni7i4OPUeDh6PR2RlZYnBgweLuLi4qJftARDjx49XA64MZZErO1m32nbh9XqFw+FQN1yKoohzzz1XfZ6eni48Ho9aJhlk5DKoKIrweDwiLy9PZGVlqRsDbV2bTCZ1Qzlo0CB1GRgxYsRx90jRzi+XyyWmTZumll27QfJ4PMLn84mePXuqp2u1GxVZrzJcyWHK9ut2u4XFYhEul0tt406nUyQnJ6sbAG1ZjEajSE5OFi6XS1gsFuH3+8PWH9o2IcevnVfy/kkZGRnC6/VGvVeNxWIRGRkZ6rrN4XCoG9B+/foJq9Uq/H6/ujy43W513Wg2m9X1owxv2rLLevB4PMJutwu/3y9Gjx4tevbsqW6wI8ujKIoYM2aMSE5OFunp6eKmm24Sfr9fDVNy5zA2NlZd1mQ9yKAqw5p2eYu2oyDnvby8VNtWfT6fGDBggNqWZHkj27YM09odPLnOlG1Qziv52aFDh6rDTUlJEb1794562av2lhLy3k+RQSUuLk4tv6Io6rIvl2MZyLQ7KtodKG2AlqfdLBaLSEpKUqdR7vxGBuDIgG0wGI67xDmyPUTuyGjrLvKz8iGX+eHDh4snn3yyQ9v+LhVEfve734kLLrjguBtXRc5U2TgiG4T2/8gNvnaFH23F29pDroiireDj4+PDGp1Mh3LvXrvSa+sROVy54YxsDJF7fNppkIlYvhe5kWttWiNXxtHO4UaueCOHI8sp96raOkcuQ0bk/GptPkYu1HIh0x75cTqdYYEjWr1Gbsg6Mj8ix60NC9o2pZ0v2gXfZDKpG0RtG5E3/Iq82ZYcljwSFNmuWyt35E2KorX/E01z5LyLDLDRHnIFqA2l2nYcOV/knqWcHm0fhshxaadd7qlG7tVFayeRw4hsv20tE9G+31r/H+3eY2S71gZg+b92Qxu5UYtWlmjzW5YhNzdXxMTEtNrPQI5LHq2QR420Rwcih68NzLL8kdMfra2eqA61w4rWJlqrg8zMzLAQ079/fwHguKOWketG7bIQWT6z2dyuG17K8rSnv1/kkVz5f+S9W+TzX/ziFwKAeuQp2vop2nPtEUPtTmm0+R9tx6qtthUfH69uDwCI7OzsVudz5JEml8sl3G63GDRokJg1a5aYO3duh7b9XaaPCNByXrhXr16IiYlRz0HJ8+I+nw+zZs1Sz3N5PB7MnDkz7FyUPP8qhyXPlRl/Oo8LtJzPOu+889TzfvHx8er5S7PZrJ6zk9+LjY2FzWaD2WzG/Pnzw65fN2rOB8vnoVAIVqsVV155Jcxms3qfDNnvRZ53lOX0+XzqfRfkvQ9uvPFGAMfOacq+A/LyTIfDAZfLFXZe0ul0qudlDT9duy5vtyu/I69dl+dzgZbzpdpba8vLLvv27Rt2HrdPnz7IysoK698gr2WX/Q/i4uJgMpkwZ84cdbzAsXtUWK1WtR+D2WxWp0H2mzGbzcjIyDiun4T2f3k+1e12IyMjA3Fxcer9A+SlZbKetfcL0N5jAgAuuOCCsLYTeS5cnjOVdaYoChISEtTr9c1mM3Jzc9XxyL4Php+upDFo+huEQiH1EmXZPoCWy7mDwaBaDovFAqvVql7CKi8jlX1R+vfvH9a3adasWUhLSwvrr2AwHH9fEqPRiLS0NFgsFrUvh6xT2fbET+eBXS5XWF8ki8Wi9idISEhQ77OiKAp69eoFg8GAYDAY1t9F2y/J5XLhlltuCbtvRXp6elh/Irk8OBwOdbzmn+6lIculXWZMJhNycnLUYbhcLmRmZqr3MklLS0NiYqJaTz6fD/Hx8Wq9y2Fq24fJZEJMTAxiY2NhNBrhdrvVPg+yT4783+FwhPVnsNlsaj8ou92utkPtvTgAqH065HcNBgOSkpLgdDrV+SjXP4mJiWH9zex2Oy699NKwe1kEAgEIITB27Fj16kKPx4Pk5GR1+XI4HGhsbEQoFFKv3JHrKqHpiyHXY16vF7GxscjJycHkyZORnJwMq9Ua1nfGbDbjhhtuANCy/oiLi8OMGTPUulIUBampqbDb7ep8lG08NTVVHY/hp34esn6MRqO6jpPkJdOyDcpLvwOBgLouMv90HyGr1Qqr1QpFUdT1oLaNAVD7wMh5I9uGnE+mn66GlNMJQL2SSI5LWz7ZdrS09+jIyMiA1+tFdna22l/KaDTihx9+UOszEAiow7XZbGr70vbfSktLg8lkUvuTuVwudRzaflAGTV8Q7XKsXYZkeSP7xch1v1yfFhcXq7dGkNMVSfa/k/fSKS4uxr59+9RbPbRXl7l8FwC++uorAEBRURG2bt2KwYMHY+TIkbj33nvh8Xhwzz33YPXq1XjwwQcxadIkDB06FFu3bsVnn32GrKwsbNy4EVOmTMGSJUvUa+CXLl2KUCgEp9OJCRMmqL+XUFpaiv/4j//AiBEjMGzYMLz11lvqpZ0LFy7E0KFDUVJSgiFDhmDdunWYMGEC7r//fqxatQp33XUXDh06hB49emDPnj0477zzkJKSoi7wR48exbXXXovS0lKsXr0an332Gf7yl7+ow3n55ZfxzTffIBAI4Oabb0bfvn3xyiuvwG63o6GhAXl5efj000+RnZ2NFStWYMiQIaioqECfPn2wdetWeDwe5ObmYsqUKXjsscewadMmDBkyBEIIjB8/HitWrMDjjz+Ojz/+GEeOHMH777+PtLQ0jBkzBj/88AMaGxtx4MABHDp0CBaLBTk5ObjwwgvxyCOPoKSkBLGxsfj2228xZ84cfPrpp+pvM6xduxaKomDNmjXqfSvsdjt2796NtWvXYubMmdi7dy/+/e9/489//jNKS0vxzjvvIC8vD7t27cJNN92EQ4cOwev1YtSoUXjwwQdx5513Yt++ffjrX/+K7OxsZGRk4C9/+QuuvPJKVFVVISkpCUlJSSgvL8fBgwfhdDpRWVmJe+65B9dddx127tyJhx56CAMGDMCrr76KSZMm4dtvv1VvslNQUIBNmzapvzexevVqBAIBvPnmm9i6dSsWLlyIxsZG9V4E+fn5cDgcyMjIQCgUQnx8PPLy8vDVV19h7969SEpKwuTJk7FmzRrEx8ejuroaM2bMwIsvvgiTyYTY2Fi8//77yMjIQFlZGTIzM3HgwAHccccd2LlzJ15++WUMHToU5eXl2LNnD0KhEMaNGwe3242CggKUl5ejuroadXV1SExMxNChQzFkyBDk5+fj6NGjqKioUO+R89BDD8Hr9eLvf/87tm7dinPOOQc1NTVYvXo1PB6Pev+Inj17YurUqXj33XfhdDpx2WWXYcuWLXj00UdhNBpx7rnnYvPmzTCZTKipqYHJZMK4ceMQExODgoICVFdXo7q6GmPHjsUll1yCRYsWYcyYMWp9vv3227DZbOjTpw+8Xi+2b9+OtLQ0bNiwAQMHDsRzzz2HuXPn4s0338TEiRPxhz/8Ac899xw++ugjjBw5EpWVlbBYLOpvpLz00kuIiYlBRUUF8vPz0dzcjMsvvxwFBQVYt24d+vXrhzfeeAMrV67EI488gpkzZyI9PR2PPvoobDYbnnrqKbz33nuorKzEu+++i7/97W+w2+146623sG7dOlRXV6O2thaXXXYZNm/ejAMHDiAuLg7jxo3DhAkT8OGHH6KpqQkGgwE7d+6EyWRCMBjELbfcgkWLFuGee+7BP//5T1RWVuKTTz7B9OnTkZKSArvdjm+++QajRo3CypUrUVlZiR49esBoNGL9+vVoaGjAnDlzcOjQIaxbtw4+nw99+/bF3Llz8eOPP6KwsBAFBQXIz8+Hx+NBc3Mz3G43tmzZgqysLMycORPr1q1Dfn4+ysrK1HD6yCOP4N1338XGjRuxadMm9O3bF16vF4mJiXA6nfj000/x448/Ijc3F/3798eqVavw1VdfqZ1x+/XrB0VRsGvXLgwaNAgNDQ2YO3cu/H4/PB4P7r33XuzevRsNDQ0oKyuD1WrFqlWrcN9992H79u244oorMGrUKKxZswarVq3C7t278eCDD+Kll15CUlKS2tF39uzZiI2Nxf3334+///3vaGhowIIFC/D000/jww8/hNFoxMKFC1FeXo4nnngCR44cwUUXXYTGxkbs2rULeXl5CIVC2L17N7777jtkZGRg5cqVmDVrltoJ9+KLL8arr76KyspKAMDhw4eRkJCAgwcPIhQKYdKkSUhOTsbLL7+MPn364JJLLkFFRQWef/55WK1W9OzZE5MmTcKnn34Kv9+PMWPG4J133sG+fftw9dVXY8mSJbjpppvwyCOPoKGhAW63G5deeinef/999OvXD9999x2MRiOqqqqQkZGBK664AoFAAEePHkV6ejpmz56NF154AV999RXeeecdDB06FNnZ2fjqq6/Qp08fCCFQXl6Om2++GW+//Ta+/vpr2O12/PWvf8WWLVuwatUqJCcnq+Hoxx9/xD333IMnnngCgUBADSybN2+GoijIy8vD999/jwMHDsDj8SA9PR1VVVVIS0tDYWEhtm/frgZA+ZtW33zzDeLi4pCfn4+EhATU1tZi7Nix+PLLLzF+/Hhs2rRJvdxdURTU1tbi6quvxgcffICxY8ciJiYGf/nLX8JuqHkiXSqIEBERUffSpU7NEBERUffCIEJERES6YRAhIiIi3TCIEBERkW4YRIiIiEg3DCJERESkGwYRIiIi0s3/B1grn7LnxoreAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Utilização de dendograma para definir o N° de Clusters\n",
    "#Foi definido  a quantidade de 2 Clusters\n",
    "dendrograma = dendrogram(linkage(X_base, method = 'ward'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Aplicação do Modelo Agrupamento Hierárquico\n",
    "hc_base = AgglomerativeClustering(n_clusters=2, linkage = 'ward')\n",
    "rotulos_hc = hc_base.fit_predict(X_base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "x=%{x}<br>y=%{y}<br>color=%{marker.color}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": [
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0
          ],
          "coloraxis": "coloraxis",
          "symbol": "circle"
         },
         "mode": "markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          -0.18490489291461773,
          0.11844070742238616,
          -0.1291428340291391,
          -0.2228230929567432,
          -0.20051826940255177,
          -0.16706103407126457,
          -0.2272840576675815,
          -0.22505357531216236,
          -0.04215402216779238,
          -0.2072097164688092,
          0.10951877800070957,
          -0.2228230929567432,
          -0.25628032828803043,
          -0.2272840576675815,
          0.058217683826069205,
          0.8611913317769618,
          -0.18490489291461773,
          0.406172931271456,
          -0.1938268223362943,
          -0.0912246339870136,
          -0.12691235167371992,
          -0.21613164589048578,
          -0.21390116353506664,
          -0.15813910464958797,
          -0.2362059870892581,
          -0.16260006936042629,
          -0.2272840576675815,
          -0.18713537527003687,
          0.06044816618148835,
          -0.20051826940255177,
          -0.18490489291461773,
          -0.08899415163159445,
          -0.2072097164688092,
          -0.24735839886635383,
          -0.2406669518000964,
          -0.24958888122177297,
          0.11174926035612871,
          0.9481801436383085,
          -0.22059261060132407,
          -0.21836212824590492,
          -0.18936585762545602,
          -0.23397550473383896,
          -0.16929151642668372,
          1.516953144270191,
          -0.21836212824590492,
          0.16081987217534993,
          -0.12691235167371992,
          -0.23174502237841982,
          -0.20944019882422835,
          -0.04884546923404982,
          -0.19159633998087516,
          -0.16929151642668372,
          -0.20497923411339006,
          -0.07115029278824128,
          -0.13360379873997738,
          -0.01538823390276262,
          -0.2362059870892581,
          -0.2116706811796475,
          0.2031990369283137,
          -0.21390116353506664,
          1.6307077443965672,
          -0.2406669518000964,
          -0.031001610390696644,
          -0.1782134458483603,
          -0.25181936357719215,
          23.638877145317284,
          -0.046614986878630665,
          -0.2072097164688092,
          -0.21836212824590492,
          -0.2406669518000964,
          -0.2228230929567432,
          3.711747782002631,
          -0.2116706811796475,
          -0.1157599398966242,
          -0.22951454002300067,
          0.2165819310608286,
          -0.21836212824590492,
          0.3035707429221753,
          0.3370279782534625,
          -0.20497923411339006,
          -0.24735839886635383,
          -0.2072097164688092,
          -0.1603695870050071,
          -0.18713537527003687,
          -0.1291428340291391,
          -0.18044392820377944,
          -0.19159633998087516,
          -0.20497923411339006,
          -0.1603695870050071,
          -0.10460752811952848,
          -0.2027487517579709,
          -0.24512791651093468,
          -0.1157599398966242,
          0.04260430733813518,
          -0.18713537527003687,
          -0.2362059870892581,
          0.2210428957716669,
          -0.22505357531216236,
          -0.1202209046074625,
          -0.21390116353506664,
          0.08944443680193725,
          0.00245562494059055,
          -0.16483055171584543,
          -0.1603695870050071,
          -0.20497923411339006,
          -0.19605730469171348,
          -0.20944019882422835,
          -0.25181936357719215,
          -0.1447562105170731,
          0.16081987217534993,
          -0.2072097164688092,
          -0.2027487517579709,
          -0.13360379873997738,
          -0.25404984593261126,
          -0.01984919861360091,
          -0.0020053397702477424,
          -0.13360379873997738,
          -0.2272840576675815,
          -0.07338077514366043,
          -0.03992353981237323,
          -0.06445884572198383,
          -0.2362059870892581,
          0.5020836725544793,
          -0.17152199878210286,
          -0.173752481137522,
          -0.053306433944888106,
          -0.06445884572198383,
          -0.21390116353506664,
          -0.2406669518000964,
          -0.17152199878210286,
          -0.18044392820377944,
          -0.2362059870892581,
          -0.20497923411339006,
          -0.2406669518000964,
          0.2589610958137924,
          -0.18267441055919859,
          -0.1492171752279114,
          -0.10237704576410933,
          -0.20944019882422835,
          -0.013157751547343473,
          -0.18267441055919859,
          -0.18044392820377944,
          -0.12468186931830079,
          -0.24289743415551554,
          -0.10014656340869017,
          0.12736263684406274,
          0.9481801436383085,
          -0.21836212824590492,
          -0.19828778704713262,
          -0.03323209274611579,
          -0.24289743415551554,
          -0.1492171752279114,
          -0.17598296349294115,
          -0.12691235167371992,
          0.12736263684406274,
          0.18981614279579884,
          -0.046614986878630665,
          -0.15590862229416882,
          -0.18490489291461773,
          -0.19159633998087516,
          -0.24289743415551554,
          -0.23843646944467725,
          -0.25181936357719215,
          -0.24735839886635383,
          -0.046614986878630665,
          0.47085691957861125,
          -0.19828778704713262,
          -0.23397550473383896,
          -0.20051826940255177,
          -0.23174502237841982,
          -0.05553691630030725,
          -0.24289743415551554,
          -0.21613164589048578,
          -0.19605730469171348,
          -0.20051826940255177,
          -0.2272840576675815,
          -0.2027487517579709,
          -0.16706103407126457,
          -0.2406669518000964,
          -0.19605730469171348,
          -0.24289743415551554,
          -0.2027487517579709,
          0.0626786485369075,
          -0.22059261060132407,
          -0.20944019882422835,
          -0.2362059870892581,
          -0.22059261060132407,
          -0.173752481137522,
          -0.25404984593261126,
          0.09390540151277554,
          -0.24289743415551554,
          -0.23397550473383896,
          -0.03769305745695408,
          -0.20051826940255177,
          -0.09568559869785188,
          -0.2027487517579709,
          -0.22951454002300067,
          -0.18044392820377944,
          -0.12245138696288164,
          0.5310799431749282,
          -0.22505357531216236,
          -0.173752481137522,
          1.443347226541359,
          -0.024310163324439204,
          -0.24958888122177297,
          5.748178172500311,
          -0.14029524580623481,
          -0.01538823390276262,
          -0.17152199878210286,
          -0.25404984593261126,
          0.10505781328987128,
          -0.2072097164688092,
          0.053756719115230917,
          0.8745742259094768,
          -0.18936585762545602,
          -0.23843646944467725,
          -0.23843646944467725,
          -0.2272840576675815,
          -0.23843646944467725,
          -0.2406669518000964,
          -0.23397550473383896,
          -0.16929151642668372,
          -0.21390116353506664,
          -0.16929151642668372,
          -0.2027487517579709,
          -0.18936585762545602,
          -0.18713537527003687,
          -0.2027487517579709,
          -0.2272840576675815,
          -0.12691235167371992,
          -0.16929151642668372,
          -0.21836212824590492,
          0.8188121670239981,
          -0.18713537527003687,
          -0.2406669518000964,
          -0.18044392820377944,
          -0.11129897518578591,
          -0.21836212824590492,
          -0.2027487517579709,
          -0.2406669518000964,
          0.5712286255724728,
          -0.24512791651093468,
          -0.2116706811796475,
          -0.2072097164688092,
          -0.053306433944888106,
          -0.22059261060132407,
          -0.19159633998087516,
          2.507287310076292,
          -0.1938268223362943,
          -0.17598296349294115,
          -0.21390116353506664,
          -0.21836212824590492,
          -0.19605730469171348,
          -0.2027487517579709,
          -0.23397550473383896,
          -0.24289743415551554,
          -0.21613164589048578,
          -0.13806476345081567,
          -0.2228230929567432,
          -0.1291428340291391,
          -0.22059261060132407,
          -0.24958888122177297,
          -0.24958888122177297,
          -0.2116706811796475,
          -0.00869678683650518,
          -0.14029524580623481,
          -0.173752481137522,
          -0.2116706811796475,
          -0.10014656340869017,
          -0.08007222220991786,
          0.6849832256988493,
          -0.010927269191924327,
          -0.0577673986557264,
          -0.2272840576675815,
          -0.20944019882422835,
          -0.24512791651093468,
          -0.24289743415551554,
          -0.17598296349294115,
          -0.1202209046074625,
          -0.1782134458483603,
          0.267883025235469,
          -0.23174502237841982,
          -0.2362059870892581,
          -0.18490489291461773,
          -0.1938268223362943,
          -0.13360379873997738,
          -0.20944019882422835,
          -0.1603695870050071,
          -0.1447562105170731,
          -0.18267441055919859,
          0.5890724844158259,
          -0.21836212824590492,
          -0.2406669518000964,
          -0.21613164589048578,
          -0.2228230929567432,
          -0.21836212824590492,
          0.04483478969355433,
          -0.20051826940255177,
          -0.20944019882422835,
          -0.19159633998087516,
          -0.24289743415551554,
          0.029221413205620304,
          -0.2272840576675815,
          -0.2228230929567432,
          0.9258753200841171,
          -0.18490489291461773,
          -0.17152199878210286,
          -0.24512791651093468,
          -0.22951454002300067,
          -0.21836212824590492,
          -0.19605730469171348,
          -0.24958888122177297,
          -0.22059261060132407,
          -0.07115029278824128,
          3.5266177465028417,
          -0.1782134458483603,
          -0.24512791651093468,
          0.1251321544886436,
          -0.07561125749907957,
          -0.17152199878210286,
          -0.2228230929567432,
          -0.06668932807740298,
          -0.173752481137522,
          -0.23174502237841982,
          -0.20944019882422835,
          0.3972510018497794,
          -0.1938268223362943,
          -0.18713537527003687,
          -0.21390116353506664,
          -0.22951454002300067,
          -0.20944019882422835,
          -0.1202209046074625,
          -0.18936585762545602,
          0.07383106031400323,
          -0.2072097164688092,
          -0.21390116353506664,
          -0.13806476345081567,
          1.472343497161808,
          -0.2406669518000964,
          -0.24289743415551554,
          -0.19159633998087516,
          0.2611915781692115,
          -0.19605730469171348,
          -0.19828778704713262,
          -0.2272840576675815,
          -0.10906849283036676,
          -0.22059261060132407,
          -0.23174502237841982,
          -0.21836212824590492,
          -0.2027487517579709,
          -0.23174502237841982,
          -0.10460752811952848,
          -0.18044392820377944,
          -0.18713537527003687,
          -0.00869678683650518,
          -0.028771128035277496,
          2.59204563958222,
          -0.2072097164688092,
          -0.1447562105170731,
          -0.1492171752279114,
          1.166767414469385,
          -0.1603695870050071,
          0.2857268840788221,
          -0.2362059870892581,
          -0.09791608105327103,
          -0.0912246339870136,
          -0.14029524580623481,
          0.5801505549941494,
          -0.02207968096902006,
          -0.2272840576675815,
          0.10282733093445214,
          -0.24512791651093468,
          -0.20051826940255177,
          -0.1603695870050071,
          -0.15367813993874968,
          -0.10683801047494762,
          -0.017618716258181767,
          -0.1492171752279114,
          -0.11799042225204334,
          -0.14698669287249225,
          -0.10460752811952848,
          -0.0577673986557264,
          0.8232731317348363,
          -0.20944019882422835,
          -0.18490489291461773,
          -0.20497923411339006,
          0.6113773079700174,
          -0.20051826940255177,
          0.3035707429221753,
          -0.24735839886635383,
          -0.046614986878630665,
          -0.09568559869785188,
          -0.173752481137522,
          -0.082302704565337,
          -0.2272840576675815,
          0.16528083688618822,
          -0.21836212824590492,
          0.6158382726808558,
          0.41286437833771344,
          -0.22951454002300067,
          -0.21613164589048578,
          -0.17598296349294115,
          -0.2406669518000964,
          -0.1157599398966242,
          -0.16706103407126457,
          -0.18267441055919859,
          0.03145189556103945,
          -0.22951454002300067,
          -0.173752481137522,
          -0.24958888122177297,
          0.6693698492109152,
          0.19204662515121798,
          -0.21613164589048578,
          -0.18936585762545602,
          -0.2362059870892581,
          -0.20497923411339006,
          -0.2406669518000964,
          0.16305035453076908,
          6.916950926739944,
          -0.20051826940255177,
          -0.20051826940255177,
          -0.2272840576675815,
          -0.12245138696288164,
          -0.21836212824590492,
          0.4953922254882218,
          -0.21836212824590492,
          -0.1938268223362943,
          -0.082302704565337,
          -0.16260006936042629,
          0.3325670135426242,
          -0.03992353981237323,
          -0.08453318692075615,
          -0.2362059870892581,
          -0.20497923411339006,
          -0.18490489291461773,
          0.7585891434276811,
          -0.22059261060132407,
          -0.23397550473383896,
          0.314723154699271,
          -0.24289743415551554,
          -0.09791608105327103,
          -0.15813910464958797,
          -0.1938268223362943,
          -0.23174502237841982,
          -0.2027487517579709,
          -0.18936585762545602,
          -0.03769305745695408,
          -0.19828778704713262,
          0.14074553097657763,
          -0.19828778704713262,
          -0.01984919861360091,
          -0.23397550473383896,
          -0.03323209274611579,
          0.7496672140060046,
          -0.024310163324439204,
          0.047065272048973476,
          -0.11352945754120505,
          -0.17598296349294115,
          -0.18267441055919859,
          0.7050575668976216,
          -0.21390116353506664,
          -0.05107595158946896,
          -0.24512791651093468,
          -0.2228230929567432,
          -0.24512791651093468,
          -0.14698669287249225,
          -0.15813910464958797,
          -0.18936585762545602,
          -0.2272840576675815,
          0.2411172369704392,
          -0.2272840576675815,
          -0.0867636692761753,
          -0.1492171752279114,
          -0.04884546923404982,
          -0.13583428109539653,
          0.2031990369283137,
          -0.22505357531216236,
          -0.2406669518000964,
          -0.09791608105327103,
          -0.22059261060132407,
          -0.18490489291461773,
          -0.23397550473383896,
          -0.082302704565337,
          -0.19828778704713262,
          -0.1603695870050071,
          -0.17152199878210286,
          -0.12691235167371992,
          -0.25181936357719215,
          -0.1938268223362943,
          -0.16260006936042629,
          -0.23174502237841982,
          -0.1603695870050071,
          -0.1447562105170731,
          -0.07115029278824128,
          -0.06445884572198383,
          -0.17152199878210286,
          0.27234398994630726,
          -0.24958888122177297,
          -0.04438450452321152,
          -0.1157599398966242,
          4.590557830037775,
          -0.23174502237841982,
          -0.0912246339870136,
          -0.23397550473383896,
          -0.24289743415551554,
          -0.2027487517579709,
          0.8478084376444469,
          -0.10237704576410933,
          -0.05107595158946896,
          -0.25181936357719215,
          0.10728829564529042,
          -0.16483055171584543,
          -0.21836212824590492,
          -0.24958888122177297,
          -0.18713537527003687,
          0.04260430733813518,
          -0.18044392820377944,
          -0.2362059870892581,
          -0.053306433944888106,
          0.8522694023552853,
          -0.23174502237841982,
          -0.11129897518578591,
          -0.19828778704713262,
          -0.19159633998087516,
          0.9794068966141766,
          -0.20944019882422835,
          0.07160057795858409,
          -0.18267441055919859,
          -0.24289743415551554,
          -0.24958888122177297,
          -0.18267441055919859,
          -0.22505357531216236,
          0.09836636622361385,
          -0.24958888122177297,
          -0.24512791651093468,
          -0.21613164589048578,
          -0.19828778704713262,
          0.2411172369704392,
          0.00022514258517140383,
          0.7206709433855556,
          -0.1938268223362943,
          -0.23397550473383896,
          -0.06222836336656469,
          -0.21390116353506664,
          -0.22505357531216236,
          -0.19605730469171348,
          -0.24512791651093468,
          -0.2362059870892581,
          -0.2362059870892581,
          -0.035462575101534936,
          0.5979944138375026,
          0.7675110728493577,
          0.047065272048973476,
          -0.11352945754120505,
          0.18981614279579884,
          -0.18044392820377944,
          -0.23397550473383896,
          -0.25404984593261126,
          -0.25628032828803043,
          1.2559867086861507,
          -0.2362059870892581,
          2.0098897448178223,
          0.6403735785904664,
          -0.18713537527003687,
          -0.20497923411339006,
          -0.2228230929567432,
          -0.22059261060132407,
          -0.15590862229416882,
          -0.03323209274611579,
          -0.24735839886635383,
          -0.23397550473383896,
          -0.22951454002300067,
          -0.21613164589048578,
          -0.2072097164688092,
          -0.1447562105170731,
          -0.22505357531216236,
          0.3727156959401688,
          -0.25404984593261126,
          -0.22505357531216236,
          -0.21390116353506664,
          -0.1492171752279114,
          -0.06222836336656469,
          -0.03323209274611579,
          -0.15144765758333054,
          -0.2272840576675815,
          -0.21836212824590492,
          -0.173752481137522,
          -0.20944019882422835,
          -0.21613164589048578,
          -0.2272840576675815,
          -0.18490489291461773,
          -0.19605730469171348,
          -0.22505357531216236,
          -0.22059261060132407,
          -0.2027487517579709,
          -0.1603695870050071,
          -0.22951454002300067,
          -0.20051826940255177,
          -0.17598296349294115,
          0.42847775482564743,
          -0.12691235167371992,
          0.033682377916458596,
          0.13182360155490103,
          -0.046614986878630665,
          -0.12691235167371992,
          1.9295923800227328,
          -0.21390116353506664,
          0.15635890746451164,
          0.47531788428944954,
          -0.20497923411339006,
          -0.17598296349294115,
          0.00022514258517140383,
          -0.18044392820377944,
          -0.15367813993874968,
          1.6463211208845012,
          -0.2027487517579709,
          -0.2027487517579709,
          0.06490913089232665,
          -0.1782134458483603,
          -0.2406669518000964,
          -0.24735839886635383,
          -0.22505357531216236,
          -0.2116706811796475,
          -0.1492171752279114,
          -0.017618716258181767,
          -0.22059261060132407,
          -0.24512791651093468,
          -0.06668932807740298,
          -0.046614986878630665,
          -0.18713537527003687,
          -0.18713537527003687,
          -0.1782134458483603,
          -0.07561125749907957,
          -0.21836212824590492,
          -0.1782134458483603,
          -0.21613164589048578,
          3.4708556876173633,
          -0.23174502237841982,
          -0.09568559869785188,
          -0.08453318692075615,
          -0.24289743415551554,
          -0.23174502237841982,
          -0.22059261060132407,
          -0.19605730469171348,
          -0.12691235167371992,
          -0.06891981043282214,
          -0.13137331638455824,
          -0.13137331638455824,
          -0.08899415163159445,
          -0.2228230929567432,
          -0.15813910464958797,
          -0.22505357531216236,
          -0.22059261060132407,
          -0.1447562105170731,
          -0.22951454002300067,
          -0.23843646944467725,
          -0.21836212824590492,
          -0.17598296349294115,
          1.3162097322824677,
          -0.10460752811952848,
          0.10951877800070957,
          0.018069001428524575,
          -0.22059261060132407,
          0.16528083688618822,
          -0.21390116353506664,
          -0.2228230929567432,
          -0.22951454002300067,
          -0.18267441055919859,
          -0.22951454002300067,
          -0.23397550473383896,
          -0.21390116353506664,
          -0.24512791651093468,
          -0.24289743415551554,
          0.022529966139362867,
          2.395763192305335,
          -0.13806476345081567,
          -0.19159633998087516,
          -0.22951454002300067,
          -0.10683801047494762,
          -0.20944019882422835,
          -0.25404984593261126,
          -0.1492171752279114,
          -0.2362059870892581,
          -0.22059261060132407,
          0.17420276630786483,
          -0.22505357531216236,
          -0.07561125749907957,
          -0.21390116353506664,
          -0.21390116353506664,
          -0.21390116353506664,
          -0.22059261060132407,
          -0.2406669518000964,
          -0.2228230929567432,
          -0.18267441055919859,
          0.19873807221747541,
          -0.2072097164688092,
          -0.23397550473383896,
          -0.082302704565337,
          -0.2228230929567432,
          -0.20051826940255177,
          -0.21613164589048578,
          -0.15367813993874968,
          0.03814334262729689,
          -0.23174502237841982,
          -0.24958888122177297,
          -0.22951454002300067,
          0.3013402605667561,
          -0.1492171752279114,
          -0.1938268223362943,
          -0.21390116353506664,
          -0.10014656340869017,
          -0.24512791651093468,
          0.330336531187205,
          -0.2116706811796475,
          -0.18936585762545602,
          -0.20497923411339006,
          -0.18713537527003687,
          -0.24512791651093468,
          -0.21613164589048578,
          -0.17598296349294115,
          -0.1202209046074625,
          -0.13806476345081567,
          -0.21390116353506664,
          -0.03992353981237323,
          0.3481803900305582,
          -0.18936585762545602,
          -0.22505357531216236,
          -0.25181936357719215,
          -0.1447562105170731,
          -0.18044392820377944,
          0.7005966021867833,
          -0.18713537527003687,
          -0.22059261060132407,
          -0.16260006936042629,
          -0.22951454002300067,
          -0.15590862229416882,
          -0.10014656340869017,
          -0.024310163324439204,
          0.2321953075487626,
          -0.19159633998087516,
          0.06044816618148835,
          -0.2406669518000964,
          -0.19828778704713262,
          -0.2272840576675815,
          -0.24289743415551554,
          -0.2228230929567432,
          -0.20051826940255177,
          -0.2362059870892581,
          0.1697418015970265,
          -0.21836212824590492,
          -0.2072097164688092,
          -0.23174502237841982,
          -0.18044392820377944,
          -0.16929151642668372,
          -0.2072097164688092,
          -0.24735839886635383,
          -0.18267441055919859,
          -0.1938268223362943,
          -0.24289743415551554,
          -0.1938268223362943,
          -0.18044392820377944,
          -0.25404984593261126,
          0.5600762137953771,
          -0.20051826940255177,
          -0.18713537527003687,
          -0.16706103407126457,
          -0.18267441055919859,
          -0.22951454002300067,
          -0.20497923411339006,
          0.10282733093445214,
          -0.25181936357719215,
          -0.16483055171584543,
          -0.21836212824590492,
          -0.20497923411339006,
          -0.25181936357719215,
          -0.21613164589048578,
          -0.24289743415551554,
          -0.20944019882422835,
          -0.1938268223362943,
          -0.22059261060132407,
          -0.24735839886635383,
          -0.2228230929567432,
          -0.14252572816165396,
          -0.19828778704713262,
          -0.1782134458483603,
          -0.2228230929567432,
          -0.23843646944467725,
          -0.01984919861360091,
          3.1652796049249403,
          -0.15144765758333054,
          -0.23843646944467725,
          -0.20051826940255177,
          -0.22059261060132407,
          -0.10906849283036676,
          -0.18936585762545602,
          -0.21836212824590492,
          -0.23174502237841982,
          0.2121209663499903,
          -0.2272840576675815,
          -0.18267441055919859,
          -0.25404984593261126,
          -0.2272840576675815,
          -0.12691235167371992,
          -0.11799042225204334,
          1.3429755205474974,
          0.44186064895816235,
          -0.15590862229416882,
          -0.1603695870050071,
          -0.09345511634243274,
          -0.25628032828803043,
          -0.20497923411339006,
          -0.18267441055919859,
          1.1779198262464805,
          0.21881241341624774,
          0.4262472724702283,
          -0.18267441055919859,
          0.029221413205620304,
          -0.13583428109539653,
          -0.22951454002300067,
          0.6448345433013046,
          -0.18713537527003687,
          -0.13360379873997738,
          3.680521029026763,
          5.600966337042648,
          -0.23843646944467725,
          0.6626784021446578,
          -0.20497923411339006,
          -0.2362059870892581,
          -0.10906849283036676,
          -0.19159633998087516,
          -0.20497923411339006,
          -0.23397550473383896,
          -0.24735839886635383,
          1.673086909149531,
          -0.2072097164688092,
          0.12736263684406274,
          -0.07338077514366043,
          -0.09791608105327103,
          -0.1157599398966242,
          -0.22505357531216236,
          -0.23174502237841982,
          -0.23397550473383896,
          1.3697413088125272,
          0.4597045078015155,
          -0.22505357531216236,
          -0.19605730469171348,
          -0.20944019882422835,
          -0.15813910464958797,
          -0.25181936357719215,
          0.22773434283792432,
          -0.21836212824590492,
          -0.23397550473383896
         ],
         "xaxis": "x",
         "y": [
          -0.19732360523316692,
          -0.1802747278288778,
          -0.1258201044778648,
          -0.09792483305330968,
          -0.1850776765006085,
          -0.18965797192265632,
          -0.20635696564887232,
          -0.16026774296451615,
          -0.14840350551712836,
          -0.1844415243586574,
          -0.16039497339290634,
          -0.18946712628007098,
          -0.16577045899239304,
          -0.058483400252342305,
          -0.028488826759348582,
          0.07539481802126381,
          -0.051453919083782815,
          -0.16402104060202752,
          -0.08847797374533602,
          -0.09363080609513984,
          -0.09770217980362679,
          -0.0421979054183945,
          -0.04458347595071108,
          -0.15311103136756643,
          -0.174549358551318,
          -0.1400699124575691,
          -0.18460056239414518,
          -0.11392405942337948,
          0.0547834886220486,
          -0.18224679946892616,
          -0.08742832271111674,
          -0.15336549222434684,
          -0.18272391357538947,
          -0.1616036624626134,
          -0.1829783744321699,
          -0.1588364006451262,
          -0.17117775219897724,
          -0.08268898925358116,
          -0.1162778223485985,
          -0.13571227028520422,
          -0.1283329054385716,
          -0.1718457119480259,
          -0.10078751769208956,
          0.0852233686144081,
          -0.040766563099004546,
          0.03840257096680815,
          -0.06401792388731677,
          -0.16631118831305144,
          -0.15829567132446776,
          -0.20956953396572534,
          0.06305346646741275,
          -0.19617853137765495,
          -0.2084562677173109,
          -0.14213740691891016,
          -0.17712577472621993,
          -0.16853772080988025,
          -0.18879916653102236,
          0.1799782301580224,
          0.06785641513914342,
          -0.1403561809214471,
          0.3050775488727035,
          -0.17299078580353788,
          0.5582661013692358,
          0.0763172386270929,
          -0.19372934563114327,
          22.007757755212086,
          0.007294731225400026,
          -0.1449682839505925,
          -0.16672468720531966,
          -0.19261607938272887,
          -0.1868907101051691,
          3.5875589861261137,
          -0.18227860707602372,
          0.0974056821327714,
          -0.2034624734029949,
          -0.0727014006249491,
          -0.1861909427490229,
          -0.1723228260544892,
          -0.08437479242975152,
          -0.1676153002040512,
          -0.15167968904817647,
          -0.12839652065276672,
          -0.1419147536692273,
          -0.04493335962878417,
          -0.14258271341827594,
          -0.14162848520534932,
          -0.21046014696445686,
          -0.21173245124835902,
          -0.03612265246276163,
          -0.07880846118767951,
          -0.20823361446762806,
          -0.1593135147515895,
          -0.2009496724422881,
          -0.14719481644742133,
          -0.09674795159070015,
          -0.18262849075409682,
          -0.026389524690910007,
          -0.12251211333971915,
          -0.20177667022682452,
          -0.1403879885285447,
          -0.2053391222217506,
          -0.2094423035373351,
          -0.19958194533709328,
          -0.12139884709130477,
          -0.02858424958064125,
          -0.09573010816357841,
          -0.17830265618882943,
          -0.18370994939541366,
          0.013115523324252462,
          0.0073583464395951224,
          -0.06150512292660997,
          -0.06338177174536569,
          -0.15641902250571205,
          -0.17947953765143893,
          -0.06296827285309747,
          0.1641698494305379,
          -0.06099620121304911,
          -0.1989457931951422,
          -0.0689481029874377,
          -0.10603577286318602,
          -0.20428947118753132,
          -0.1966238378770207,
          0.0948292659578695,
          -0.08857339656662869,
          -0.1986595247312642,
          -0.16188993092649137,
          -0.11207921821172133,
          -0.14115137109888598,
          -0.13421731275161913,
          -0.1799884593649998,
          -0.15816844089607754,
          -0.13087751400637593,
          -0.09712964287587082,
          -0.09506214841452977,
          -0.08940039435116512,
          -0.14993027065781098,
          0.13579746389951944,
          -0.14487286112929984,
          -0.16771072302534384,
          -0.17378597598097673,
          -0.15670529096959004,
          -0.06853460409516948,
          -0.16993725552217262,
          -0.16163547006971096,
          -0.06452684560087764,
          0.06120862525575461,
          0.0008377869845964963,
          -0.2013631713345563,
          -0.10018317315723603,
          -0.20149040176294652,
          -0.1880039763535835,
          -0.14741746969710418,
          -0.12184415359067051,
          -0.08380225550199555,
          -0.0561296373271233,
          -0.1494213489442501,
          -0.15743686593283382,
          -0.07782242536765535,
          -0.20543454504304323,
          -0.20228559194038537,
          -0.08892328024470178,
          -0.17012810116475796,
          -0.17531274112165932,
          -0.19649660744863048,
          -0.13800241799622812,
          0.20860507654582133,
          -0.14744927730420174,
          -0.1501211163003963,
          -0.16666107199112454,
          -0.16758349259695363,
          0.44655778524262524,
          -0.20782011557535987,
          -0.12391164805201153,
          -0.11926773741576863,
          -0.15597371600634627,
          -0.12912809561601044,
          -0.180401958257268,
          -0.20788373078955497,
          -0.18475960042963296,
          -0.10431816207991809,
          -0.15489225736502946,
          -0.18832205242455902,
          -0.06786664434612083,
          -0.00816376582401137,
          -0.14547720566415337,
          -0.21150979799867614,
          -0.18762228506841283,
          -0.1263926414056208,
          -0.17849350183141477,
          -0.15260210965400553,
          -0.13370839103805826,
          -0.1647526155652713,
          -0.17712577472621993,
          -0.1511707673346156,
          -0.11207921821172133,
          -0.027948097438690176,
          -0.20568900589982372,
          0.3319867844772345,
          -0.0481141203385396,
          0.3332908963682342,
          -0.1820877614334384,
          -0.18552298299997427,
          0.9107898108314305,
          -0.17534454872875688,
          -0.16418007863751533,
          9.936866284511517,
          -0.12305284266037758,
          -0.18370994939541366,
          -0.19083485338526585,
          -0.1632894656387838,
          -0.19032593167170495,
          -0.15988605167934547,
          -0.19223438809755822,
          1.2857378832974007,
          -0.18797216874648592,
          -0.15317464658176153,
          -0.14131040913437373,
          -0.20565719829272613,
          -0.11007533896457543,
          -0.0270256768328611,
          -0.17543997155004953,
          -0.1921707728833631,
          -0.20263547561845846,
          -0.15823205611027266,
          -0.200599788764215,
          -0.10826230536001483,
          -0.1139876746375746,
          -0.1165640908124765,
          -0.16023593535741856,
          -0.12642444901271835,
          -0.16408465581622264,
          -0.17871615508109764,
          -0.14242367538278816,
          -0.16392561778073486,
          -0.15804121046768732,
          -0.200599788764215,
          0.10478504697940398,
          -0.14643143387708,
          -0.15543298668568786,
          -0.1530474161533713,
          -0.180974495185024,
          -0.1515842662268838,
          -0.15578287036376098,
          -0.10504973704316183,
          -0.024989989978617625,
          -0.18113353322051176,
          -0.06427238474409719,
          0.8180706361420597,
          -0.04929100180114913,
          -0.1341855051445216,
          -0.16325765803168624,
          -0.20559358307853104,
          0.04209225339012444,
          -0.1809108799708289,
          -0.13469442685808244,
          -0.1335493530025705,
          0.05599217769175569,
          0.034999157007369816,
          -0.17811181054624411,
          -0.18380537221670634,
          -0.1513616129772009,
          -0.18959435670846123,
          -0.2013631713345563,
          -0.10562227397091781,
          -0.052280916868319226,
          0.011652373397764938,
          -0.1867316720696813,
          -0.02705748443995865,
          -0.11729566577572025,
          -0.03974871967188283,
          0.079307153694263,
          0.021385501169616565,
          -0.1681560295247096,
          -0.14029256570725201,
          -0.06996594641455943,
          -0.1670427632762952,
          -0.2061025047920919,
          -0.1935066923814604,
          -0.10893026510906346,
          -0.10126463179855287,
          0.4755663229155946,
          -0.1246432230152553,
          -0.15858193978834575,
          -0.17432670530163513,
          -0.18536394496448647,
          -0.19137558270592425,
          -0.16157185485551587,
          -0.19194811963368022,
          -0.12709240876176697,
          -0.0882235128885556,
          -0.07543685483533877,
          -0.21310017835355385,
          -0.16942833380861178,
          -0.17044617723573352,
          -0.1692056805589289,
          -0.21087364585672505,
          -0.19277511741821665,
          -0.19764168130414247,
          -0.1913437750988267,
          -0.16424369385171042,
          -0.15556021711407808,
          0.01117525929130165,
          -0.1768713138694395,
          -0.200599788764215,
          -0.14318705795312947,
          -0.1453817828428607,
          -0.19248884895433865,
          -0.21115991432060305,
          -0.15613275404183408,
          -0.13991087442208136,
          -0.13517154096454578,
          -0.13956099074400827,
          -0.1405152189569349,
          -0.17836627140302455,
          0.1292450968374233,
          -0.20858349814570115,
          -0.19703733676928892,
          -0.1245796078010602,
          -0.1730862086248305,
          -0.13097293682766858,
          -0.1788115779023903,
          -0.01338021338801028,
          -0.12709240876176697,
          -0.10699000107611263,
          -0.20991941764379843,
          0.34544140227949993,
          -0.07674096672633848,
          -0.14646324148417755,
          -0.13571227028520422,
          -0.2110326838922128,
          -0.09324911480996917,
          -0.10775338364645394,
          -0.17222740323319655,
          -0.19382476845243593,
          -0.19710095198348404,
          -0.17423128248034248,
          -0.15800940286058976,
          7.266172362172467,
          -0.06328634892407302,
          -0.16392561778073486,
          -0.16567503617110035,
          1.0944787418198068,
          -0.062204890282756164,
          -0.18539575257158405,
          -0.008322803859499133,
          -0.11230187146140422,
          -0.1070218086832102,
          -0.06474949885056053,
          -0.19986821380097125,
          -0.19633756941314273,
          -0.19312500109628974,
          -0.1358395007135944,
          -0.13895664620915474,
          -0.1754717791571471,
          0.2613420891135663,
          -0.08399310114458088,
          4.173168840399186,
          -0.19420645973760658,
          -0.12254392094681672,
          -0.15587829318505364,
          0.067601954282363,
          -0.06230031310404883,
          0.0915530824268214,
          -0.21240041099740767,
          -0.17531274112165932,
          -0.11268356274657489,
          -0.15075726844234738,
          0.7841319193689692,
          -0.1816742625411702,
          -0.09585733859196863,
          -0.17279994016095254,
          -0.2020629386907025,
          -0.07941280572253306,
          -0.1110613747845996,
          0.11808062674618171,
          -0.14757650773259193,
          -0.1302731694715224,
          -0.1957968400924843,
          -0.15581467797085852,
          0.007676422510570648,
          -0.08023980350706947,
          0.07870280915940948,
          0.40667104594229203,
          -0.15683252139798026,
          -0.19347488477436284,
          -0.17744385079719546,
          -0.09483949516484688,
          -0.13008232382893706,
          -0.1332630845386925,
          -0.18390079503799897,
          -0.16176270049810118,
          -0.19477899666536255,
          -0.16173089289100362,
          0.013560829823618224,
          -0.15991785928644306,
          -0.17451755094422047,
          -0.19353849998855793,
          -0.11688216688345206,
          -0.18886278174521745,
          -0.13666649849813084,
          -0.15107534451332294,
          -0.1365392680697406,
          -0.15177511186946913,
          -0.14786277619646995,
          -0.20371693425977533,
          -0.17792096490365877,
          -0.198246025838996,
          -0.11373321378079417,
          -0.19341126956016771,
          -0.16093570271356478,
          2.352246949278397,
          -0.2061025047920919,
          -0.2044803168301166,
          -0.1600132821077357,
          -0.18685890249807155,
          -0.1449046687363974,
          -0.1986595247312642,
          0.7870582192219442,
          0.9780310922356602,
          -0.19220258049046066,
          -0.059978357785927375,
          -0.20266728322555605,
          -0.16720180131178297,
          -0.20565719829272613,
          0.1517012674482966,
          -0.2024128223687756,
          -0.13475804207227757,
          -0.14846712073132345,
          -0.1969101063408987,
          0.8219193566008637,
          -0.06653072484802355,
          0.08471444690084724,
          -0.13456719642969223,
          -0.1274104848327425,
          -0.21290933271096854,
          0.370060490173007,
          -0.1910575066349487,
          -0.1706688304854164,
          -0.047477968196588526,
          -0.1824376451115115,
          -0.15543298668568786,
          -0.19897760080223972,
          -0.11198379539042867,
          -0.06783483673902328,
          -0.17200474998351367,
          -0.1844415243586574,
          -0.1714322130557577,
          -0.15788217243219957,
          -0.015415900242253758,
          -0.1864772112129009,
          -0.14344151880990988,
          -0.15288837811788353,
          -0.189180857816193,
          0.24518382470800879,
          0.13843749528861649,
          -0.09677975919779772,
          -0.11109318239169716,
          -0.13081389879218083,
          0.003382395552400833,
          -0.0564795210051964,
          -0.1353623866071311,
          1.2134391923646597,
          -0.08068511000643523,
          -0.1932204239175824,
          -0.12562925883527948,
          -0.1778891572965612,
          0.01581916992754456,
          -0.09258115506092054,
          -0.17502647265778132,
          0.17940569323026645,
          -0.16389381017363733,
          0.06597976632038775,
          -0.20540273743594573,
          0.001060440234279355,
          -0.13889303099495964,
          0.25399453187403126,
          -0.17346789991000117,
          -0.2068658873624332,
          -0.17531274112165932,
          -0.1616036624626134,
          -0.12524756755010882,
          -0.16166727767680852,
          -0.17712577472621993,
          -0.16583407420658816,
          -0.15994966689354057,
          -0.12540660558559658,
          -0.08475648371492218,
          -0.19891398558804463,
          -0.11487828763630611,
          -0.10151909265533329,
          -0.20937868832314,
          -0.09747952655394392,
          -0.1902305088504123,
          -0.1952561107718259,
          -0.15540117907859033,
          -0.12146246230549987,
          -0.1070218086832102,
          -0.18383717982380388,
          -0.10823049775291725,
          0.042792020746270636,
          0.1470573568120537,
          -0.200599788764215,
          -0.20613431239918947,
          -0.20149040176294652,
          -0.19910483123062994,
          -0.0962390298771393,
          0.17345767070302376,
          -0.14970761740812807,
          -0.05011799958568553,
          -0.1864772112129009,
          -0.14655866430547024,
          -0.062332120711146376,
          -0.1960831085563623,
          -0.14089691024210554,
          -0.14379140248798297,
          -0.08335694900262978,
          -0.18959435670846123,
          -0.15167968904817647,
          -0.06672157049060888,
          0.6075996999775427,
          -0.18899001217360767,
          -0.1781754257604392,
          -0.04359744013068688,
          -0.08637867167689744,
          0.9685842329276867,
          -0.11077510632072161,
          -0.16958737184409953,
          -0.17668046822685415,
          -0.16643841874144166,
          -0.18526852214319384,
          -0.21179606646255414,
          -0.07120644309136404,
          -0.0807805328277279,
          -0.16195354614068652,
          -0.18173787775536532,
          -0.044360822701028195,
          0.0003606728781331635,
          0.2560938339424699,
          -0.02871148000903146,
          -0.028934133258714342,
          -0.11560986259954986,
          -0.18393260264509656,
          -0.11869520048801263,
          -0.1989457931951422,
          -0.19888217798094707,
          -0.15858193978834575,
          -0.13972002877949602,
          -0.16262150588973515,
          -0.17369055315968407,
          -0.13997448963627648,
          0.34054303078647663,
          -0.18364633418121853,
          -0.05711567314714747,
          -0.023654070480520338,
          -0.09741591133974879,
          -0.04194344456161407,
          -0.15718240507605338,
          -0.19115292945624138,
          -0.16592949702788082,
          0.04613181949151383,
          -0.18533213735738893,
          -0.061218854462731995,
          -0.12057184930676834,
          -0.0561296373271233,
          -0.11732747338281779,
          -0.15667348336249248,
          -0.17738023558300034,
          -0.16430730906590552,
          -0.17127317502026992,
          -0.08609240321301945,
          -0.15915447671610172,
          -0.18237402989731638,
          -0.09468045712935913,
          -0.06296827285309747,
          -0.19818241062480088,
          -0.19026231645750985,
          0.4597897497952077,
          -0.1690148349163436,
          -0.10263235890374771,
          -0.15517852582890743,
          -0.06344538695956078,
          -0.19770529651833757,
          0.0313412821911511,
          -0.1289054423663276,
          -0.18418706350187697,
          -0.17369055315968407,
          0.028128713874298095,
          -0.0689481029874377,
          -0.17461297376551313,
          -0.1584865169670531,
          -0.15431972043727346,
          0.004877353085985882,
          -0.20161763219133674,
          -0.14395044052347078,
          -0.16786976106083162,
          -0.13781157235364278,
          -0.12559745122818192,
          0.012479371182301366,
          -0.03520023185693254,
          0.10189055473352655,
          0.03595338522029644,
          -0.0709519822345836,
          -0.09286742352479853,
          -0.10832592057420992,
          -0.11004353135747785,
          0.7322537121928581,
          -0.18154703211277998,
          -0.18126076364890198,
          0.17049956324295124,
          -0.2001862898719468,
          -0.19140739031302179,
          -0.15190234229785934,
          -0.10193259154760151,
          -0.15043919237137185,
          0.6719782967429927,
          -0.14057883417113,
          -0.1109977595704045,
          -0.2013631713345563,
          -0.09592095380616375,
          -0.20177667022682452,
          -0.15482864215083433,
          -0.20413043315204352,
          -0.1683468751672949,
          -0.20292174408233646,
          0.07370901484509343,
          -0.20180847783392206,
          -0.18329645050314544,
          0.49690922727805364,
          -0.12238488291132894,
          -0.07053848334231541,
          -0.05558890800646487,
          -0.16220800699746696,
          -0.16933291098731912,
          -0.14096052545630064,
          -0.20727938625470144,
          -0.1987867551596544,
          6.54315364523796,
          0.0435235957095144,
          -0.07705904279731403,
          -0.11414671267306235,
          -0.18921266542329054,
          -0.14948496415844523,
          -0.14760831533968952,
          -0.14347332641700747,
          -0.0905136605995795,
          -0.18577744385675468,
          -0.19112112184914382,
          -0.09522118645001755,
          -0.00018005644252526532,
          -0.17299078580353788,
          -0.1792250767946585,
          -0.18072003432824355,
          -0.12820567501018137,
          0.159239670330417,
          -0.19353849998855793,
          -0.08450202285814173,
          -0.20371693425977533,
          -0.18603190471353512,
          1.1405679645041629,
          -0.1707324456996115,
          -0.19236161852594844,
          -0.15132980537010338,
          -0.19926386926611772,
          -0.07839496229541132,
          0.030514284406614668,
          -0.19640118462733785,
          -0.1511707673346156,
          7.0150194965301775,
          -0.19888217798094707,
          -0.1625260830684425,
          -0.12260753616101182,
          -0.21612190102782153,
          -0.1516478814410789,
          -0.1508208836565425,
          2.73899564397756,
          -0.016052052384204853,
          -0.1641164634233202,
          -0.1856502134283645,
          -0.1547968345437368,
          -0.16647022634853922,
          -0.18402802546638922,
          0.09613337784886922,
          -0.1875904774613153,
          -0.18176968536246285,
          0.14619855142041974,
          -0.1821513766476335,
          -0.1977371041254351,
          -0.09751133416104146,
          -0.1512343825488107,
          -0.20215836151199515,
          -0.15473321932954165,
          -0.18650901881999846,
          -0.09372622891643251,
          -0.13768434192525256,
          0.29620322649248587,
          -0.19500164991504543,
          -0.1638301949594422,
          -0.10749892278967352,
          -0.16061762664258925,
          -0.11665951363376917,
          -0.1792250767946585,
          -0.15476502693663924,
          -0.14283717427505635,
          -0.1935066923814604,
          -0.16637480352724657,
          -0.1999000214080688,
          -0.008354611466596704,
          -0.03351442868076218,
          -0.10463623815089364,
          0.074027090916069,
          -0.14560443609254362,
          -0.15734144311154113,
          -0.16923748816602643,
          -0.157850364825102,
          -0.20381235708106799,
          -0.1272196391901572,
          -0.04372467055907712,
          -0.1509481140849327,
          -0.1843779091444623,
          -0.2112553371418957,
          -0.07909472965155752,
          -0.11637324516989117,
          -0.18930808824458323,
          -0.07247874737526622,
          -0.06971148555777898,
          -0.17553539437134222,
          -0.20460754725850686,
          -0.14305982752473925,
          -0.17884338550948786,
          -0.1589000158593213,
          -0.02231815098242305,
          0.030005362693053813,
          -0.09703422005457815,
          -0.03275104611042087,
          -0.18959435670846123,
          -0.1804655734714631,
          -0.1180908559531591,
          -0.020377886949472238,
          1.3025322998449096,
          -0.13956099074400827,
          1.5064508689473302,
          -0.16338488846007646,
          -0.1497712326223232,
          -0.07190621044751025,
          -0.18644540360580333,
          -0.129446171686986,
          -0.16287596674651558,
          -0.059882934964634704,
          2.235990145336836,
          -0.08752374553240941,
          -0.16039497339290634,
          -0.16729722413307563,
          -0.16338488846007646,
          -0.20648419607726257,
          -0.2091560350734571,
          -0.18867193610263214,
          -0.15807301807478488,
          -0.09862460040945586,
          -0.08548805867816592,
          0.024407223843884236,
          -0.15126619015590825,
          -0.13943376031561805,
          0.06025439704282794,
          -0.1577867496109069,
          -0.14283717427505635,
          -0.16058581903549166,
          -0.16484803838656395,
          -0.14954857937264032,
          -0.10555865875672271,
          1.6661568641841504,
          -0.1761715465132933,
          -0.08933677913697,
          -0.14751289251839683,
          -0.07257417019655886,
          -0.14989846305071342,
          -0.20657961889855522,
          -0.11783639509637867,
          -0.19439730538019193,
          -0.08109860889870345,
          -0.07925376768704527,
          -0.169555564237002,
          -0.16478442317236883,
          -0.1909938914207536,
          -0.1165640908124765,
          -0.10412731643733275,
          -0.1946199586298748,
          -0.19026231645750985,
          -0.16262150588973515,
          1.126922501059312,
          -0.16096751032066234,
          -0.17305440101773298,
          -0.1570233670405656,
          -0.1508844988707376,
          -0.0908635442776526,
          -0.14096052545630064,
          -0.12928713365149822,
          -0.15947255278707728,
          -0.13380381385935092,
          -0.16418007863751533,
          -0.20886976660957915,
          -0.2068022721482381,
          -0.1791614615804634,
          -0.1560373312205414,
          0.013815290680398653,
          -0.08516998260719037,
          1.577254602346486,
          0.07663531469806843,
          -0.20797915361084762,
          0.07612639298450757,
          -0.11386044420918438,
          -0.0522173016541241,
          -0.12394345565910911,
          0.06998752481467957,
          -0.1856502134283645,
          0.03484011897188206,
          -0.18253306793280416,
          -0.17550358676424463,
          -0.1648162307794664,
          -0.1489442348377868,
          0.58695656297123,
          -0.1745811661584156,
          -0.0009434390128665527,
          0.017568588317910083,
          0.33131882472818586,
          -0.1989457931951422,
          -0.18733601660453486,
          -0.20934688071604243,
          -0.20250824519006827,
          0.022944073917396758,
          -0.19318861631048484,
          -0.0623957359253415,
          -0.20323982015331202,
          -0.18997604799363185,
          0.8778371298783642,
          -0.18593648189224246,
          -0.17162305869834302,
          -0.14643143387708,
          -0.1867634796767789,
          -0.2044485092230191,
          -0.19388838366663103,
          -0.2094423035373351,
          -0.08475648371492218,
          5.566914568199821,
          0.5919503572855459,
          -0.11554624738535477,
          -0.17677589104814684,
          -0.1331994693244974,
          -0.1453817828428607,
          -0.1684422979885876,
          0.29187739192721845,
          -0.1512343825488107,
          -0.14684493276934824
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "coloraxis": {
         "colorbar": {
          "title": {
           "text": "color"
          }
         },
         "colorscale": [
          [
           0,
           "#0d0887"
          ],
          [
           0.1111111111111111,
           "#46039f"
          ],
          [
           0.2222222222222222,
           "#7201a8"
          ],
          [
           0.3333333333333333,
           "#9c179e"
          ],
          [
           0.4444444444444444,
           "#bd3786"
          ],
          [
           0.5555555555555556,
           "#d8576b"
          ],
          [
           0.6666666666666666,
           "#ed7953"
          ],
          [
           0.7777777777777778,
           "#fb9f3a"
          ],
          [
           0.8888888888888888,
           "#fdca26"
          ],
          [
           1,
           "#f0f921"
          ]
         ]
        },
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 60
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "fillpattern": {
             "fillmode": "overlay",
             "size": 10,
             "solidity": 0.2
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "x"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "y"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grafico_hierarquico = px.scatter( x = X_base[:,0], y = X_base[:,1], color = rotulos_hc)\n",
    "grafico_hierarquico.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DBSCAN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DBSCAN()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DBSCAN</label><div class=\"sk-toggleable__content\"><pre>DBSCAN()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "DBSCAN()"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Aplicação do Modelo DBSCAN, utilizando os parâmetros 'eps' e 'min_samples' no padrão\n",
    "dbscan_base = DBSCAN(eps = 0.5, min_samples=5)\n",
    "dbscan_base.fit(X_base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0, -1,  0,  0,\n",
       "        0,  0,  0, -1,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0, -1,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0, -1,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0, -1,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0, -1,  0,  0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "       -1,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0, -1,  0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "       -1,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0, -1, -1,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0,  0,  0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0,  0,  0,\n",
       "        0,  0], dtype=int64)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Rótulos gerado pelo algoritmo\n",
    "rotulos_dbscan = dbscan_base.labels_\n",
    "rotulos_dbscan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "x=%{x}<br>y=%{y}<br>color=%{marker.color}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": [
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           -1,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0,
           0
          ],
          "coloraxis": "coloraxis",
          "symbol": "circle"
         },
         "mode": "markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
          -0.18490489291461773,
          0.11844070742238616,
          -0.1291428340291391,
          -0.2228230929567432,
          -0.20051826940255177,
          -0.16706103407126457,
          -0.2272840576675815,
          -0.22505357531216236,
          -0.04215402216779238,
          -0.2072097164688092,
          0.10951877800070957,
          -0.2228230929567432,
          -0.25628032828803043,
          -0.2272840576675815,
          0.058217683826069205,
          0.8611913317769618,
          -0.18490489291461773,
          0.406172931271456,
          -0.1938268223362943,
          -0.0912246339870136,
          -0.12691235167371992,
          -0.21613164589048578,
          -0.21390116353506664,
          -0.15813910464958797,
          -0.2362059870892581,
          -0.16260006936042629,
          -0.2272840576675815,
          -0.18713537527003687,
          0.06044816618148835,
          -0.20051826940255177,
          -0.18490489291461773,
          -0.08899415163159445,
          -0.2072097164688092,
          -0.24735839886635383,
          -0.2406669518000964,
          -0.24958888122177297,
          0.11174926035612871,
          0.9481801436383085,
          -0.22059261060132407,
          -0.21836212824590492,
          -0.18936585762545602,
          -0.23397550473383896,
          -0.16929151642668372,
          1.516953144270191,
          -0.21836212824590492,
          0.16081987217534993,
          -0.12691235167371992,
          -0.23174502237841982,
          -0.20944019882422835,
          -0.04884546923404982,
          -0.19159633998087516,
          -0.16929151642668372,
          -0.20497923411339006,
          -0.07115029278824128,
          -0.13360379873997738,
          -0.01538823390276262,
          -0.2362059870892581,
          -0.2116706811796475,
          0.2031990369283137,
          -0.21390116353506664,
          1.6307077443965672,
          -0.2406669518000964,
          -0.031001610390696644,
          -0.1782134458483603,
          -0.25181936357719215,
          23.638877145317284,
          -0.046614986878630665,
          -0.2072097164688092,
          -0.21836212824590492,
          -0.2406669518000964,
          -0.2228230929567432,
          3.711747782002631,
          -0.2116706811796475,
          -0.1157599398966242,
          -0.22951454002300067,
          0.2165819310608286,
          -0.21836212824590492,
          0.3035707429221753,
          0.3370279782534625,
          -0.20497923411339006,
          -0.24735839886635383,
          -0.2072097164688092,
          -0.1603695870050071,
          -0.18713537527003687,
          -0.1291428340291391,
          -0.18044392820377944,
          -0.19159633998087516,
          -0.20497923411339006,
          -0.1603695870050071,
          -0.10460752811952848,
          -0.2027487517579709,
          -0.24512791651093468,
          -0.1157599398966242,
          0.04260430733813518,
          -0.18713537527003687,
          -0.2362059870892581,
          0.2210428957716669,
          -0.22505357531216236,
          -0.1202209046074625,
          -0.21390116353506664,
          0.08944443680193725,
          0.00245562494059055,
          -0.16483055171584543,
          -0.1603695870050071,
          -0.20497923411339006,
          -0.19605730469171348,
          -0.20944019882422835,
          -0.25181936357719215,
          -0.1447562105170731,
          0.16081987217534993,
          -0.2072097164688092,
          -0.2027487517579709,
          -0.13360379873997738,
          -0.25404984593261126,
          -0.01984919861360091,
          -0.0020053397702477424,
          -0.13360379873997738,
          -0.2272840576675815,
          -0.07338077514366043,
          -0.03992353981237323,
          -0.06445884572198383,
          -0.2362059870892581,
          0.5020836725544793,
          -0.17152199878210286,
          -0.173752481137522,
          -0.053306433944888106,
          -0.06445884572198383,
          -0.21390116353506664,
          -0.2406669518000964,
          -0.17152199878210286,
          -0.18044392820377944,
          -0.2362059870892581,
          -0.20497923411339006,
          -0.2406669518000964,
          0.2589610958137924,
          -0.18267441055919859,
          -0.1492171752279114,
          -0.10237704576410933,
          -0.20944019882422835,
          -0.013157751547343473,
          -0.18267441055919859,
          -0.18044392820377944,
          -0.12468186931830079,
          -0.24289743415551554,
          -0.10014656340869017,
          0.12736263684406274,
          0.9481801436383085,
          -0.21836212824590492,
          -0.19828778704713262,
          -0.03323209274611579,
          -0.24289743415551554,
          -0.1492171752279114,
          -0.17598296349294115,
          -0.12691235167371992,
          0.12736263684406274,
          0.18981614279579884,
          -0.046614986878630665,
          -0.15590862229416882,
          -0.18490489291461773,
          -0.19159633998087516,
          -0.24289743415551554,
          -0.23843646944467725,
          -0.25181936357719215,
          -0.24735839886635383,
          -0.046614986878630665,
          0.47085691957861125,
          -0.19828778704713262,
          -0.23397550473383896,
          -0.20051826940255177,
          -0.23174502237841982,
          -0.05553691630030725,
          -0.24289743415551554,
          -0.21613164589048578,
          -0.19605730469171348,
          -0.20051826940255177,
          -0.2272840576675815,
          -0.2027487517579709,
          -0.16706103407126457,
          -0.2406669518000964,
          -0.19605730469171348,
          -0.24289743415551554,
          -0.2027487517579709,
          0.0626786485369075,
          -0.22059261060132407,
          -0.20944019882422835,
          -0.2362059870892581,
          -0.22059261060132407,
          -0.173752481137522,
          -0.25404984593261126,
          0.09390540151277554,
          -0.24289743415551554,
          -0.23397550473383896,
          -0.03769305745695408,
          -0.20051826940255177,
          -0.09568559869785188,
          -0.2027487517579709,
          -0.22951454002300067,
          -0.18044392820377944,
          -0.12245138696288164,
          0.5310799431749282,
          -0.22505357531216236,
          -0.173752481137522,
          1.443347226541359,
          -0.024310163324439204,
          -0.24958888122177297,
          5.748178172500311,
          -0.14029524580623481,
          -0.01538823390276262,
          -0.17152199878210286,
          -0.25404984593261126,
          0.10505781328987128,
          -0.2072097164688092,
          0.053756719115230917,
          0.8745742259094768,
          -0.18936585762545602,
          -0.23843646944467725,
          -0.23843646944467725,
          -0.2272840576675815,
          -0.23843646944467725,
          -0.2406669518000964,
          -0.23397550473383896,
          -0.16929151642668372,
          -0.21390116353506664,
          -0.16929151642668372,
          -0.2027487517579709,
          -0.18936585762545602,
          -0.18713537527003687,
          -0.2027487517579709,
          -0.2272840576675815,
          -0.12691235167371992,
          -0.16929151642668372,
          -0.21836212824590492,
          0.8188121670239981,
          -0.18713537527003687,
          -0.2406669518000964,
          -0.18044392820377944,
          -0.11129897518578591,
          -0.21836212824590492,
          -0.2027487517579709,
          -0.2406669518000964,
          0.5712286255724728,
          -0.24512791651093468,
          -0.2116706811796475,
          -0.2072097164688092,
          -0.053306433944888106,
          -0.22059261060132407,
          -0.19159633998087516,
          2.507287310076292,
          -0.1938268223362943,
          -0.17598296349294115,
          -0.21390116353506664,
          -0.21836212824590492,
          -0.19605730469171348,
          -0.2027487517579709,
          -0.23397550473383896,
          -0.24289743415551554,
          -0.21613164589048578,
          -0.13806476345081567,
          -0.2228230929567432,
          -0.1291428340291391,
          -0.22059261060132407,
          -0.24958888122177297,
          -0.24958888122177297,
          -0.2116706811796475,
          -0.00869678683650518,
          -0.14029524580623481,
          -0.173752481137522,
          -0.2116706811796475,
          -0.10014656340869017,
          -0.08007222220991786,
          0.6849832256988493,
          -0.010927269191924327,
          -0.0577673986557264,
          -0.2272840576675815,
          -0.20944019882422835,
          -0.24512791651093468,
          -0.24289743415551554,
          -0.17598296349294115,
          -0.1202209046074625,
          -0.1782134458483603,
          0.267883025235469,
          -0.23174502237841982,
          -0.2362059870892581,
          -0.18490489291461773,
          -0.1938268223362943,
          -0.13360379873997738,
          -0.20944019882422835,
          -0.1603695870050071,
          -0.1447562105170731,
          -0.18267441055919859,
          0.5890724844158259,
          -0.21836212824590492,
          -0.2406669518000964,
          -0.21613164589048578,
          -0.2228230929567432,
          -0.21836212824590492,
          0.04483478969355433,
          -0.20051826940255177,
          -0.20944019882422835,
          -0.19159633998087516,
          -0.24289743415551554,
          0.029221413205620304,
          -0.2272840576675815,
          -0.2228230929567432,
          0.9258753200841171,
          -0.18490489291461773,
          -0.17152199878210286,
          -0.24512791651093468,
          -0.22951454002300067,
          -0.21836212824590492,
          -0.19605730469171348,
          -0.24958888122177297,
          -0.22059261060132407,
          -0.07115029278824128,
          3.5266177465028417,
          -0.1782134458483603,
          -0.24512791651093468,
          0.1251321544886436,
          -0.07561125749907957,
          -0.17152199878210286,
          -0.2228230929567432,
          -0.06668932807740298,
          -0.173752481137522,
          -0.23174502237841982,
          -0.20944019882422835,
          0.3972510018497794,
          -0.1938268223362943,
          -0.18713537527003687,
          -0.21390116353506664,
          -0.22951454002300067,
          -0.20944019882422835,
          -0.1202209046074625,
          -0.18936585762545602,
          0.07383106031400323,
          -0.2072097164688092,
          -0.21390116353506664,
          -0.13806476345081567,
          1.472343497161808,
          -0.2406669518000964,
          -0.24289743415551554,
          -0.19159633998087516,
          0.2611915781692115,
          -0.19605730469171348,
          -0.19828778704713262,
          -0.2272840576675815,
          -0.10906849283036676,
          -0.22059261060132407,
          -0.23174502237841982,
          -0.21836212824590492,
          -0.2027487517579709,
          -0.23174502237841982,
          -0.10460752811952848,
          -0.18044392820377944,
          -0.18713537527003687,
          -0.00869678683650518,
          -0.028771128035277496,
          2.59204563958222,
          -0.2072097164688092,
          -0.1447562105170731,
          -0.1492171752279114,
          1.166767414469385,
          -0.1603695870050071,
          0.2857268840788221,
          -0.2362059870892581,
          -0.09791608105327103,
          -0.0912246339870136,
          -0.14029524580623481,
          0.5801505549941494,
          -0.02207968096902006,
          -0.2272840576675815,
          0.10282733093445214,
          -0.24512791651093468,
          -0.20051826940255177,
          -0.1603695870050071,
          -0.15367813993874968,
          -0.10683801047494762,
          -0.017618716258181767,
          -0.1492171752279114,
          -0.11799042225204334,
          -0.14698669287249225,
          -0.10460752811952848,
          -0.0577673986557264,
          0.8232731317348363,
          -0.20944019882422835,
          -0.18490489291461773,
          -0.20497923411339006,
          0.6113773079700174,
          -0.20051826940255177,
          0.3035707429221753,
          -0.24735839886635383,
          -0.046614986878630665,
          -0.09568559869785188,
          -0.173752481137522,
          -0.082302704565337,
          -0.2272840576675815,
          0.16528083688618822,
          -0.21836212824590492,
          0.6158382726808558,
          0.41286437833771344,
          -0.22951454002300067,
          -0.21613164589048578,
          -0.17598296349294115,
          -0.2406669518000964,
          -0.1157599398966242,
          -0.16706103407126457,
          -0.18267441055919859,
          0.03145189556103945,
          -0.22951454002300067,
          -0.173752481137522,
          -0.24958888122177297,
          0.6693698492109152,
          0.19204662515121798,
          -0.21613164589048578,
          -0.18936585762545602,
          -0.2362059870892581,
          -0.20497923411339006,
          -0.2406669518000964,
          0.16305035453076908,
          6.916950926739944,
          -0.20051826940255177,
          -0.20051826940255177,
          -0.2272840576675815,
          -0.12245138696288164,
          -0.21836212824590492,
          0.4953922254882218,
          -0.21836212824590492,
          -0.1938268223362943,
          -0.082302704565337,
          -0.16260006936042629,
          0.3325670135426242,
          -0.03992353981237323,
          -0.08453318692075615,
          -0.2362059870892581,
          -0.20497923411339006,
          -0.18490489291461773,
          0.7585891434276811,
          -0.22059261060132407,
          -0.23397550473383896,
          0.314723154699271,
          -0.24289743415551554,
          -0.09791608105327103,
          -0.15813910464958797,
          -0.1938268223362943,
          -0.23174502237841982,
          -0.2027487517579709,
          -0.18936585762545602,
          -0.03769305745695408,
          -0.19828778704713262,
          0.14074553097657763,
          -0.19828778704713262,
          -0.01984919861360091,
          -0.23397550473383896,
          -0.03323209274611579,
          0.7496672140060046,
          -0.024310163324439204,
          0.047065272048973476,
          -0.11352945754120505,
          -0.17598296349294115,
          -0.18267441055919859,
          0.7050575668976216,
          -0.21390116353506664,
          -0.05107595158946896,
          -0.24512791651093468,
          -0.2228230929567432,
          -0.24512791651093468,
          -0.14698669287249225,
          -0.15813910464958797,
          -0.18936585762545602,
          -0.2272840576675815,
          0.2411172369704392,
          -0.2272840576675815,
          -0.0867636692761753,
          -0.1492171752279114,
          -0.04884546923404982,
          -0.13583428109539653,
          0.2031990369283137,
          -0.22505357531216236,
          -0.2406669518000964,
          -0.09791608105327103,
          -0.22059261060132407,
          -0.18490489291461773,
          -0.23397550473383896,
          -0.082302704565337,
          -0.19828778704713262,
          -0.1603695870050071,
          -0.17152199878210286,
          -0.12691235167371992,
          -0.25181936357719215,
          -0.1938268223362943,
          -0.16260006936042629,
          -0.23174502237841982,
          -0.1603695870050071,
          -0.1447562105170731,
          -0.07115029278824128,
          -0.06445884572198383,
          -0.17152199878210286,
          0.27234398994630726,
          -0.24958888122177297,
          -0.04438450452321152,
          -0.1157599398966242,
          4.590557830037775,
          -0.23174502237841982,
          -0.0912246339870136,
          -0.23397550473383896,
          -0.24289743415551554,
          -0.2027487517579709,
          0.8478084376444469,
          -0.10237704576410933,
          -0.05107595158946896,
          -0.25181936357719215,
          0.10728829564529042,
          -0.16483055171584543,
          -0.21836212824590492,
          -0.24958888122177297,
          -0.18713537527003687,
          0.04260430733813518,
          -0.18044392820377944,
          -0.2362059870892581,
          -0.053306433944888106,
          0.8522694023552853,
          -0.23174502237841982,
          -0.11129897518578591,
          -0.19828778704713262,
          -0.19159633998087516,
          0.9794068966141766,
          -0.20944019882422835,
          0.07160057795858409,
          -0.18267441055919859,
          -0.24289743415551554,
          -0.24958888122177297,
          -0.18267441055919859,
          -0.22505357531216236,
          0.09836636622361385,
          -0.24958888122177297,
          -0.24512791651093468,
          -0.21613164589048578,
          -0.19828778704713262,
          0.2411172369704392,
          0.00022514258517140383,
          0.7206709433855556,
          -0.1938268223362943,
          -0.23397550473383896,
          -0.06222836336656469,
          -0.21390116353506664,
          -0.22505357531216236,
          -0.19605730469171348,
          -0.24512791651093468,
          -0.2362059870892581,
          -0.2362059870892581,
          -0.035462575101534936,
          0.5979944138375026,
          0.7675110728493577,
          0.047065272048973476,
          -0.11352945754120505,
          0.18981614279579884,
          -0.18044392820377944,
          -0.23397550473383896,
          -0.25404984593261126,
          -0.25628032828803043,
          1.2559867086861507,
          -0.2362059870892581,
          2.0098897448178223,
          0.6403735785904664,
          -0.18713537527003687,
          -0.20497923411339006,
          -0.2228230929567432,
          -0.22059261060132407,
          -0.15590862229416882,
          -0.03323209274611579,
          -0.24735839886635383,
          -0.23397550473383896,
          -0.22951454002300067,
          -0.21613164589048578,
          -0.2072097164688092,
          -0.1447562105170731,
          -0.22505357531216236,
          0.3727156959401688,
          -0.25404984593261126,
          -0.22505357531216236,
          -0.21390116353506664,
          -0.1492171752279114,
          -0.06222836336656469,
          -0.03323209274611579,
          -0.15144765758333054,
          -0.2272840576675815,
          -0.21836212824590492,
          -0.173752481137522,
          -0.20944019882422835,
          -0.21613164589048578,
          -0.2272840576675815,
          -0.18490489291461773,
          -0.19605730469171348,
          -0.22505357531216236,
          -0.22059261060132407,
          -0.2027487517579709,
          -0.1603695870050071,
          -0.22951454002300067,
          -0.20051826940255177,
          -0.17598296349294115,
          0.42847775482564743,
          -0.12691235167371992,
          0.033682377916458596,
          0.13182360155490103,
          -0.046614986878630665,
          -0.12691235167371992,
          1.9295923800227328,
          -0.21390116353506664,
          0.15635890746451164,
          0.47531788428944954,
          -0.20497923411339006,
          -0.17598296349294115,
          0.00022514258517140383,
          -0.18044392820377944,
          -0.15367813993874968,
          1.6463211208845012,
          -0.2027487517579709,
          -0.2027487517579709,
          0.06490913089232665,
          -0.1782134458483603,
          -0.2406669518000964,
          -0.24735839886635383,
          -0.22505357531216236,
          -0.2116706811796475,
          -0.1492171752279114,
          -0.017618716258181767,
          -0.22059261060132407,
          -0.24512791651093468,
          -0.06668932807740298,
          -0.046614986878630665,
          -0.18713537527003687,
          -0.18713537527003687,
          -0.1782134458483603,
          -0.07561125749907957,
          -0.21836212824590492,
          -0.1782134458483603,
          -0.21613164589048578,
          3.4708556876173633,
          -0.23174502237841982,
          -0.09568559869785188,
          -0.08453318692075615,
          -0.24289743415551554,
          -0.23174502237841982,
          -0.22059261060132407,
          -0.19605730469171348,
          -0.12691235167371992,
          -0.06891981043282214,
          -0.13137331638455824,
          -0.13137331638455824,
          -0.08899415163159445,
          -0.2228230929567432,
          -0.15813910464958797,
          -0.22505357531216236,
          -0.22059261060132407,
          -0.1447562105170731,
          -0.22951454002300067,
          -0.23843646944467725,
          -0.21836212824590492,
          -0.17598296349294115,
          1.3162097322824677,
          -0.10460752811952848,
          0.10951877800070957,
          0.018069001428524575,
          -0.22059261060132407,
          0.16528083688618822,
          -0.21390116353506664,
          -0.2228230929567432,
          -0.22951454002300067,
          -0.18267441055919859,
          -0.22951454002300067,
          -0.23397550473383896,
          -0.21390116353506664,
          -0.24512791651093468,
          -0.24289743415551554,
          0.022529966139362867,
          2.395763192305335,
          -0.13806476345081567,
          -0.19159633998087516,
          -0.22951454002300067,
          -0.10683801047494762,
          -0.20944019882422835,
          -0.25404984593261126,
          -0.1492171752279114,
          -0.2362059870892581,
          -0.22059261060132407,
          0.17420276630786483,
          -0.22505357531216236,
          -0.07561125749907957,
          -0.21390116353506664,
          -0.21390116353506664,
          -0.21390116353506664,
          -0.22059261060132407,
          -0.2406669518000964,
          -0.2228230929567432,
          -0.18267441055919859,
          0.19873807221747541,
          -0.2072097164688092,
          -0.23397550473383896,
          -0.082302704565337,
          -0.2228230929567432,
          -0.20051826940255177,
          -0.21613164589048578,
          -0.15367813993874968,
          0.03814334262729689,
          -0.23174502237841982,
          -0.24958888122177297,
          -0.22951454002300067,
          0.3013402605667561,
          -0.1492171752279114,
          -0.1938268223362943,
          -0.21390116353506664,
          -0.10014656340869017,
          -0.24512791651093468,
          0.330336531187205,
          -0.2116706811796475,
          -0.18936585762545602,
          -0.20497923411339006,
          -0.18713537527003687,
          -0.24512791651093468,
          -0.21613164589048578,
          -0.17598296349294115,
          -0.1202209046074625,
          -0.13806476345081567,
          -0.21390116353506664,
          -0.03992353981237323,
          0.3481803900305582,
          -0.18936585762545602,
          -0.22505357531216236,
          -0.25181936357719215,
          -0.1447562105170731,
          -0.18044392820377944,
          0.7005966021867833,
          -0.18713537527003687,
          -0.22059261060132407,
          -0.16260006936042629,
          -0.22951454002300067,
          -0.15590862229416882,
          -0.10014656340869017,
          -0.024310163324439204,
          0.2321953075487626,
          -0.19159633998087516,
          0.06044816618148835,
          -0.2406669518000964,
          -0.19828778704713262,
          -0.2272840576675815,
          -0.24289743415551554,
          -0.2228230929567432,
          -0.20051826940255177,
          -0.2362059870892581,
          0.1697418015970265,
          -0.21836212824590492,
          -0.2072097164688092,
          -0.23174502237841982,
          -0.18044392820377944,
          -0.16929151642668372,
          -0.2072097164688092,
          -0.24735839886635383,
          -0.18267441055919859,
          -0.1938268223362943,
          -0.24289743415551554,
          -0.1938268223362943,
          -0.18044392820377944,
          -0.25404984593261126,
          0.5600762137953771,
          -0.20051826940255177,
          -0.18713537527003687,
          -0.16706103407126457,
          -0.18267441055919859,
          -0.22951454002300067,
          -0.20497923411339006,
          0.10282733093445214,
          -0.25181936357719215,
          -0.16483055171584543,
          -0.21836212824590492,
          -0.20497923411339006,
          -0.25181936357719215,
          -0.21613164589048578,
          -0.24289743415551554,
          -0.20944019882422835,
          -0.1938268223362943,
          -0.22059261060132407,
          -0.24735839886635383,
          -0.2228230929567432,
          -0.14252572816165396,
          -0.19828778704713262,
          -0.1782134458483603,
          -0.2228230929567432,
          -0.23843646944467725,
          -0.01984919861360091,
          3.1652796049249403,
          -0.15144765758333054,
          -0.23843646944467725,
          -0.20051826940255177,
          -0.22059261060132407,
          -0.10906849283036676,
          -0.18936585762545602,
          -0.21836212824590492,
          -0.23174502237841982,
          0.2121209663499903,
          -0.2272840576675815,
          -0.18267441055919859,
          -0.25404984593261126,
          -0.2272840576675815,
          -0.12691235167371992,
          -0.11799042225204334,
          1.3429755205474974,
          0.44186064895816235,
          -0.15590862229416882,
          -0.1603695870050071,
          -0.09345511634243274,
          -0.25628032828803043,
          -0.20497923411339006,
          -0.18267441055919859,
          1.1779198262464805,
          0.21881241341624774,
          0.4262472724702283,
          -0.18267441055919859,
          0.029221413205620304,
          -0.13583428109539653,
          -0.22951454002300067,
          0.6448345433013046,
          -0.18713537527003687,
          -0.13360379873997738,
          3.680521029026763,
          5.600966337042648,
          -0.23843646944467725,
          0.6626784021446578,
          -0.20497923411339006,
          -0.2362059870892581,
          -0.10906849283036676,
          -0.19159633998087516,
          -0.20497923411339006,
          -0.23397550473383896,
          -0.24735839886635383,
          1.673086909149531,
          -0.2072097164688092,
          0.12736263684406274,
          -0.07338077514366043,
          -0.09791608105327103,
          -0.1157599398966242,
          -0.22505357531216236,
          -0.23174502237841982,
          -0.23397550473383896,
          1.3697413088125272,
          0.4597045078015155,
          -0.22505357531216236,
          -0.19605730469171348,
          -0.20944019882422835,
          -0.15813910464958797,
          -0.25181936357719215,
          0.22773434283792432,
          -0.21836212824590492,
          -0.23397550473383896
         ],
         "xaxis": "x",
         "y": [
          -0.19732360523316692,
          -0.1802747278288778,
          -0.1258201044778648,
          -0.09792483305330968,
          -0.1850776765006085,
          -0.18965797192265632,
          -0.20635696564887232,
          -0.16026774296451615,
          -0.14840350551712836,
          -0.1844415243586574,
          -0.16039497339290634,
          -0.18946712628007098,
          -0.16577045899239304,
          -0.058483400252342305,
          -0.028488826759348582,
          0.07539481802126381,
          -0.051453919083782815,
          -0.16402104060202752,
          -0.08847797374533602,
          -0.09363080609513984,
          -0.09770217980362679,
          -0.0421979054183945,
          -0.04458347595071108,
          -0.15311103136756643,
          -0.174549358551318,
          -0.1400699124575691,
          -0.18460056239414518,
          -0.11392405942337948,
          0.0547834886220486,
          -0.18224679946892616,
          -0.08742832271111674,
          -0.15336549222434684,
          -0.18272391357538947,
          -0.1616036624626134,
          -0.1829783744321699,
          -0.1588364006451262,
          -0.17117775219897724,
          -0.08268898925358116,
          -0.1162778223485985,
          -0.13571227028520422,
          -0.1283329054385716,
          -0.1718457119480259,
          -0.10078751769208956,
          0.0852233686144081,
          -0.040766563099004546,
          0.03840257096680815,
          -0.06401792388731677,
          -0.16631118831305144,
          -0.15829567132446776,
          -0.20956953396572534,
          0.06305346646741275,
          -0.19617853137765495,
          -0.2084562677173109,
          -0.14213740691891016,
          -0.17712577472621993,
          -0.16853772080988025,
          -0.18879916653102236,
          0.1799782301580224,
          0.06785641513914342,
          -0.1403561809214471,
          0.3050775488727035,
          -0.17299078580353788,
          0.5582661013692358,
          0.0763172386270929,
          -0.19372934563114327,
          22.007757755212086,
          0.007294731225400026,
          -0.1449682839505925,
          -0.16672468720531966,
          -0.19261607938272887,
          -0.1868907101051691,
          3.5875589861261137,
          -0.18227860707602372,
          0.0974056821327714,
          -0.2034624734029949,
          -0.0727014006249491,
          -0.1861909427490229,
          -0.1723228260544892,
          -0.08437479242975152,
          -0.1676153002040512,
          -0.15167968904817647,
          -0.12839652065276672,
          -0.1419147536692273,
          -0.04493335962878417,
          -0.14258271341827594,
          -0.14162848520534932,
          -0.21046014696445686,
          -0.21173245124835902,
          -0.03612265246276163,
          -0.07880846118767951,
          -0.20823361446762806,
          -0.1593135147515895,
          -0.2009496724422881,
          -0.14719481644742133,
          -0.09674795159070015,
          -0.18262849075409682,
          -0.026389524690910007,
          -0.12251211333971915,
          -0.20177667022682452,
          -0.1403879885285447,
          -0.2053391222217506,
          -0.2094423035373351,
          -0.19958194533709328,
          -0.12139884709130477,
          -0.02858424958064125,
          -0.09573010816357841,
          -0.17830265618882943,
          -0.18370994939541366,
          0.013115523324252462,
          0.0073583464395951224,
          -0.06150512292660997,
          -0.06338177174536569,
          -0.15641902250571205,
          -0.17947953765143893,
          -0.06296827285309747,
          0.1641698494305379,
          -0.06099620121304911,
          -0.1989457931951422,
          -0.0689481029874377,
          -0.10603577286318602,
          -0.20428947118753132,
          -0.1966238378770207,
          0.0948292659578695,
          -0.08857339656662869,
          -0.1986595247312642,
          -0.16188993092649137,
          -0.11207921821172133,
          -0.14115137109888598,
          -0.13421731275161913,
          -0.1799884593649998,
          -0.15816844089607754,
          -0.13087751400637593,
          -0.09712964287587082,
          -0.09506214841452977,
          -0.08940039435116512,
          -0.14993027065781098,
          0.13579746389951944,
          -0.14487286112929984,
          -0.16771072302534384,
          -0.17378597598097673,
          -0.15670529096959004,
          -0.06853460409516948,
          -0.16993725552217262,
          -0.16163547006971096,
          -0.06452684560087764,
          0.06120862525575461,
          0.0008377869845964963,
          -0.2013631713345563,
          -0.10018317315723603,
          -0.20149040176294652,
          -0.1880039763535835,
          -0.14741746969710418,
          -0.12184415359067051,
          -0.08380225550199555,
          -0.0561296373271233,
          -0.1494213489442501,
          -0.15743686593283382,
          -0.07782242536765535,
          -0.20543454504304323,
          -0.20228559194038537,
          -0.08892328024470178,
          -0.17012810116475796,
          -0.17531274112165932,
          -0.19649660744863048,
          -0.13800241799622812,
          0.20860507654582133,
          -0.14744927730420174,
          -0.1501211163003963,
          -0.16666107199112454,
          -0.16758349259695363,
          0.44655778524262524,
          -0.20782011557535987,
          -0.12391164805201153,
          -0.11926773741576863,
          -0.15597371600634627,
          -0.12912809561601044,
          -0.180401958257268,
          -0.20788373078955497,
          -0.18475960042963296,
          -0.10431816207991809,
          -0.15489225736502946,
          -0.18832205242455902,
          -0.06786664434612083,
          -0.00816376582401137,
          -0.14547720566415337,
          -0.21150979799867614,
          -0.18762228506841283,
          -0.1263926414056208,
          -0.17849350183141477,
          -0.15260210965400553,
          -0.13370839103805826,
          -0.1647526155652713,
          -0.17712577472621993,
          -0.1511707673346156,
          -0.11207921821172133,
          -0.027948097438690176,
          -0.20568900589982372,
          0.3319867844772345,
          -0.0481141203385396,
          0.3332908963682342,
          -0.1820877614334384,
          -0.18552298299997427,
          0.9107898108314305,
          -0.17534454872875688,
          -0.16418007863751533,
          9.936866284511517,
          -0.12305284266037758,
          -0.18370994939541366,
          -0.19083485338526585,
          -0.1632894656387838,
          -0.19032593167170495,
          -0.15988605167934547,
          -0.19223438809755822,
          1.2857378832974007,
          -0.18797216874648592,
          -0.15317464658176153,
          -0.14131040913437373,
          -0.20565719829272613,
          -0.11007533896457543,
          -0.0270256768328611,
          -0.17543997155004953,
          -0.1921707728833631,
          -0.20263547561845846,
          -0.15823205611027266,
          -0.200599788764215,
          -0.10826230536001483,
          -0.1139876746375746,
          -0.1165640908124765,
          -0.16023593535741856,
          -0.12642444901271835,
          -0.16408465581622264,
          -0.17871615508109764,
          -0.14242367538278816,
          -0.16392561778073486,
          -0.15804121046768732,
          -0.200599788764215,
          0.10478504697940398,
          -0.14643143387708,
          -0.15543298668568786,
          -0.1530474161533713,
          -0.180974495185024,
          -0.1515842662268838,
          -0.15578287036376098,
          -0.10504973704316183,
          -0.024989989978617625,
          -0.18113353322051176,
          -0.06427238474409719,
          0.8180706361420597,
          -0.04929100180114913,
          -0.1341855051445216,
          -0.16325765803168624,
          -0.20559358307853104,
          0.04209225339012444,
          -0.1809108799708289,
          -0.13469442685808244,
          -0.1335493530025705,
          0.05599217769175569,
          0.034999157007369816,
          -0.17811181054624411,
          -0.18380537221670634,
          -0.1513616129772009,
          -0.18959435670846123,
          -0.2013631713345563,
          -0.10562227397091781,
          -0.052280916868319226,
          0.011652373397764938,
          -0.1867316720696813,
          -0.02705748443995865,
          -0.11729566577572025,
          -0.03974871967188283,
          0.079307153694263,
          0.021385501169616565,
          -0.1681560295247096,
          -0.14029256570725201,
          -0.06996594641455943,
          -0.1670427632762952,
          -0.2061025047920919,
          -0.1935066923814604,
          -0.10893026510906346,
          -0.10126463179855287,
          0.4755663229155946,
          -0.1246432230152553,
          -0.15858193978834575,
          -0.17432670530163513,
          -0.18536394496448647,
          -0.19137558270592425,
          -0.16157185485551587,
          -0.19194811963368022,
          -0.12709240876176697,
          -0.0882235128885556,
          -0.07543685483533877,
          -0.21310017835355385,
          -0.16942833380861178,
          -0.17044617723573352,
          -0.1692056805589289,
          -0.21087364585672505,
          -0.19277511741821665,
          -0.19764168130414247,
          -0.1913437750988267,
          -0.16424369385171042,
          -0.15556021711407808,
          0.01117525929130165,
          -0.1768713138694395,
          -0.200599788764215,
          -0.14318705795312947,
          -0.1453817828428607,
          -0.19248884895433865,
          -0.21115991432060305,
          -0.15613275404183408,
          -0.13991087442208136,
          -0.13517154096454578,
          -0.13956099074400827,
          -0.1405152189569349,
          -0.17836627140302455,
          0.1292450968374233,
          -0.20858349814570115,
          -0.19703733676928892,
          -0.1245796078010602,
          -0.1730862086248305,
          -0.13097293682766858,
          -0.1788115779023903,
          -0.01338021338801028,
          -0.12709240876176697,
          -0.10699000107611263,
          -0.20991941764379843,
          0.34544140227949993,
          -0.07674096672633848,
          -0.14646324148417755,
          -0.13571227028520422,
          -0.2110326838922128,
          -0.09324911480996917,
          -0.10775338364645394,
          -0.17222740323319655,
          -0.19382476845243593,
          -0.19710095198348404,
          -0.17423128248034248,
          -0.15800940286058976,
          7.266172362172467,
          -0.06328634892407302,
          -0.16392561778073486,
          -0.16567503617110035,
          1.0944787418198068,
          -0.062204890282756164,
          -0.18539575257158405,
          -0.008322803859499133,
          -0.11230187146140422,
          -0.1070218086832102,
          -0.06474949885056053,
          -0.19986821380097125,
          -0.19633756941314273,
          -0.19312500109628974,
          -0.1358395007135944,
          -0.13895664620915474,
          -0.1754717791571471,
          0.2613420891135663,
          -0.08399310114458088,
          4.173168840399186,
          -0.19420645973760658,
          -0.12254392094681672,
          -0.15587829318505364,
          0.067601954282363,
          -0.06230031310404883,
          0.0915530824268214,
          -0.21240041099740767,
          -0.17531274112165932,
          -0.11268356274657489,
          -0.15075726844234738,
          0.7841319193689692,
          -0.1816742625411702,
          -0.09585733859196863,
          -0.17279994016095254,
          -0.2020629386907025,
          -0.07941280572253306,
          -0.1110613747845996,
          0.11808062674618171,
          -0.14757650773259193,
          -0.1302731694715224,
          -0.1957968400924843,
          -0.15581467797085852,
          0.007676422510570648,
          -0.08023980350706947,
          0.07870280915940948,
          0.40667104594229203,
          -0.15683252139798026,
          -0.19347488477436284,
          -0.17744385079719546,
          -0.09483949516484688,
          -0.13008232382893706,
          -0.1332630845386925,
          -0.18390079503799897,
          -0.16176270049810118,
          -0.19477899666536255,
          -0.16173089289100362,
          0.013560829823618224,
          -0.15991785928644306,
          -0.17451755094422047,
          -0.19353849998855793,
          -0.11688216688345206,
          -0.18886278174521745,
          -0.13666649849813084,
          -0.15107534451332294,
          -0.1365392680697406,
          -0.15177511186946913,
          -0.14786277619646995,
          -0.20371693425977533,
          -0.17792096490365877,
          -0.198246025838996,
          -0.11373321378079417,
          -0.19341126956016771,
          -0.16093570271356478,
          2.352246949278397,
          -0.2061025047920919,
          -0.2044803168301166,
          -0.1600132821077357,
          -0.18685890249807155,
          -0.1449046687363974,
          -0.1986595247312642,
          0.7870582192219442,
          0.9780310922356602,
          -0.19220258049046066,
          -0.059978357785927375,
          -0.20266728322555605,
          -0.16720180131178297,
          -0.20565719829272613,
          0.1517012674482966,
          -0.2024128223687756,
          -0.13475804207227757,
          -0.14846712073132345,
          -0.1969101063408987,
          0.8219193566008637,
          -0.06653072484802355,
          0.08471444690084724,
          -0.13456719642969223,
          -0.1274104848327425,
          -0.21290933271096854,
          0.370060490173007,
          -0.1910575066349487,
          -0.1706688304854164,
          -0.047477968196588526,
          -0.1824376451115115,
          -0.15543298668568786,
          -0.19897760080223972,
          -0.11198379539042867,
          -0.06783483673902328,
          -0.17200474998351367,
          -0.1844415243586574,
          -0.1714322130557577,
          -0.15788217243219957,
          -0.015415900242253758,
          -0.1864772112129009,
          -0.14344151880990988,
          -0.15288837811788353,
          -0.189180857816193,
          0.24518382470800879,
          0.13843749528861649,
          -0.09677975919779772,
          -0.11109318239169716,
          -0.13081389879218083,
          0.003382395552400833,
          -0.0564795210051964,
          -0.1353623866071311,
          1.2134391923646597,
          -0.08068511000643523,
          -0.1932204239175824,
          -0.12562925883527948,
          -0.1778891572965612,
          0.01581916992754456,
          -0.09258115506092054,
          -0.17502647265778132,
          0.17940569323026645,
          -0.16389381017363733,
          0.06597976632038775,
          -0.20540273743594573,
          0.001060440234279355,
          -0.13889303099495964,
          0.25399453187403126,
          -0.17346789991000117,
          -0.2068658873624332,
          -0.17531274112165932,
          -0.1616036624626134,
          -0.12524756755010882,
          -0.16166727767680852,
          -0.17712577472621993,
          -0.16583407420658816,
          -0.15994966689354057,
          -0.12540660558559658,
          -0.08475648371492218,
          -0.19891398558804463,
          -0.11487828763630611,
          -0.10151909265533329,
          -0.20937868832314,
          -0.09747952655394392,
          -0.1902305088504123,
          -0.1952561107718259,
          -0.15540117907859033,
          -0.12146246230549987,
          -0.1070218086832102,
          -0.18383717982380388,
          -0.10823049775291725,
          0.042792020746270636,
          0.1470573568120537,
          -0.200599788764215,
          -0.20613431239918947,
          -0.20149040176294652,
          -0.19910483123062994,
          -0.0962390298771393,
          0.17345767070302376,
          -0.14970761740812807,
          -0.05011799958568553,
          -0.1864772112129009,
          -0.14655866430547024,
          -0.062332120711146376,
          -0.1960831085563623,
          -0.14089691024210554,
          -0.14379140248798297,
          -0.08335694900262978,
          -0.18959435670846123,
          -0.15167968904817647,
          -0.06672157049060888,
          0.6075996999775427,
          -0.18899001217360767,
          -0.1781754257604392,
          -0.04359744013068688,
          -0.08637867167689744,
          0.9685842329276867,
          -0.11077510632072161,
          -0.16958737184409953,
          -0.17668046822685415,
          -0.16643841874144166,
          -0.18526852214319384,
          -0.21179606646255414,
          -0.07120644309136404,
          -0.0807805328277279,
          -0.16195354614068652,
          -0.18173787775536532,
          -0.044360822701028195,
          0.0003606728781331635,
          0.2560938339424699,
          -0.02871148000903146,
          -0.028934133258714342,
          -0.11560986259954986,
          -0.18393260264509656,
          -0.11869520048801263,
          -0.1989457931951422,
          -0.19888217798094707,
          -0.15858193978834575,
          -0.13972002877949602,
          -0.16262150588973515,
          -0.17369055315968407,
          -0.13997448963627648,
          0.34054303078647663,
          -0.18364633418121853,
          -0.05711567314714747,
          -0.023654070480520338,
          -0.09741591133974879,
          -0.04194344456161407,
          -0.15718240507605338,
          -0.19115292945624138,
          -0.16592949702788082,
          0.04613181949151383,
          -0.18533213735738893,
          -0.061218854462731995,
          -0.12057184930676834,
          -0.0561296373271233,
          -0.11732747338281779,
          -0.15667348336249248,
          -0.17738023558300034,
          -0.16430730906590552,
          -0.17127317502026992,
          -0.08609240321301945,
          -0.15915447671610172,
          -0.18237402989731638,
          -0.09468045712935913,
          -0.06296827285309747,
          -0.19818241062480088,
          -0.19026231645750985,
          0.4597897497952077,
          -0.1690148349163436,
          -0.10263235890374771,
          -0.15517852582890743,
          -0.06344538695956078,
          -0.19770529651833757,
          0.0313412821911511,
          -0.1289054423663276,
          -0.18418706350187697,
          -0.17369055315968407,
          0.028128713874298095,
          -0.0689481029874377,
          -0.17461297376551313,
          -0.1584865169670531,
          -0.15431972043727346,
          0.004877353085985882,
          -0.20161763219133674,
          -0.14395044052347078,
          -0.16786976106083162,
          -0.13781157235364278,
          -0.12559745122818192,
          0.012479371182301366,
          -0.03520023185693254,
          0.10189055473352655,
          0.03595338522029644,
          -0.0709519822345836,
          -0.09286742352479853,
          -0.10832592057420992,
          -0.11004353135747785,
          0.7322537121928581,
          -0.18154703211277998,
          -0.18126076364890198,
          0.17049956324295124,
          -0.2001862898719468,
          -0.19140739031302179,
          -0.15190234229785934,
          -0.10193259154760151,
          -0.15043919237137185,
          0.6719782967429927,
          -0.14057883417113,
          -0.1109977595704045,
          -0.2013631713345563,
          -0.09592095380616375,
          -0.20177667022682452,
          -0.15482864215083433,
          -0.20413043315204352,
          -0.1683468751672949,
          -0.20292174408233646,
          0.07370901484509343,
          -0.20180847783392206,
          -0.18329645050314544,
          0.49690922727805364,
          -0.12238488291132894,
          -0.07053848334231541,
          -0.05558890800646487,
          -0.16220800699746696,
          -0.16933291098731912,
          -0.14096052545630064,
          -0.20727938625470144,
          -0.1987867551596544,
          6.54315364523796,
          0.0435235957095144,
          -0.07705904279731403,
          -0.11414671267306235,
          -0.18921266542329054,
          -0.14948496415844523,
          -0.14760831533968952,
          -0.14347332641700747,
          -0.0905136605995795,
          -0.18577744385675468,
          -0.19112112184914382,
          -0.09522118645001755,
          -0.00018005644252526532,
          -0.17299078580353788,
          -0.1792250767946585,
          -0.18072003432824355,
          -0.12820567501018137,
          0.159239670330417,
          -0.19353849998855793,
          -0.08450202285814173,
          -0.20371693425977533,
          -0.18603190471353512,
          1.1405679645041629,
          -0.1707324456996115,
          -0.19236161852594844,
          -0.15132980537010338,
          -0.19926386926611772,
          -0.07839496229541132,
          0.030514284406614668,
          -0.19640118462733785,
          -0.1511707673346156,
          7.0150194965301775,
          -0.19888217798094707,
          -0.1625260830684425,
          -0.12260753616101182,
          -0.21612190102782153,
          -0.1516478814410789,
          -0.1508208836565425,
          2.73899564397756,
          -0.016052052384204853,
          -0.1641164634233202,
          -0.1856502134283645,
          -0.1547968345437368,
          -0.16647022634853922,
          -0.18402802546638922,
          0.09613337784886922,
          -0.1875904774613153,
          -0.18176968536246285,
          0.14619855142041974,
          -0.1821513766476335,
          -0.1977371041254351,
          -0.09751133416104146,
          -0.1512343825488107,
          -0.20215836151199515,
          -0.15473321932954165,
          -0.18650901881999846,
          -0.09372622891643251,
          -0.13768434192525256,
          0.29620322649248587,
          -0.19500164991504543,
          -0.1638301949594422,
          -0.10749892278967352,
          -0.16061762664258925,
          -0.11665951363376917,
          -0.1792250767946585,
          -0.15476502693663924,
          -0.14283717427505635,
          -0.1935066923814604,
          -0.16637480352724657,
          -0.1999000214080688,
          -0.008354611466596704,
          -0.03351442868076218,
          -0.10463623815089364,
          0.074027090916069,
          -0.14560443609254362,
          -0.15734144311154113,
          -0.16923748816602643,
          -0.157850364825102,
          -0.20381235708106799,
          -0.1272196391901572,
          -0.04372467055907712,
          -0.1509481140849327,
          -0.1843779091444623,
          -0.2112553371418957,
          -0.07909472965155752,
          -0.11637324516989117,
          -0.18930808824458323,
          -0.07247874737526622,
          -0.06971148555777898,
          -0.17553539437134222,
          -0.20460754725850686,
          -0.14305982752473925,
          -0.17884338550948786,
          -0.1589000158593213,
          -0.02231815098242305,
          0.030005362693053813,
          -0.09703422005457815,
          -0.03275104611042087,
          -0.18959435670846123,
          -0.1804655734714631,
          -0.1180908559531591,
          -0.020377886949472238,
          1.3025322998449096,
          -0.13956099074400827,
          1.5064508689473302,
          -0.16338488846007646,
          -0.1497712326223232,
          -0.07190621044751025,
          -0.18644540360580333,
          -0.129446171686986,
          -0.16287596674651558,
          -0.059882934964634704,
          2.235990145336836,
          -0.08752374553240941,
          -0.16039497339290634,
          -0.16729722413307563,
          -0.16338488846007646,
          -0.20648419607726257,
          -0.2091560350734571,
          -0.18867193610263214,
          -0.15807301807478488,
          -0.09862460040945586,
          -0.08548805867816592,
          0.024407223843884236,
          -0.15126619015590825,
          -0.13943376031561805,
          0.06025439704282794,
          -0.1577867496109069,
          -0.14283717427505635,
          -0.16058581903549166,
          -0.16484803838656395,
          -0.14954857937264032,
          -0.10555865875672271,
          1.6661568641841504,
          -0.1761715465132933,
          -0.08933677913697,
          -0.14751289251839683,
          -0.07257417019655886,
          -0.14989846305071342,
          -0.20657961889855522,
          -0.11783639509637867,
          -0.19439730538019193,
          -0.08109860889870345,
          -0.07925376768704527,
          -0.169555564237002,
          -0.16478442317236883,
          -0.1909938914207536,
          -0.1165640908124765,
          -0.10412731643733275,
          -0.1946199586298748,
          -0.19026231645750985,
          -0.16262150588973515,
          1.126922501059312,
          -0.16096751032066234,
          -0.17305440101773298,
          -0.1570233670405656,
          -0.1508844988707376,
          -0.0908635442776526,
          -0.14096052545630064,
          -0.12928713365149822,
          -0.15947255278707728,
          -0.13380381385935092,
          -0.16418007863751533,
          -0.20886976660957915,
          -0.2068022721482381,
          -0.1791614615804634,
          -0.1560373312205414,
          0.013815290680398653,
          -0.08516998260719037,
          1.577254602346486,
          0.07663531469806843,
          -0.20797915361084762,
          0.07612639298450757,
          -0.11386044420918438,
          -0.0522173016541241,
          -0.12394345565910911,
          0.06998752481467957,
          -0.1856502134283645,
          0.03484011897188206,
          -0.18253306793280416,
          -0.17550358676424463,
          -0.1648162307794664,
          -0.1489442348377868,
          0.58695656297123,
          -0.1745811661584156,
          -0.0009434390128665527,
          0.017568588317910083,
          0.33131882472818586,
          -0.1989457931951422,
          -0.18733601660453486,
          -0.20934688071604243,
          -0.20250824519006827,
          0.022944073917396758,
          -0.19318861631048484,
          -0.0623957359253415,
          -0.20323982015331202,
          -0.18997604799363185,
          0.8778371298783642,
          -0.18593648189224246,
          -0.17162305869834302,
          -0.14643143387708,
          -0.1867634796767789,
          -0.2044485092230191,
          -0.19388838366663103,
          -0.2094423035373351,
          -0.08475648371492218,
          5.566914568199821,
          0.5919503572855459,
          -0.11554624738535477,
          -0.17677589104814684,
          -0.1331994693244974,
          -0.1453817828428607,
          -0.1684422979885876,
          0.29187739192721845,
          -0.1512343825488107,
          -0.14684493276934824
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "coloraxis": {
         "colorbar": {
          "title": {
           "text": "color"
          }
         },
         "colorscale": [
          [
           0,
           "#0d0887"
          ],
          [
           0.1111111111111111,
           "#46039f"
          ],
          [
           0.2222222222222222,
           "#7201a8"
          ],
          [
           0.3333333333333333,
           "#9c179e"
          ],
          [
           0.4444444444444444,
           "#bd3786"
          ],
          [
           0.5555555555555556,
           "#d8576b"
          ],
          [
           0.6666666666666666,
           "#ed7953"
          ],
          [
           0.7777777777777778,
           "#fb9f3a"
          ],
          [
           0.8888888888888888,
           "#fdca26"
          ],
          [
           1,
           "#f0f921"
          ]
         ]
        },
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 60
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "fillpattern": {
             "fillmode": "overlay",
             "size": 10,
             "solidity": 0.2
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "x"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "y"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotagem DBSCAN\n",
    "grafico_dbscan = px.scatter(x = X_base[:,0], y = X_base[:,1], color = rotulos_dbscan)\n",
    "grafico_dbscan.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Escolha do melhor modelo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observa-se que o K-Means foi melhor aplicado, pois nesse modelo foram apresentados três grupos distintos, sendo que o terceiro grupo é representado pelo outlier. Com isso, podemos ver que há trÊs grupos distintos com características distintas, enquanto os demais modelos nos mostra apenas dois grupos."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}