diff --git a/notebooks_jupyter/wikidata_exploration/wdt_genre_analyse.ipynb b/notebooks_jupyter/wikidata_exploration/wdt_genre_analyse.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9150426b-5190-4539-8204-61253a0f1bd4",
+   "metadata": {},
+   "source": [
+    "# Analyse des spécificités des genres\n",
+    "\n",
+    "Dans ce carnet est proposée une analyse des spécificités des genres, en relation avec le temps et la région d'origine.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 327,
+   "id": "f2085427-bf14-40c6-8939-b74d38f31d16",
+   "metadata": {
+    "metadata": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import scipy.stats as stats\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 328,
+   "id": "e6ce0f0e-db36-47cd-8015-a5bf33f0f7fa",
+   "metadata": {
+    "metadata": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "### Librairies déjà installées avec Python\n",
+    "import pprint\n",
+    "import sqlite3 as sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 329,
+   "id": "707a3b6f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from fanalysis.ca import CA \n",
+    "from fanalysis.mca import MCA"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "61cf955b-aaca-446c-a957-47b86a4ea610",
+   "metadata": {},
+   "source": [
+    "### Importer les données à analyser"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 330,
+   "id": "00b2f7ff-7d67-4602-9b1e-38dd37809a75",
+   "metadata": {
+    "metadata": {}
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<sqlite3.Connection at 0x7f2164861f40>"
+      ]
+     },
+     "execution_count": 330,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Se connecter à la base de données dans laquelle on va insérer\n",
+    "# le résultat de la requête SPARQL\n",
+    "cn = sql.connect('../../data/astronomers_import.db')\n",
+    "cn"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 331,
+   "id": "a28e6ce2",
+   "metadata": {
+    "metadata": {}
+   },
+   "outputs": [],
+   "source": [
+    "qr = \"\"\"\n",
+    "SELECT wp.personUri, wp.personLabel, \n",
+    " CASE \n",
+    "       WHEN wp.genderUri = \t'http://www.wikidata.org/entity/Q6581097'\n",
+    "       THEN 'M'\n",
+    "       WHEN wp.genderUri = \t'http://www.wikidata.org/entity/Q6581072'\n",
+    "       THEN 'F'\n",
+    "       ELSE 'A'\n",
+    "   END AS gender, max(wp.birthYear) AS birthYear,\n",
+    "   max(ga.label) AS area_label\n",
+    "FROM wdt_personne wp \n",
+    "   JOIN wdt_person_citizenship wpc\n",
+    "\t ON wpc.personUri = wp.personUri\n",
+    "   JOIN wdt_country wc \n",
+    "     ON wc.wdt_uri = wpc.nationaliteUri \n",
+    "   JOIN geographic_area ga\n",
+    "     ON ga.pk_geographic_area = wc.fk_geographic_area\n",
+    "     GROUP BY wp.personUri, personLabel\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 332,
+   "id": "34f32038-ae06-47de-8a52-fc50cdfb2da9",
+   "metadata": {
+    "metadata": {}
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "23459\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[('http://www.wikidata.org/entity/Q1000193',\n",
+       "  'Hans Elsässer',\n",
+       "  'M',\n",
+       "  '1929',\n",
+       "  'Espace_germanique'),\n",
+       " ('http://www.wikidata.org/entity/Q1000934',\n",
+       "  'Charles Christian Lauritsen',\n",
+       "  'M',\n",
+       "  '1892',\n",
+       "  'Amérique_nord'),\n",
+       " ('http://www.wikidata.org/entity/Q100153910',\n",
+       "  'Frank J. Blatt',\n",
+       "  'M',\n",
+       "  '1924',\n",
+       "  'Espace_germanique')]"
+      ]
+     },
+     "execution_count": 332,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Vérifier que les données ont été importées correctement\n",
+    "cur = cn.cursor()\n",
+    "l = cur.execute(qr).fetchall()\n",
+    "print(len(l))\n",
+    "l[:3]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 333,
+   "id": "8d825e48",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 23459 entries, 0 to 23458\n",
+      "Data columns (total 5 columns):\n",
+      " #   Column         Non-Null Count  Dtype \n",
+      "---  ------         --------------  ----- \n",
+      " 0   uri            23459 non-null  object\n",
+      " 1   nom            23459 non-null  object\n",
+      " 2   gender         23459 non-null  object\n",
+      " 3   annee_nais     23459 non-null  object\n",
+      " 4   origines_geog  23459 non-null  object\n",
+      "dtypes: object(5)\n",
+      "memory usage: 916.5+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "### Créer un DataFrame contenant les données\n",
+    "df_orig = pd.DataFrame(l, columns=['uri', 'nom', 'gender', 'annee_nais', \n",
+    "                     'origines_geog'])\n",
+    "df_orig.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 334,
+   "id": "d9ce9030",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "gender\n",
+       "M    21392\n",
+       "F     2055\n",
+       "A       12\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 334,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Distribution des genres\n",
+    "df_orig.groupby(by='gender').size().sort_values(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9ed6f1c4",
+   "metadata": {},
+   "source": [
+    "### Codage par périodes de cinquante ans"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 335,
+   "id": "e13186ea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### On transforme le type de valeur de la colonne BirthYear\n",
+    "# de objet à entier\n",
+    "df_orig['annee_nais'] = df_orig['annee_nais'].astype(int)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 336,
+   "id": "cec8612e",
+   "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>uri</th>\n",
+       "      <th>nom</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>annee_nais</th>\n",
+       "      <th>origines_geog</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q1000193</td>\n",
+       "      <td>Hans Elsässer</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1929</td>\n",
+       "      <td>Espace_germanique</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q1000934</td>\n",
+       "      <td>Charles Christian Lauritsen</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1892</td>\n",
+       "      <td>Amérique_nord</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q100153910</td>\n",
+       "      <td>Frank J. Blatt</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>Espace_germanique</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         uri                          nom  \\\n",
+       "0    http://www.wikidata.org/entity/Q1000193                Hans Elsässer   \n",
+       "1    http://www.wikidata.org/entity/Q1000934  Charles Christian Lauritsen   \n",
+       "2  http://www.wikidata.org/entity/Q100153910               Frank J. Blatt   \n",
+       "\n",
+       "  gender  annee_nais      origines_geog  \n",
+       "0      M        1929  Espace_germanique  \n",
+       "1      M        1892      Amérique_nord  \n",
+       "2      M        1924  Espace_germanique  "
+      ]
+     },
+     "execution_count": 336,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Créer une copie indépendante du DataFrame (attention aux copies de variables qui sont seulement des alias) \n",
+    "cdf_p = df_orig[df_orig['annee_nais'] < 1981].copy(deep=True)\n",
+    "cdf_p.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 337,
+   "id": "b9b36a35",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1360, 1980)"
+      ]
+     },
+     "execution_count": 337,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Année minimale et maximale dans la population\n",
+    "min(cdf_p['annee_nais']), max(cdf_p['annee_nais'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 338,
+   "id": "22968555",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([1351, 1401, 1451, 1501, 1551], [1801, 1851, 1901, 1951, 2001])"
+      ]
+     },
+     "execution_count": 338,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Créer une liste d'années pour séparer en périodes de 25 ans\n",
+    "# noter que la dernière année sera exclue, \n",
+    "# elle donc doit être supérieure à la valeur maximale \n",
+    "l_50 = list(range(1351, 2002, 50))\n",
+    "l_50[:5],l_50[-5:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 339,
+   "id": "ac6dbfe7",
+   "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>uri</th>\n",
+       "      <th>nom</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>annee_nais</th>\n",
+       "      <th>origines_geog</th>\n",
+       "      <th>periodes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q1000193</td>\n",
+       "      <td>Hans Elsässer</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1929</td>\n",
+       "      <td>Espace_germanique</td>\n",
+       "      <td>1901-1950</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q1000934</td>\n",
+       "      <td>Charles Christian Lauritsen</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1892</td>\n",
+       "      <td>Amérique_nord</td>\n",
+       "      <td>1851-1900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q100153910</td>\n",
+       "      <td>Frank J. Blatt</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>Espace_germanique</td>\n",
+       "      <td>1901-1950</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         uri                          nom  \\\n",
+       "0    http://www.wikidata.org/entity/Q1000193                Hans Elsässer   \n",
+       "1    http://www.wikidata.org/entity/Q1000934  Charles Christian Lauritsen   \n",
+       "2  http://www.wikidata.org/entity/Q100153910               Frank J. Blatt   \n",
+       "\n",
+       "  gender  annee_nais      origines_geog   periodes  \n",
+       "0      M        1929  Espace_germanique  1901-1950  \n",
+       "1      M        1892      Amérique_nord  1851-1900  \n",
+       "2      M        1924  Espace_germanique  1901-1950  "
+      ]
+     },
+     "execution_count": 339,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### fonction pd.cut : https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.cut.html\n",
+    "# On ajoute une nouvelle colonne qui contient la période sur la base de la liste précédente\n",
+    "# et de la valeur de l'année\n",
+    "\n",
+    "cdf_p['periodes'] = pd.cut(cdf_p['annee_nais'], l_50, right=False)\n",
+    "\n",
+    "### Transformer le code ajouté pour qu'il soit plus lisible\n",
+    "# noter qu'on a arrondi les valeurs\n",
+    "cdf_p['periodes'] = cdf_p['periodes'].apply(lambda x : str(int(x.left))+'-'+ str(int(x.right)-1))\n",
+    "\n",
+    "# Inspection\n",
+    "cdf_p.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 340,
+   "id": "05d5cea7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = cdf_p.groupby(by='periodes', observed=True).size()\\\n",
+    "      .plot(kind='bar',rot=60, fontsize=8, figsize=(6,4))\n",
+    "\n",
+    "ax.bar_label(ax.containers[0], fontsize=8)\n",
+    "\n",
+    "plt.ylabel('Effectif')\n",
+    "plt.xlabel('Périodes')\n",
+    "plt.title('Naissances par périodes de cinquante ans')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "87e98f2f",
+   "metadata": {},
+   "source": [
+    "### Distributions des genres par périodes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 341,
+   "id": "79339470",
+   "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>periodes</th>\n",
+       "      <th>1351-1400</th>\n",
+       "      <th>1401-1450</th>\n",
+       "      <th>1451-1500</th>\n",
+       "      <th>1501-1550</th>\n",
+       "      <th>1551-1600</th>\n",
+       "      <th>1601-1650</th>\n",
+       "      <th>1651-1700</th>\n",
+       "      <th>1701-1750</th>\n",
+       "      <th>1751-1800</th>\n",
+       "      <th>1801-1850</th>\n",
+       "      <th>1851-1900</th>\n",
+       "      <th>1901-1950</th>\n",
+       "      <th>1951-2000</th>\n",
+       "      <th>Total</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gender</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>F</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>24</td>\n",
+       "      <td>208</td>\n",
+       "      <td>820</td>\n",
+       "      <td>793</td>\n",
+       "      <td>1877</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>M</th>\n",
+       "      <td>13</td>\n",
+       "      <td>29</td>\n",
+       "      <td>66</td>\n",
+       "      <td>100</td>\n",
+       "      <td>147</td>\n",
+       "      <td>155</td>\n",
+       "      <td>202</td>\n",
+       "      <td>410</td>\n",
+       "      <td>513</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>2915</td>\n",
+       "      <td>10854</td>\n",
+       "      <td>4206</td>\n",
+       "      <td>20839</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Total</th>\n",
+       "      <td>13</td>\n",
+       "      <td>30</td>\n",
+       "      <td>66</td>\n",
+       "      <td>100</td>\n",
+       "      <td>149</td>\n",
+       "      <td>158</td>\n",
+       "      <td>208</td>\n",
+       "      <td>420</td>\n",
+       "      <td>523</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>3123</td>\n",
+       "      <td>11676</td>\n",
+       "      <td>5005</td>\n",
+       "      <td>22724</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "periodes  1351-1400  1401-1450  1451-1500  1501-1550  1551-1600  1601-1650  \\\n",
+       "gender                                                                       \n",
+       "A                 0          0          0          0          0          0   \n",
+       "F                 0          1          0          0          2          3   \n",
+       "M                13         29         66        100        147        155   \n",
+       "Total            13         30         66        100        149        158   \n",
+       "\n",
+       "periodes  1651-1700  1701-1750  1751-1800  1801-1850  1851-1900  1901-1950  \\\n",
+       "gender                                                                       \n",
+       "A                 0          0          0          0          0          2   \n",
+       "F                 6         10         10         24        208        820   \n",
+       "M               202        410        513       1229       2915      10854   \n",
+       "Total           208        420        523       1253       3123      11676   \n",
+       "\n",
+       "periodes  1951-2000  Total  \n",
+       "gender                      \n",
+       "A                 6      8  \n",
+       "F               793   1877  \n",
+       "M              4206  20839  \n",
+       "Total          5005  22724  "
+      ]
+     },
+     "execution_count": 341,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Tableau de contingence\n",
+    "X = \"periodes\"  # \"0\"\n",
+    "Y = \"gender\"\n",
+    "\n",
+    "ddf = cdf_p[[Y,X]].pivot_table(index=Y,columns=X,aggfunc=len,margins=True,margins_name=\"Total\").fillna(0).astype(int)\n",
+    "ddf"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c69696e5",
+   "metadata": {},
+   "source": [
+    "#### Commentaire\n",
+    "\n",
+    "Le tableau de contingence montre que une analyse quantitative est possible seulement à partir de 1851 et à l'exclusion du genre A='autres'. Aussi on limitera les naissances aux personnes nées avant 1976 afin de disposer de périodes de 25 ans complètes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 342,
+   "id": "477a5ed0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 19353 entries, 0 to 23458\n",
+      "Data columns (total 6 columns):\n",
+      " #   Column         Non-Null Count  Dtype   \n",
+      "---  ------         --------------  -----   \n",
+      " 0   uri            19353 non-null  object  \n",
+      " 1   nom            19353 non-null  object  \n",
+      " 2   gender         19353 non-null  object  \n",
+      " 3   annee_nais     19353 non-null  int64   \n",
+      " 4   origines_geog  19353 non-null  object  \n",
+      " 5   periodes       19353 non-null  category\n",
+      "dtypes: category(1), int64(1), object(4)\n",
+      "memory usage: 926.7+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "### Création d'un tableau de données pour la période contemporaine \n",
+    "cdf_cont = cdf_p[(cdf_p.annee_nais > 1851) \\\n",
+    "                 & (cdf_p.annee_nais < 1976) \\\n",
+    "                 & (cdf_p.gender != 'A')].copy(deep=True)\n",
+    "cdf_cont.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 343,
+   "id": "d98b562c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([1851, 1876, 1901, 1926, 1951], [1876, 1901, 1926, 1951, 1976])"
+      ]
+     },
+     "execution_count": 343,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Créer une liste d'années pour séparer en périodes de 25 ans\n",
+    "# noter que la dernière année sera exclue, \n",
+    "# elle donc doit être supérieure à la valeur maximale \n",
+    "l_25 = list(range(1851, 1977, 25))\n",
+    "l_25[:5],l_25[-5:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 344,
+   "id": "ada36319",
+   "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>uri</th>\n",
+       "      <th>nom</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>annee_nais</th>\n",
+       "      <th>origines_geog</th>\n",
+       "      <th>periodes</th>\n",
+       "      <th>period_25</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q1000193</td>\n",
+       "      <td>Hans Elsässer</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1929</td>\n",
+       "      <td>Espace_germanique</td>\n",
+       "      <td>1901-1950</td>\n",
+       "      <td>1926-1950</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q1000934</td>\n",
+       "      <td>Charles Christian Lauritsen</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1892</td>\n",
+       "      <td>Amérique_nord</td>\n",
+       "      <td>1851-1900</td>\n",
+       "      <td>1876-1900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q100153910</td>\n",
+       "      <td>Frank J. Blatt</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>Espace_germanique</td>\n",
+       "      <td>1901-1950</td>\n",
+       "      <td>1901-1925</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         uri                          nom  \\\n",
+       "0    http://www.wikidata.org/entity/Q1000193                Hans Elsässer   \n",
+       "1    http://www.wikidata.org/entity/Q1000934  Charles Christian Lauritsen   \n",
+       "2  http://www.wikidata.org/entity/Q100153910               Frank J. Blatt   \n",
+       "\n",
+       "  gender  annee_nais      origines_geog   periodes  period_25  \n",
+       "0      M        1929  Espace_germanique  1901-1950  1926-1950  \n",
+       "1      M        1892      Amérique_nord  1851-1900  1876-1900  \n",
+       "2      M        1924  Espace_germanique  1901-1950  1901-1925  "
+      ]
+     },
+     "execution_count": 344,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### fonction pd.cut : https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.cut.html\n",
+    "# On ajoute une nouvelle colonne qui contient la période sur la base de la liste précédente\n",
+    "# et de la valeur de l'année\n",
+    "\n",
+    "cdf_cont['period_25'] = pd.cut(cdf_cont['annee_nais'], l_25, right=False)\n",
+    "\n",
+    "### Transformer le code ajouté pour qu'il soit plus lisible\n",
+    "# noter qu'on a arrondi les valeurs\n",
+    "cdf_cont['period_25'] = cdf_cont['period_25'].apply(lambda x : str(int(x.left))+'-'+ str(int(x.right)-1))\n",
+    "\n",
+    "# Inspection\n",
+    "cdf_cont.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 345,
+   "id": "cd4b9b33",
+   "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>period_25</th>\n",
+       "      <th>1851-1875</th>\n",
+       "      <th>1876-1900</th>\n",
+       "      <th>1901-1925</th>\n",
+       "      <th>1926-1950</th>\n",
+       "      <th>1951-1975</th>\n",
+       "      <th>Total</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gender</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>F</th>\n",
+       "      <td>53</td>\n",
+       "      <td>152</td>\n",
+       "      <td>294</td>\n",
+       "      <td>526</td>\n",
+       "      <td>685</td>\n",
+       "      <td>1710</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>M</th>\n",
+       "      <td>1154</td>\n",
+       "      <td>1723</td>\n",
+       "      <td>3736</td>\n",
+       "      <td>7118</td>\n",
+       "      <td>3912</td>\n",
+       "      <td>17643</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Total</th>\n",
+       "      <td>1207</td>\n",
+       "      <td>1875</td>\n",
+       "      <td>4030</td>\n",
+       "      <td>7644</td>\n",
+       "      <td>4597</td>\n",
+       "      <td>19353</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "period_25  1851-1875  1876-1900  1901-1925  1926-1950  1951-1975  Total\n",
+       "gender                                                                 \n",
+       "F                 53        152        294        526        685   1710\n",
+       "M               1154       1723       3736       7118       3912  17643\n",
+       "Total           1207       1875       4030       7644       4597  19353"
+      ]
+     },
+     "execution_count": 345,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Tableau de contingence\n",
+    "X = \"period_25\"  # \"0\"\n",
+    "Y = \"gender\"\n",
+    "\n",
+    "ddf = cdf_cont[[Y,X]].pivot_table(index=Y,columns=X,aggfunc=len,margins=True,margins_name=\"Total\").fillna(0).astype(int)\n",
+    "ddf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 346,
+   "id": "61486cb0",
+   "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>period_25</th>\n",
+       "      <th>1851-1875</th>\n",
+       "      <th>1876-1900</th>\n",
+       "      <th>1901-1925</th>\n",
+       "      <th>1926-1950</th>\n",
+       "      <th>1951-1975</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gender</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>F</th>\n",
+       "      <td>53</td>\n",
+       "      <td>152</td>\n",
+       "      <td>294</td>\n",
+       "      <td>526</td>\n",
+       "      <td>685</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>M</th>\n",
+       "      <td>1154</td>\n",
+       "      <td>1723</td>\n",
+       "      <td>3736</td>\n",
+       "      <td>7118</td>\n",
+       "      <td>3912</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "period_25  1851-1875  1876-1900  1901-1925  1926-1950  1951-1975\n",
+       "gender                                                          \n",
+       "F                 53        152        294        526        685\n",
+       "M               1154       1723       3736       7118       3912"
+      ]
+     },
+     "execution_count": 346,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Production du tableau à analyser\n",
+    "D = ddf.iloc[:-1,:-1].copy(deep=True)\n",
+    "D"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 347,
+   "id": "c6612908",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dimensions: ( 2 , 5 ), effectif: 19353 , nombre max. facteurs: 1\n"
+     ]
+    }
+   ],
+   "source": [
+    "## Nombre de modalités ligne\n",
+    "K = D.shape[0]\n",
+    "## Nombre de modalités colonnes\n",
+    "L = D.shape[1]\n",
+    "# Effectif total\n",
+    "n = np.sum(D.values)\n",
+    "# Nombre max. de facteur\n",
+    "Hmax = np.min([K-1,L-1])\n",
+    "\n",
+    "print('Dimensions: (', K, ',', L, '), effectif:', n, ', nombre max. facteurs:', Hmax)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 348,
+   "id": "f35e0906",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Chi2 : 288.9077850587688 , dof : 4\n",
+      "p-value : 2.6742187719147277e-61\n",
+      "phi2 = inertie (variance totale) : 0.014928320418476144\n",
+      "Cramer:  0.1221815060411196\n"
+     ]
+    }
+   ],
+   "source": [
+    "### Valeurs produites par la fonction de la librairie 'stats'\n",
+    "statistic, p, dof, expected = stats.chi2_contingency(D)\n",
+    "\n",
+    "print('Chi2 :', statistic, ', dof :',dof)\n",
+    "print('p-value :', p)\n",
+    "\n",
+    "\n",
+    "print('phi2 = inertie (variance totale) :', statistic/n)\n",
+    "\n",
+    "\n",
+    "### Tableau à l'indépendance\n",
+    "dfe = round(pd.DataFrame(expected),4)\n",
+    "\n",
+    "### Coéfficient de Cramer\n",
+    "# https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.contingency.association.html\n",
+    "\n",
+    "vc = stats.contingency.association(D, method='cramer')\n",
+    "print('Cramer: ', vc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 349,
+   "id": "0ab34c76",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 500x200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Résidus pondérés (avec le signe)\n",
+    "### Doc. :\n",
+    "#   Rakotomalala, p.240\n",
+    "residus_ponderes = (round((D.values-dfe)/np.sqrt(dfe),2))\n",
+    "residus_ponderes.columns= D.columns\n",
+    "residus_ponderes.index=D.index\n",
+    "\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(5,2))         \n",
+    "# Sample figsize in inches\n",
+    "g = sns.heatmap(residus_ponderes, annot=residus_ponderes, cmap=\"coolwarm\", linewidths=.5, ax=ax)\n",
+    "labelsx = residus_ponderes.columns\n",
+    "labelsy = residus_ponderes.index\n",
+    "xt = g.set_xticklabels(labelsx, rotation=45, fontsize=8)\n",
+    "yt = g.set_yticklabels(labelsy, rotation=45, fontsize=8)\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e2be8d40",
+   "metadata": {},
+   "source": [
+    "#### Commentaire\n",
+    "\n",
+    "On observe une progression mais aussi une fluctuation avant 1951, puis un changement d'orientation qui sera à confirmer lorsque les données de la prochaine génération seront disponibles, ce qui n'est pas encore le cas.\n",
+    "\n",
+    "\n",
+    "Comme la variable 'gender' a deux modalités un seul facteur résumé la variance et une analyse factorielle n'est pas utile."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc339c76",
+   "metadata": {},
+   "source": [
+    "### Distributions des genres par origines"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 350,
+   "id": "6307b4e0",
+   "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>gender</th>\n",
+       "      <th>F</th>\n",
+       "      <th>M</th>\n",
+       "      <th>Total</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>origines_geog</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Afrique_subsaharienne</th>\n",
+       "      <td>7</td>\n",
+       "      <td>41</td>\n",
+       "      <td>48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Amérique_latine</th>\n",
+       "      <td>91</td>\n",
+       "      <td>329</td>\n",
+       "      <td>420</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Amérique_nord</th>\n",
+       "      <td>389</td>\n",
+       "      <td>3322</td>\n",
+       "      <td>3711</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_méridionale_Inde</th>\n",
+       "      <td>63</td>\n",
+       "      <td>554</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_orientale_Chine</th>\n",
+       "      <td>56</td>\n",
+       "      <td>1083</td>\n",
+       "      <td>1139</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Balkans</th>\n",
+       "      <td>35</td>\n",
+       "      <td>228</td>\n",
+       "      <td>263</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Espace_germanique</th>\n",
+       "      <td>180</td>\n",
+       "      <td>2869</td>\n",
+       "      <td>3049</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_centrale</th>\n",
+       "      <td>183</td>\n",
+       "      <td>1964</td>\n",
+       "      <td>2147</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_méridionale</th>\n",
+       "      <td>161</td>\n",
+       "      <td>1279</td>\n",
+       "      <td>1440</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>France_Benelux</th>\n",
+       "      <td>171</td>\n",
+       "      <td>1482</td>\n",
+       "      <td>1653</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Iles_britanniques</th>\n",
+       "      <td>108</td>\n",
+       "      <td>956</td>\n",
+       "      <td>1064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Moyen_Orient_Afrique_Nord</th>\n",
+       "      <td>39</td>\n",
+       "      <td>378</td>\n",
+       "      <td>417</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Russie</th>\n",
+       "      <td>124</td>\n",
+       "      <td>2174</td>\n",
+       "      <td>2298</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Scandinavie</th>\n",
+       "      <td>103</td>\n",
+       "      <td>984</td>\n",
+       "      <td>1087</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Total</th>\n",
+       "      <td>1710</td>\n",
+       "      <td>17643</td>\n",
+       "      <td>19353</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "gender                        F      M  Total\n",
+       "origines_geog                                \n",
+       "Afrique_subsaharienne         7     41     48\n",
+       "Amérique_latine              91    329    420\n",
+       "Amérique_nord               389   3322   3711\n",
+       "Asie_méridionale_Inde        63    554    617\n",
+       "Asie_orientale_Chine         56   1083   1139\n",
+       "Balkans                      35    228    263\n",
+       "Espace_germanique           180   2869   3049\n",
+       "Europe_centrale             183   1964   2147\n",
+       "Europe_méridionale          161   1279   1440\n",
+       "France_Benelux              171   1482   1653\n",
+       "Iles_britanniques           108    956   1064\n",
+       "Moyen_Orient_Afrique_Nord    39    378    417\n",
+       "Russie                      124   2174   2298\n",
+       "Scandinavie                 103    984   1087\n",
+       "Total                      1710  17643  19353"
+      ]
+     },
+     "execution_count": 350,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Tableau de contingence\n",
+    "X = \"gender\"\n",
+    "Y = \"origines_geog\"\n",
+    "\n",
+    "ddf = cdf_cont[[Y,X]].pivot_table(index=Y,columns=X,aggfunc=len,margins=True,margins_name=\"Total\").fillna(0).astype(int)\n",
+    "ddf"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c72a829b",
+   "metadata": {},
+   "source": [
+    "Si cette table de contingence concerne l'ensemble de la population, on utilise pour la suite la même population que pour l'analyse précédente, limitée donc dans le temps et sans le genre 'A'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 351,
+   "id": "78d13911",
+   "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>gender</th>\n",
+       "      <th>F</th>\n",
+       "      <th>M</th>\n",
+       "      <th>Total</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>origines_geog</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Afrique_subsaharienne</th>\n",
+       "      <td>7</td>\n",
+       "      <td>41</td>\n",
+       "      <td>48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Amérique_latine</th>\n",
+       "      <td>91</td>\n",
+       "      <td>329</td>\n",
+       "      <td>420</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Amérique_nord</th>\n",
+       "      <td>389</td>\n",
+       "      <td>3322</td>\n",
+       "      <td>3711</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_méridionale_Inde</th>\n",
+       "      <td>63</td>\n",
+       "      <td>554</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_orientale_Chine</th>\n",
+       "      <td>56</td>\n",
+       "      <td>1083</td>\n",
+       "      <td>1139</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Balkans</th>\n",
+       "      <td>35</td>\n",
+       "      <td>228</td>\n",
+       "      <td>263</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Espace_germanique</th>\n",
+       "      <td>180</td>\n",
+       "      <td>2869</td>\n",
+       "      <td>3049</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_centrale</th>\n",
+       "      <td>183</td>\n",
+       "      <td>1964</td>\n",
+       "      <td>2147</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_méridionale</th>\n",
+       "      <td>161</td>\n",
+       "      <td>1279</td>\n",
+       "      <td>1440</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>France_Benelux</th>\n",
+       "      <td>171</td>\n",
+       "      <td>1482</td>\n",
+       "      <td>1653</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Iles_britanniques</th>\n",
+       "      <td>108</td>\n",
+       "      <td>956</td>\n",
+       "      <td>1064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Moyen_Orient_Afrique_Nord</th>\n",
+       "      <td>39</td>\n",
+       "      <td>378</td>\n",
+       "      <td>417</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Russie</th>\n",
+       "      <td>124</td>\n",
+       "      <td>2174</td>\n",
+       "      <td>2298</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Scandinavie</th>\n",
+       "      <td>103</td>\n",
+       "      <td>984</td>\n",
+       "      <td>1087</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Total</th>\n",
+       "      <td>1710</td>\n",
+       "      <td>17643</td>\n",
+       "      <td>19353</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "gender                        F      M  Total\n",
+       "origines_geog                                \n",
+       "Afrique_subsaharienne         7     41     48\n",
+       "Amérique_latine              91    329    420\n",
+       "Amérique_nord               389   3322   3711\n",
+       "Asie_méridionale_Inde        63    554    617\n",
+       "Asie_orientale_Chine         56   1083   1139\n",
+       "Balkans                      35    228    263\n",
+       "Espace_germanique           180   2869   3049\n",
+       "Europe_centrale             183   1964   2147\n",
+       "Europe_méridionale          161   1279   1440\n",
+       "France_Benelux              171   1482   1653\n",
+       "Iles_britanniques           108    956   1064\n",
+       "Moyen_Orient_Afrique_Nord    39    378    417\n",
+       "Russie                      124   2174   2298\n",
+       "Scandinavie                 103    984   1087\n",
+       "Total                      1710  17643  19353"
+      ]
+     },
+     "execution_count": 351,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Tableau de contingence\n",
+    "X = \"gender\"\n",
+    "Y = \"origines_geog\"\n",
+    "\n",
+    "ddf = cdf_cont[[Y,X]].pivot_table(index=Y,columns=X,aggfunc=len,margins=True,margins_name=\"Total\").fillna(0).astype(int)\n",
+    "ddf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 352,
+   "id": "9d25b537",
+   "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>gender</th>\n",
+       "      <th>F</th>\n",
+       "      <th>M</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>origines_geog</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Afrique_subsaharienne</th>\n",
+       "      <td>7</td>\n",
+       "      <td>41</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Amérique_latine</th>\n",
+       "      <td>91</td>\n",
+       "      <td>329</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Amérique_nord</th>\n",
+       "      <td>389</td>\n",
+       "      <td>3322</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_méridionale_Inde</th>\n",
+       "      <td>63</td>\n",
+       "      <td>554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_orientale_Chine</th>\n",
+       "      <td>56</td>\n",
+       "      <td>1083</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Balkans</th>\n",
+       "      <td>35</td>\n",
+       "      <td>228</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Espace_germanique</th>\n",
+       "      <td>180</td>\n",
+       "      <td>2869</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_centrale</th>\n",
+       "      <td>183</td>\n",
+       "      <td>1964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_méridionale</th>\n",
+       "      <td>161</td>\n",
+       "      <td>1279</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>France_Benelux</th>\n",
+       "      <td>171</td>\n",
+       "      <td>1482</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Iles_britanniques</th>\n",
+       "      <td>108</td>\n",
+       "      <td>956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Moyen_Orient_Afrique_Nord</th>\n",
+       "      <td>39</td>\n",
+       "      <td>378</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Russie</th>\n",
+       "      <td>124</td>\n",
+       "      <td>2174</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Scandinavie</th>\n",
+       "      <td>103</td>\n",
+       "      <td>984</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "gender                       F     M\n",
+       "origines_geog                       \n",
+       "Afrique_subsaharienne        7    41\n",
+       "Amérique_latine             91   329\n",
+       "Amérique_nord              389  3322\n",
+       "Asie_méridionale_Inde       63   554\n",
+       "Asie_orientale_Chine        56  1083\n",
+       "Balkans                     35   228\n",
+       "Espace_germanique          180  2869\n",
+       "Europe_centrale            183  1964\n",
+       "Europe_méridionale         161  1279\n",
+       "France_Benelux             171  1482\n",
+       "Iles_britanniques          108   956\n",
+       "Moyen_Orient_Afrique_Nord   39   378\n",
+       "Russie                     124  2174\n",
+       "Scandinavie                103   984"
+      ]
+     },
+     "execution_count": 352,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Production du tableau à analyser\n",
+    "D = ddf.iloc[:-1,:-1].copy(deep=True)\n",
+    "D"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 353,
+   "id": "87a21982",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dimensions: ( 14 , 2 ), effectif: 19353 , nombre max. facteurs: 1\n"
+     ]
+    }
+   ],
+   "source": [
+    "## Nombre de modalités ligne\n",
+    "K = D.shape[0]\n",
+    "## Nombre de modalités colonnes\n",
+    "L = D.shape[1]\n",
+    "# Effectif total\n",
+    "n = np.sum(D.values)\n",
+    "# Nombre max. de facteur\n",
+    "Hmax = np.min([K-1,L-1])\n",
+    "\n",
+    "print('Dimensions: (', K, ',', L, '), effectif:', n, ', nombre max. facteurs:', Hmax)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 354,
+   "id": "c1264e68",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Chi2 : 214.03103881899477 , dof : 13\n",
+      "p-value : 1.7749063811497727e-38\n",
+      "phi2 = inertie (variance totale) : 0.011059320974473971\n",
+      "Cramer:  0.10516330621692137\n"
+     ]
+    }
+   ],
+   "source": [
+    "### Valeurs produites par la fonction de la librairie 'stats'\n",
+    "statistic, p, dof, expected = stats.chi2_contingency(D)\n",
+    "\n",
+    "print('Chi2 :', statistic, ', dof :',dof)\n",
+    "print('p-value :', p)\n",
+    "\n",
+    "\n",
+    "print('phi2 = inertie (variance totale) :', statistic/n)\n",
+    "\n",
+    "\n",
+    "### Tableau à l'indépendance\n",
+    "dfe = round(pd.DataFrame(expected),4)\n",
+    "\n",
+    "### Coéfficient de Cramer\n",
+    "# https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.contingency.association.html\n",
+    "\n",
+    "vc = stats.contingency.association(D, method='cramer')\n",
+    "print('Cramer: ', vc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 355,
+   "id": "7079ee7f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 200x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Résidus pondérés (avec le signe)\n",
+    "### Doc. :\n",
+    "#   Rakotomalala, p.240\n",
+    "residus_ponderes = (round((D.values-dfe)/np.sqrt(dfe),2))\n",
+    "residus_ponderes.columns= D.columns\n",
+    "residus_ponderes.index=D.index\n",
+    "\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(2,5))         \n",
+    "# Sample figsize in inches\n",
+    "g = sns.heatmap(residus_ponderes, annot=residus_ponderes, \n",
+    "                cmap=\"coolwarm\", linewidths=.5, ax=ax)\n",
+    "labelsx = residus_ponderes.columns\n",
+    "labelsy = residus_ponderes.index\n",
+    "xt = g.set_xticklabels(labelsx, rotation=0, fontsize=8)\n",
+    "yt = g.set_yticklabels(labelsy, rotation=10, fontsize=8)\n",
+    "\n",
+    "\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fff5f57b",
+   "metadata": {},
+   "source": [
+    "### Commentaire\n",
+    "\n",
+    "On observe une présence plus importante des femmes dans les pays qu'on pourrait globalement dire 'latins' ou méridionaux, avec l'exception de l'Amérique du nord"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f6eee928",
+   "metadata": {},
+   "source": [
+    "## Analyser le lien entre genre+période et l'aire géographique\n",
+    "\n",
+    "Cette analyse plus fine permet de comparer trois variable mais dans une logique bivariée"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 388,
+   "id": "d369f038",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 19353 entries, 0 to 23458\n",
+      "Data columns (total 8 columns):\n",
+      " #   Column            Non-Null Count  Dtype   \n",
+      "---  ------            --------------  -----   \n",
+      " 0   uri               19353 non-null  object  \n",
+      " 1   nom               19353 non-null  object  \n",
+      " 2   gender            19353 non-null  object  \n",
+      " 3   annee_nais        19353 non-null  int64   \n",
+      " 4   origines_geog     19353 non-null  object  \n",
+      " 5   periodes          19353 non-null  category\n",
+      " 6   period_25         19353 non-null  object  \n",
+      " 7   gender_period_25  19353 non-null  object  \n",
+      "dtypes: category(1), int64(1), object(6)\n",
+      "memory usage: 1.2+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "cdf_cont.period_25 = cdf_cont.period_25.astype(\"str\")\n",
+    "cdf_cont.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 389,
+   "id": "6010fd8d",
+   "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>uri</th>\n",
+       "      <th>nom</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>annee_nais</th>\n",
+       "      <th>origines_geog</th>\n",
+       "      <th>periodes</th>\n",
+       "      <th>period_25</th>\n",
+       "      <th>gender_period_25</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q1000193</td>\n",
+       "      <td>Hans Elsässer</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1929</td>\n",
+       "      <td>Espace_germanique</td>\n",
+       "      <td>1901-1950</td>\n",
+       "      <td>1926-1950</td>\n",
+       "      <td>1926-1950_M</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q1000934</td>\n",
+       "      <td>Charles Christian Lauritsen</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1892</td>\n",
+       "      <td>Amérique_nord</td>\n",
+       "      <td>1851-1900</td>\n",
+       "      <td>1876-1900</td>\n",
+       "      <td>1876-1900_M</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q100153910</td>\n",
+       "      <td>Frank J. Blatt</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>Espace_germanique</td>\n",
+       "      <td>1901-1950</td>\n",
+       "      <td>1901-1925</td>\n",
+       "      <td>1901-1925_M</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q100157315</td>\n",
+       "      <td>Ding Jing</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>Asie_orientale_Chine</td>\n",
+       "      <td>1901-1950</td>\n",
+       "      <td>1901-1925</td>\n",
+       "      <td>1901-1925_M</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>http://www.wikidata.org/entity/Q100212</td>\n",
+       "      <td>Peter Kramer</td>\n",
+       "      <td>M</td>\n",
+       "      <td>1933</td>\n",
+       "      <td>Espace_germanique</td>\n",
+       "      <td>1901-1950</td>\n",
+       "      <td>1926-1950</td>\n",
+       "      <td>1926-1950_M</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         uri                          nom  \\\n",
+       "0    http://www.wikidata.org/entity/Q1000193                Hans Elsässer   \n",
+       "1    http://www.wikidata.org/entity/Q1000934  Charles Christian Lauritsen   \n",
+       "2  http://www.wikidata.org/entity/Q100153910               Frank J. Blatt   \n",
+       "3  http://www.wikidata.org/entity/Q100157315                    Ding Jing   \n",
+       "4     http://www.wikidata.org/entity/Q100212                 Peter Kramer   \n",
+       "\n",
+       "  gender  annee_nais         origines_geog   periodes  period_25  \\\n",
+       "0      M        1929     Espace_germanique  1901-1950  1926-1950   \n",
+       "1      M        1892         Amérique_nord  1851-1900  1876-1900   \n",
+       "2      M        1924     Espace_germanique  1901-1950  1901-1925   \n",
+       "3      M        1924  Asie_orientale_Chine  1901-1950  1901-1925   \n",
+       "4      M        1933     Espace_germanique  1901-1950  1926-1950   \n",
+       "\n",
+       "  gender_period_25  \n",
+       "0      1926-1950_M  \n",
+       "1      1876-1900_M  \n",
+       "2      1901-1925_M  \n",
+       "3      1901-1925_M  \n",
+       "4      1926-1950_M  "
+      ]
+     },
+     "execution_count": 389,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cdf_cont['gender_period_25'] = cdf_cont.apply(lambda x: \\\n",
+    "                    x.period_25 + '_' + x.gender, axis=1)\n",
+    "cdf_cont.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 390,
+   "id": "a4d09d63",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "gender_period_25\n",
+       "1851-1875_F      53\n",
+       "1851-1875_M    1154\n",
+       "1876-1900_F     152\n",
+       "1876-1900_M    1723\n",
+       "1901-1925_F     294\n",
+       "1901-1925_M    3736\n",
+       "1926-1950_F     526\n",
+       "1926-1950_M    7118\n",
+       "1951-1975_F     685\n",
+       "1951-1975_M    3912\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 390,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cdf_cont.groupby(by='gender_period_25').size()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 391,
+   "id": "ca66de3e",
+   "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>gender_period_25</th>\n",
+       "      <th>1851-1875_F</th>\n",
+       "      <th>1851-1875_M</th>\n",
+       "      <th>1876-1900_F</th>\n",
+       "      <th>1876-1900_M</th>\n",
+       "      <th>1901-1925_F</th>\n",
+       "      <th>1901-1925_M</th>\n",
+       "      <th>1926-1950_F</th>\n",
+       "      <th>1926-1950_M</th>\n",
+       "      <th>1951-1975_F</th>\n",
+       "      <th>1951-1975_M</th>\n",
+       "      <th>Total</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>origines_geog</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Afrique_subsaharienne</th>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Amérique_latine</th>\n",
+       "      <td>0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>0</td>\n",
+       "      <td>20</td>\n",
+       "      <td>11</td>\n",
+       "      <td>61</td>\n",
+       "      <td>34</td>\n",
+       "      <td>149</td>\n",
+       "      <td>46</td>\n",
+       "      <td>85</td>\n",
+       "      <td>420</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Amérique_nord</th>\n",
+       "      <td>20</td>\n",
+       "      <td>161</td>\n",
+       "      <td>45</td>\n",
+       "      <td>268</td>\n",
+       "      <td>74</td>\n",
+       "      <td>914</td>\n",
+       "      <td>115</td>\n",
+       "      <td>1387</td>\n",
+       "      <td>135</td>\n",
+       "      <td>592</td>\n",
+       "      <td>3711</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_méridionale_Inde</th>\n",
+       "      <td>2</td>\n",
+       "      <td>23</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35</td>\n",
+       "      <td>10</td>\n",
+       "      <td>103</td>\n",
+       "      <td>18</td>\n",
+       "      <td>258</td>\n",
+       "      <td>32</td>\n",
+       "      <td>135</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_orientale_Chine</th>\n",
+       "      <td>0</td>\n",
+       "      <td>20</td>\n",
+       "      <td>0</td>\n",
+       "      <td>59</td>\n",
+       "      <td>14</td>\n",
+       "      <td>248</td>\n",
+       "      <td>18</td>\n",
+       "      <td>461</td>\n",
+       "      <td>24</td>\n",
+       "      <td>295</td>\n",
+       "      <td>1139</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Balkans</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>15</td>\n",
+       "      <td>15</td>\n",
+       "      <td>102</td>\n",
+       "      <td>18</td>\n",
+       "      <td>104</td>\n",
+       "      <td>263</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Espace_germanique</th>\n",
+       "      <td>3</td>\n",
+       "      <td>278</td>\n",
+       "      <td>29</td>\n",
+       "      <td>447</td>\n",
+       "      <td>33</td>\n",
+       "      <td>545</td>\n",
+       "      <td>34</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>81</td>\n",
+       "      <td>578</td>\n",
+       "      <td>3049</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_centrale</th>\n",
+       "      <td>3</td>\n",
+       "      <td>73</td>\n",
+       "      <td>12</td>\n",
+       "      <td>169</td>\n",
+       "      <td>27</td>\n",
+       "      <td>311</td>\n",
+       "      <td>90</td>\n",
+       "      <td>887</td>\n",
+       "      <td>51</td>\n",
+       "      <td>524</td>\n",
+       "      <td>2147</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_méridionale</th>\n",
+       "      <td>0</td>\n",
+       "      <td>105</td>\n",
+       "      <td>9</td>\n",
+       "      <td>117</td>\n",
+       "      <td>21</td>\n",
+       "      <td>179</td>\n",
+       "      <td>34</td>\n",
+       "      <td>414</td>\n",
+       "      <td>97</td>\n",
+       "      <td>464</td>\n",
+       "      <td>1440</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>France_Benelux</th>\n",
+       "      <td>2</td>\n",
+       "      <td>183</td>\n",
+       "      <td>21</td>\n",
+       "      <td>193</td>\n",
+       "      <td>20</td>\n",
+       "      <td>308</td>\n",
+       "      <td>50</td>\n",
+       "      <td>462</td>\n",
+       "      <td>78</td>\n",
+       "      <td>336</td>\n",
+       "      <td>1653</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Iles_britanniques</th>\n",
+       "      <td>13</td>\n",
+       "      <td>100</td>\n",
+       "      <td>9</td>\n",
+       "      <td>106</td>\n",
+       "      <td>26</td>\n",
+       "      <td>265</td>\n",
+       "      <td>29</td>\n",
+       "      <td>328</td>\n",
+       "      <td>31</td>\n",
+       "      <td>157</td>\n",
+       "      <td>1064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Moyen_Orient_Afrique_Nord</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>12</td>\n",
+       "      <td>6</td>\n",
+       "      <td>43</td>\n",
+       "      <td>14</td>\n",
+       "      <td>195</td>\n",
+       "      <td>18</td>\n",
+       "      <td>124</td>\n",
+       "      <td>417</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Russie</th>\n",
+       "      <td>4</td>\n",
+       "      <td>117</td>\n",
+       "      <td>20</td>\n",
+       "      <td>185</td>\n",
+       "      <td>33</td>\n",
+       "      <td>574</td>\n",
+       "      <td>44</td>\n",
+       "      <td>1031</td>\n",
+       "      <td>23</td>\n",
+       "      <td>267</td>\n",
+       "      <td>2298</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Scandinavie</th>\n",
+       "      <td>6</td>\n",
+       "      <td>68</td>\n",
+       "      <td>5</td>\n",
+       "      <td>103</td>\n",
+       "      <td>14</td>\n",
+       "      <td>159</td>\n",
+       "      <td>31</td>\n",
+       "      <td>407</td>\n",
+       "      <td>47</td>\n",
+       "      <td>247</td>\n",
+       "      <td>1087</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Total</th>\n",
+       "      <td>53</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>152</td>\n",
+       "      <td>1723</td>\n",
+       "      <td>294</td>\n",
+       "      <td>3736</td>\n",
+       "      <td>526</td>\n",
+       "      <td>7118</td>\n",
+       "      <td>685</td>\n",
+       "      <td>3912</td>\n",
+       "      <td>19353</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "gender_period_25           1851-1875_F  1851-1875_M  1876-1900_F  1876-1900_M  \\\n",
+       "origines_geog                                                                   \n",
+       "Afrique_subsaharienne                0            5            0            5   \n",
+       "Amérique_latine                      0           14            0           20   \n",
+       "Amérique_nord                       20          161           45          268   \n",
+       "Asie_méridionale_Inde                2           23            1           35   \n",
+       "Asie_orientale_Chine                 0           20            0           59   \n",
+       "Balkans                              0            3            0            4   \n",
+       "Espace_germanique                    3          278           29          447   \n",
+       "Europe_centrale                      3           73           12          169   \n",
+       "Europe_méridionale                   0          105            9          117   \n",
+       "France_Benelux                       2          183           21          193   \n",
+       "Iles_britanniques                   13          100            9          106   \n",
+       "Moyen_Orient_Afrique_Nord            0            4            1           12   \n",
+       "Russie                               4          117           20          185   \n",
+       "Scandinavie                          6           68            5          103   \n",
+       "Total                               53         1154          152         1723   \n",
+       "\n",
+       "gender_period_25           1901-1925_F  1901-1925_M  1926-1950_F  1926-1950_M  \\\n",
+       "origines_geog                                                                   \n",
+       "Afrique_subsaharienne                3           11            0           16   \n",
+       "Amérique_latine                     11           61           34          149   \n",
+       "Amérique_nord                       74          914          115         1387   \n",
+       "Asie_méridionale_Inde               10          103           18          258   \n",
+       "Asie_orientale_Chine                14          248           18          461   \n",
+       "Balkans                              2           15           15          102   \n",
+       "Espace_germanique                   33          545           34         1021   \n",
+       "Europe_centrale                     27          311           90          887   \n",
+       "Europe_méridionale                  21          179           34          414   \n",
+       "France_Benelux                      20          308           50          462   \n",
+       "Iles_britanniques                   26          265           29          328   \n",
+       "Moyen_Orient_Afrique_Nord            6           43           14          195   \n",
+       "Russie                              33          574           44         1031   \n",
+       "Scandinavie                         14          159           31          407   \n",
+       "Total                              294         3736          526         7118   \n",
+       "\n",
+       "gender_period_25           1951-1975_F  1951-1975_M  Total  \n",
+       "origines_geog                                               \n",
+       "Afrique_subsaharienne                4            4     48  \n",
+       "Amérique_latine                     46           85    420  \n",
+       "Amérique_nord                      135          592   3711  \n",
+       "Asie_méridionale_Inde               32          135    617  \n",
+       "Asie_orientale_Chine                24          295   1139  \n",
+       "Balkans                             18          104    263  \n",
+       "Espace_germanique                   81          578   3049  \n",
+       "Europe_centrale                     51          524   2147  \n",
+       "Europe_méridionale                  97          464   1440  \n",
+       "France_Benelux                      78          336   1653  \n",
+       "Iles_britanniques                   31          157   1064  \n",
+       "Moyen_Orient_Afrique_Nord           18          124    417  \n",
+       "Russie                              23          267   2298  \n",
+       "Scandinavie                         47          247   1087  \n",
+       "Total                              685         3912  19353  "
+      ]
+     },
+     "execution_count": 391,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Tableau de contingence\n",
+    "X = \"gender_period_25\"\n",
+    "Y = \"origines_geog\"\n",
+    "\n",
+    "ddf = cdf_cont[[Y,X]].pivot_table(index=Y,columns=X,aggfunc=len,margins=True,margins_name=\"Total\").fillna(0).astype(int)\n",
+    "ddf"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4f970b71",
+   "metadata": {},
+   "source": [
+    "NB : comme les Balkans, l'Afrique subsaharienne et le Moyen_Orient_Afrique_Nord ont des effectifs limités ils risquent de biaiser l'analyse. Nous ne les ajoutons pas aux données à analyser."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 394,
+   "id": "c14d51fe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### Liste construite manuellement à partir de cette liste\n",
+    "# print(ddf.index.to_list())\n",
+    "\n",
+    "li = ['Amérique_latine', 'Amérique_nord',\n",
+    "       'Asie_méridionale_Inde', 'Asie_orientale_Chine',\n",
+    "       'Espace_germanique', 'Europe_centrale', 'Europe_méridionale',\n",
+    "       'France_Benelux', 'Iles_britanniques',\n",
+    "       'Russie', 'Scandinavie']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 395,
+   "id": "15e8f143",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lc = ddf.columns.to_list()[:-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 400,
+   "id": "fbb66a8e",
+   "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>gender_period_25</th>\n",
+       "      <th>1851-1875_F</th>\n",
+       "      <th>1851-1875_M</th>\n",
+       "      <th>1876-1900_F</th>\n",
+       "      <th>1876-1900_M</th>\n",
+       "      <th>1901-1925_F</th>\n",
+       "      <th>1901-1925_M</th>\n",
+       "      <th>1926-1950_F</th>\n",
+       "      <th>1926-1950_M</th>\n",
+       "      <th>1951-1975_F</th>\n",
+       "      <th>1951-1975_M</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>origines_geog</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Amérique_latine</th>\n",
+       "      <td>0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>0</td>\n",
+       "      <td>20</td>\n",
+       "      <td>11</td>\n",
+       "      <td>61</td>\n",
+       "      <td>34</td>\n",
+       "      <td>149</td>\n",
+       "      <td>46</td>\n",
+       "      <td>85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Amérique_nord</th>\n",
+       "      <td>20</td>\n",
+       "      <td>161</td>\n",
+       "      <td>45</td>\n",
+       "      <td>268</td>\n",
+       "      <td>74</td>\n",
+       "      <td>914</td>\n",
+       "      <td>115</td>\n",
+       "      <td>1387</td>\n",
+       "      <td>135</td>\n",
+       "      <td>592</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_méridionale_Inde</th>\n",
+       "      <td>2</td>\n",
+       "      <td>23</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35</td>\n",
+       "      <td>10</td>\n",
+       "      <td>103</td>\n",
+       "      <td>18</td>\n",
+       "      <td>258</td>\n",
+       "      <td>32</td>\n",
+       "      <td>135</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Asie_orientale_Chine</th>\n",
+       "      <td>0</td>\n",
+       "      <td>20</td>\n",
+       "      <td>0</td>\n",
+       "      <td>59</td>\n",
+       "      <td>14</td>\n",
+       "      <td>248</td>\n",
+       "      <td>18</td>\n",
+       "      <td>461</td>\n",
+       "      <td>24</td>\n",
+       "      <td>295</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Espace_germanique</th>\n",
+       "      <td>3</td>\n",
+       "      <td>278</td>\n",
+       "      <td>29</td>\n",
+       "      <td>447</td>\n",
+       "      <td>33</td>\n",
+       "      <td>545</td>\n",
+       "      <td>34</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>81</td>\n",
+       "      <td>578</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_centrale</th>\n",
+       "      <td>3</td>\n",
+       "      <td>73</td>\n",
+       "      <td>12</td>\n",
+       "      <td>169</td>\n",
+       "      <td>27</td>\n",
+       "      <td>311</td>\n",
+       "      <td>90</td>\n",
+       "      <td>887</td>\n",
+       "      <td>51</td>\n",
+       "      <td>524</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Europe_méridionale</th>\n",
+       "      <td>0</td>\n",
+       "      <td>105</td>\n",
+       "      <td>9</td>\n",
+       "      <td>117</td>\n",
+       "      <td>21</td>\n",
+       "      <td>179</td>\n",
+       "      <td>34</td>\n",
+       "      <td>414</td>\n",
+       "      <td>97</td>\n",
+       "      <td>464</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>France_Benelux</th>\n",
+       "      <td>2</td>\n",
+       "      <td>183</td>\n",
+       "      <td>21</td>\n",
+       "      <td>193</td>\n",
+       "      <td>20</td>\n",
+       "      <td>308</td>\n",
+       "      <td>50</td>\n",
+       "      <td>462</td>\n",
+       "      <td>78</td>\n",
+       "      <td>336</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Iles_britanniques</th>\n",
+       "      <td>13</td>\n",
+       "      <td>100</td>\n",
+       "      <td>9</td>\n",
+       "      <td>106</td>\n",
+       "      <td>26</td>\n",
+       "      <td>265</td>\n",
+       "      <td>29</td>\n",
+       "      <td>328</td>\n",
+       "      <td>31</td>\n",
+       "      <td>157</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Russie</th>\n",
+       "      <td>4</td>\n",
+       "      <td>117</td>\n",
+       "      <td>20</td>\n",
+       "      <td>185</td>\n",
+       "      <td>33</td>\n",
+       "      <td>574</td>\n",
+       "      <td>44</td>\n",
+       "      <td>1031</td>\n",
+       "      <td>23</td>\n",
+       "      <td>267</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Scandinavie</th>\n",
+       "      <td>6</td>\n",
+       "      <td>68</td>\n",
+       "      <td>5</td>\n",
+       "      <td>103</td>\n",
+       "      <td>14</td>\n",
+       "      <td>159</td>\n",
+       "      <td>31</td>\n",
+       "      <td>407</td>\n",
+       "      <td>47</td>\n",
+       "      <td>247</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "gender_period_25       1851-1875_F  1851-1875_M  1876-1900_F  1876-1900_M  \\\n",
+       "origines_geog                                                               \n",
+       "Amérique_latine                  0           14            0           20   \n",
+       "Amérique_nord                   20          161           45          268   \n",
+       "Asie_méridionale_Inde            2           23            1           35   \n",
+       "Asie_orientale_Chine             0           20            0           59   \n",
+       "Espace_germanique                3          278           29          447   \n",
+       "Europe_centrale                  3           73           12          169   \n",
+       "Europe_méridionale               0          105            9          117   \n",
+       "France_Benelux                   2          183           21          193   \n",
+       "Iles_britanniques               13          100            9          106   \n",
+       "Russie                           4          117           20          185   \n",
+       "Scandinavie                      6           68            5          103   \n",
+       "\n",
+       "gender_period_25       1901-1925_F  1901-1925_M  1926-1950_F  1926-1950_M  \\\n",
+       "origines_geog                                                               \n",
+       "Amérique_latine                 11           61           34          149   \n",
+       "Amérique_nord                   74          914          115         1387   \n",
+       "Asie_méridionale_Inde           10          103           18          258   \n",
+       "Asie_orientale_Chine            14          248           18          461   \n",
+       "Espace_germanique               33          545           34         1021   \n",
+       "Europe_centrale                 27          311           90          887   \n",
+       "Europe_méridionale              21          179           34          414   \n",
+       "France_Benelux                  20          308           50          462   \n",
+       "Iles_britanniques               26          265           29          328   \n",
+       "Russie                          33          574           44         1031   \n",
+       "Scandinavie                     14          159           31          407   \n",
+       "\n",
+       "gender_period_25       1951-1975_F  1951-1975_M  \n",
+       "origines_geog                                    \n",
+       "Amérique_latine                 46           85  \n",
+       "Amérique_nord                  135          592  \n",
+       "Asie_méridionale_Inde           32          135  \n",
+       "Asie_orientale_Chine            24          295  \n",
+       "Espace_germanique               81          578  \n",
+       "Europe_centrale                 51          524  \n",
+       "Europe_méridionale              97          464  \n",
+       "France_Benelux                  78          336  \n",
+       "Iles_britanniques               31          157  \n",
+       "Russie                          23          267  \n",
+       "Scandinavie                     47          247  "
+      ]
+     },
+     "execution_count": 400,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "D = ddf.loc[li,lc].copy(deep=True)\n",
+    "D"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 401,
+   "id": "1ae0ef49",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dimensions: ( 11 , 10 ), effectif: 18625 , nombre max. facteurs: 9\n"
+     ]
+    }
+   ],
+   "source": [
+    "## Nombre de modalités ligne\n",
+    "K = D.shape[0]\n",
+    "## Nombre de modalités colonnes\n",
+    "L = D.shape[1]\n",
+    "# Effectif total\n",
+    "n = np.sum(D.values)\n",
+    "# Nombre max. de facteur\n",
+    "Hmax = np.min([K-1,L-1])\n",
+    "\n",
+    "print('Dimensions: (', K, ',', L, '), effectif:', n, ', nombre max. facteurs:', Hmax)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 402,
+   "id": "5bb430d3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Chi2 : 1430.4113356028033 , dof : 90\n",
+      "p-value : 3.872758730854973e-240\n",
+      "phi2 = inertie (variance totale) : 0.07680060862296931\n",
+      "Cramer:  0.09237640909944325\n"
+     ]
+    }
+   ],
+   "source": [
+    "### Valeurs produites par la fonction de la librairie 'stats'\n",
+    "statistic, p, dof, expected = stats.chi2_contingency(D)\n",
+    "\n",
+    "print('Chi2 :', statistic, ', dof :',dof)\n",
+    "print('p-value :', p)\n",
+    "\n",
+    "\n",
+    "print('phi2 = inertie (variance totale) :', statistic/n)\n",
+    "\n",
+    "\n",
+    "### Tableau à l'indépendance\n",
+    "dfe = round(pd.DataFrame(expected),4)\n",
+    "\n",
+    "### Coéfficient de Cramer\n",
+    "# https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.contingency.association.html\n",
+    "\n",
+    "vc = stats.contingency.association(D, method='cramer')\n",
+    "print('Cramer: ', vc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 403,
+   "id": "c9292bfe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Résidus pondérés (avec le signe)\n",
+    "### Doc. :\n",
+    "#   Rakotomalala, p.240\n",
+    "residus_ponderes = (round((D.values-dfe)/np.sqrt(dfe),2))\n",
+    "residus_ponderes.columns= D.columns\n",
+    "residus_ponderes.index=D.index\n",
+    "\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(10,8))         \n",
+    "# Sample figsize in inches\n",
+    "g = sns.heatmap(residus_ponderes, annot=residus_ponderes, \n",
+    "                cmap=\"coolwarm\", linewidths=.5, ax=ax)\n",
+    "labelsx = residus_ponderes.columns\n",
+    "labelsy = residus_ponderes.index\n",
+    "xt = g.set_xticklabels(labelsx, rotation=20, fontsize=8)\n",
+    "yt = g.set_yticklabels(labelsy, rotation=0, fontsize=8)\n",
+    "\n",
+    "\n",
+    "g.set_title('Diagramme des résidus pondérés')\n",
+    "\n",
+    "plt.savefig('images/genre_periode_aire_resid_ponderes.jpg', bbox_inches='tight')\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 404,
+   "id": "bc9d46e0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-10 {color: black;}#sk-container-id-10 pre{padding: 0;}#sk-container-id-10 div.sk-toggleable {background-color: white;}#sk-container-id-10 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-10 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-10 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-10 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-10 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-10 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-10 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-10 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-10 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-10 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-10 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-10 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-10 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-10 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-10 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-10 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-10 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-10 div.sk-item {position: relative;z-index: 1;}#sk-container-id-10 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-10 div.sk-item::before, #sk-container-id-10 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-10 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-10 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-10 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-10 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-10 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-10 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-10 div.sk-label-container {text-align: center;}#sk-container-id-10 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-10 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-10\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>CA(col_labels=Index([&#x27;1851-1875_F&#x27;, &#x27;1851-1875_M&#x27;, &#x27;1876-1900_F&#x27;, &#x27;1876-1900_M&#x27;,\n",
+       "       &#x27;1901-1925_F&#x27;, &#x27;1901-1925_M&#x27;, &#x27;1926-1950_F&#x27;, &#x27;1926-1950_M&#x27;,\n",
+       "       &#x27;1951-1975_F&#x27;, &#x27;1951-1975_M&#x27;],\n",
+       "      dtype=&#x27;object&#x27;, name=&#x27;gender_period_25&#x27;),\n",
+       "   row_labels=Index([&#x27;Amérique_latine&#x27;, &#x27;Amérique_nord&#x27;, &#x27;Asie_méridionale_Inde&#x27;,\n",
+       "       &#x27;Asie_orientale_Chine&#x27;, &#x27;Espace_germanique&#x27;, &#x27;Europe_centrale&#x27;,\n",
+       "       &#x27;Europe_méridionale&#x27;, &#x27;France_Benelux&#x27;, &#x27;Iles_britanniques&#x27;, &#x27;Russie&#x27;,\n",
+       "       &#x27;Scandinavie&#x27;],\n",
+       "      dtype=&#x27;object&#x27;, name=&#x27;origines_geog&#x27;))</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-10\" type=\"checkbox\" checked><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">CA</label><div class=\"sk-toggleable__content\"><pre>CA(col_labels=Index([&#x27;1851-1875_F&#x27;, &#x27;1851-1875_M&#x27;, &#x27;1876-1900_F&#x27;, &#x27;1876-1900_M&#x27;,\n",
+       "       &#x27;1901-1925_F&#x27;, &#x27;1901-1925_M&#x27;, &#x27;1926-1950_F&#x27;, &#x27;1926-1950_M&#x27;,\n",
+       "       &#x27;1951-1975_F&#x27;, &#x27;1951-1975_M&#x27;],\n",
+       "      dtype=&#x27;object&#x27;, name=&#x27;gender_period_25&#x27;),\n",
+       "   row_labels=Index([&#x27;Amérique_latine&#x27;, &#x27;Amérique_nord&#x27;, &#x27;Asie_méridionale_Inde&#x27;,\n",
+       "       &#x27;Asie_orientale_Chine&#x27;, &#x27;Espace_germanique&#x27;, &#x27;Europe_centrale&#x27;,\n",
+       "       &#x27;Europe_méridionale&#x27;, &#x27;France_Benelux&#x27;, &#x27;Iles_britanniques&#x27;, &#x27;Russie&#x27;,\n",
+       "       &#x27;Scandinavie&#x27;],\n",
+       "      dtype=&#x27;object&#x27;, name=&#x27;origines_geog&#x27;))</pre></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "CA(col_labels=Index(['1851-1875_F', '1851-1875_M', '1876-1900_F', '1876-1900_M',\n",
+       "       '1901-1925_F', '1901-1925_M', '1926-1950_F', '1926-1950_M',\n",
+       "       '1951-1975_F', '1951-1975_M'],\n",
+       "      dtype='object', name='gender_period_25'),\n",
+       "   row_labels=Index(['Amérique_latine', 'Amérique_nord', 'Asie_méridionale_Inde',\n",
+       "       'Asie_orientale_Chine', 'Espace_germanique', 'Europe_centrale',\n",
+       "       'Europe_méridionale', 'France_Benelux', 'Iles_britanniques', 'Russie',\n",
+       "       'Scandinavie'],\n",
+       "      dtype='object', name='origines_geog'))"
+      ]
+     },
+     "execution_count": 404,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "afc = CA(row_labels=D.index,col_labels=D.columns)\n",
+    "afc.fit(D.values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 405,
+   "id": "3f3658a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x300 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "eig = pd.DataFrame(afc.eig_)\n",
+    "\n",
+    "r1 = round(eig.iloc[0], 3)\n",
+    "r2 = round(eig.iloc[2], 2)\n",
+    "s=list(range(1,len(r1)+1))\n",
+    "r1.index=s\n",
+    "r2.index=s\n",
+    "\n",
+    "# https://www.statology.org/pandas-subplots/\n",
+    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(12,3))\n",
+    "\n",
+    "ax1 = r1.plot(kind='bar', ax=axes[0], title='Eigenvalue des axes')\n",
+    "ax2 = r2.plot(kind='bar', ax=axes[1], title=\"Frequence cumulative de l'eigenvalue \")\n",
+    "\n",
+    "\n",
+    "ax1.bar_label(ax1.containers[0])\n",
+    "ax2.bar_label(ax2.containers[0])\n",
+    "\n",
+    "\n",
+    "# Met les valeurs xticks en vertical\n",
+    "fig.autofmt_xdate(rotation=0)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "147d5566",
+   "metadata": {},
+   "source": [
+    "### Graphiques et interprétation du premier plan factoriel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 406,
+   "id": "62aa8ab1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Informations sur les contributions des colonnes\n",
+    "df = afc.col_topandas()[['col_contrib_dim1',\n",
+    "                         'col_contrib_dim2',\n",
+    "                         'col_contrib_dim3']]\n",
+    "\n",
+    "r1 = df.iloc[:,0]\n",
+    "r2 = df.iloc[:,1]\n",
+    "r3 = df.iloc[:,2]\n",
+    "\n",
+    "fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(12,6),\n",
+    "                          gridspec_kw={'height_ratios': [1, 2]})\n",
+    "\n",
+    "r1.sort_values().plot(kind='barh', ax=axes[0,0], title='Dim.1')\n",
+    "r2.sort_values().plot(kind='barh', ax=axes[0,1], title='Dim.2')\n",
+    "r3.sort_values().plot(kind='barh', ax=axes[0,2], title='Dim.3')\n",
+    "\n",
+    "### Rows\n",
+    "df = afc.row_topandas()[['row_contrib_dim1',\n",
+    "                         'row_contrib_dim2',\n",
+    "                         'row_contrib_dim3']]\n",
+    "r1 = df.iloc[:,0]\n",
+    "r2 = df.iloc[:,1]\n",
+    "r3 = df.iloc[:,2]\n",
+    "\n",
+    "r1.sort_values().plot(kind='barh', ax=axes[1,0], title='Dim.1')\n",
+    "r2.sort_values().plot(kind='barh', ax=axes[1,1], title='Dim.2')\n",
+    "r3.sort_values().plot(kind='barh', ax=axes[1,2], title='Dim.3')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 408,
+   "id": "1964a0e5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Représentation simultanée, avec amplification\n",
+    "afc.mapping(num_x_axis=1,num_y_axis=2,figsize=(10,10))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "db3d83da",
+   "metadata": {},
+   "source": [
+    "### Représenter l'autre plan factoriel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 409,
+   "id": "d36133f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Informations sur les cosinus carrés. Ces valeurs expriment \n",
+    "# la qualité de représentation d'une modalité sur l'axe correspondant\n",
+    "\n",
+    "### Colonnes\n",
+    "df = afc.col_topandas()[['col_cos2_dim1',\n",
+    "                         'col_cos2_dim2',\n",
+    "                         'col_cos2_dim3']]\n",
+    "\n",
+    "r1 = df.iloc[:,0]\n",
+    "r2 = df.iloc[:,1]\n",
+    "r3 = df.iloc[:,2]\n",
+    "\n",
+    "fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(12,6), \n",
+    "                         gridspec_kw={'height_ratios': [1, 2]})\n",
+    "\n",
+    "r1.sort_values().plot(kind='barh', ax=axes[0,0], title='Dim.1')\n",
+    "r2.sort_values().plot(kind='barh', ax=axes[0,1], title='Dim.2')\n",
+    "r3.sort_values().plot(kind='barh', ax=axes[0,2], title='Dim.3')\n",
+    "\n",
+    "### Lignes\n",
+    "df = afc.row_topandas()[['row_cos2_dim1',\n",
+    "                         'row_cos2_dim2',\n",
+    "                         'row_cos2_dim3']]\n",
+    "r1 = df.iloc[:,0]\n",
+    "r2 = df.iloc[:,1]\n",
+    "r3 = df.iloc[:,2]\n",
+    "\n",
+    "r1.sort_values().plot(kind='barh', ax=axes[1,0], title='Dim.1')\n",
+    "r2.sort_values().plot(kind='barh', ax=axes[1,1], title='Dim.2')\n",
+    "r3.sort_values().plot(kind='barh', ax=axes[1,2], title='Dim.3')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 410,
+   "id": "f5f50e9b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Représentation simultanée, avec amplification\n",
+    "afc.mapping(num_x_axis=2,num_y_axis=3,figsize=(10,10))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3baa677d",
+   "metadata": {},
+   "source": [
+    "### Commentaire\n",
+    "\n",
+    "Cette analyse factorielle met en évidence, en relation avec le diagramme des résidus pondérés qui permet de la contrôler, les moments de présence féminine significative dans les générations présentes dans les  différentes régions géoraphiques"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "py310_fanalysis",
+   "language": "python",
+   "name": "py310_fanalysis"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks_jupyter/wikidata_exploration/wdt_nationalite_analyse.ipynb b/notebooks_jupyter/wikidata_exploration/wdt_nationalite_analyse.ipynb
index 3a35492..5578007 100644
--- a/notebooks_jupyter/wikidata_exploration/wdt_nationalite_analyse.ipynb
+++ b/notebooks_jupyter/wikidata_exploration/wdt_nationalite_analyse.ipynb
@@ -76,7 +76,7 @@
     {
      "data": {
       "text/plain": [
-       "<sqlite3.Connection at 0x7f06552bfa40>"
+       "<sqlite3.Connection at 0x7fb57f647a40>"
       ]
      },
      "execution_count": 4,
@@ -238,32 +238,6 @@
     "df_orig.groupby(by='origines_geog').size().sort_values(ascending=False)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "d9ce9030",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "gender\n",
-       "M    21392\n",
-       "F     2055\n",
-       "A       12\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "### Distribution des genres\n",
-    "df_orig.groupby(by='gender').size().sort_values(ascending=False)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "9ed6f1c4",
@@ -274,7 +248,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "id": "e13186ea",
    "metadata": {},
    "outputs": [],
@@ -286,7 +260,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "id": "cec8612e",
    "metadata": {},
    "outputs": [
@@ -359,7 +333,7 @@
        "2      M        1924  Espace_germanique  "
       ]
      },
-     "execution_count": 11,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -372,7 +346,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "id": "b9b36a35",
    "metadata": {},
    "outputs": [
@@ -382,7 +356,7 @@
        "(1360, 1980)"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -394,7 +368,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "id": "22968555",
    "metadata": {},
    "outputs": [
@@ -404,7 +378,7 @@
        "([1351, 1401, 1451, 1501, 1551], [1801, 1851, 1901, 1951, 2001])"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -419,7 +393,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "id": "ac6dbfe7",
    "metadata": {},
    "outputs": [
@@ -496,7 +470,7 @@
        "2      M        1924  Espace_germanique  1901-1950  "
       ]
      },
-     "execution_count": 14,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -518,7 +492,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 14,
    "id": "ddce276a",
    "metadata": {},
    "outputs": [
@@ -542,7 +516,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -554,7 +528,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "id": "05d5cea7",
    "metadata": {},
    "outputs": [
@@ -587,7 +561,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "id": "ea2c1f99",
    "metadata": {},
    "outputs": [
@@ -611,7 +585,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -623,7 +597,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "id": "7a4e05b3",
    "metadata": {},
    "outputs": [
@@ -648,7 +622,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -668,7 +642,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "id": "c69696e5",
    "metadata": {},
    "outputs": [
@@ -699,7 +673,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 19,
    "id": "477a5ed0",
    "metadata": {},
    "outputs": [
@@ -738,7 +712,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "id": "cd4b9b33",
    "metadata": {},
    "outputs": [
@@ -1028,7 +1002,7 @@
        "Total                            523   1667  "
       ]
      },
-     "execution_count": 21,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1056,7 +1030,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "id": "61486cb0",
    "metadata": {},
    "outputs": [
@@ -1173,7 +1147,7 @@
        "Iles_britanniques          72        104  "
       ]
      },
-     "execution_count": 22,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1186,7 +1160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 22,
    "id": "3a376dc6",
    "metadata": {},
    "outputs": [
@@ -1213,7 +1187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 23,
    "id": "f35e0906",
    "metadata": {},
    "outputs": [
@@ -1224,7 +1198,7 @@
       "Chi2 : 102.73611721718783 , dof : 24\n",
       "p-value : 1.0221260332124025e-11\n",
       "phi2 = inertie (variance totale) : 0.07559684857776881\n",
-      "Cramer:  0.1598045484761636\n"
+      "Cramer:  0.1374744054158526\n"
      ]
     }
    ],
@@ -1245,7 +1219,7 @@
     "### Coéfficient de Cramer\n",
     "# https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.contingency.association.html\n",
     "\n",
-    "vc = stats.contingency.association(D.iloc[:-1,:-1], method='cramer')\n",
+    "vc = stats.contingency.association(D, method='cramer')\n",
     "print('Cramer: ', vc)"
    ]
   },
@@ -1263,7 +1237,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 24,
    "id": "3158bc79",
    "metadata": {},
    "outputs": [
@@ -1291,7 +1265,7 @@
        "      dtype='object', name='origines_geog'))"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1303,7 +1277,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 25,
    "id": "e90ac2c9",
    "metadata": {},
    "outputs": [
@@ -1362,7 +1336,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 26,
    "id": "71795d2e",
    "metadata": {},
    "outputs": [
@@ -1400,7 +1374,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 27,
    "id": "7c740a71",
    "metadata": {},
    "outputs": [
@@ -1449,7 +1423,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 28,
    "id": "08327520",
    "metadata": {},
    "outputs": [
@@ -1479,7 +1453,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 29,
    "id": "75e10095",
    "metadata": {},
    "outputs": [
@@ -1531,7 +1505,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 30,
    "id": "47e50689",
    "metadata": {},
    "outputs": [
@@ -1553,7 +1527,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 31,
    "id": "e4fb2136",
    "metadata": {},
    "outputs": [
@@ -1670,7 +1644,7 @@
        "Iles_britanniques          72        104  "
       ]
      },
-     "execution_count": 32,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1697,7 +1671,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 32,
    "id": "1be3470a",
    "metadata": {},
    "outputs": [
@@ -1882,7 +1856,7 @@
        "Total                           1253       3123      11676       5005  21057"
       ]
      },
-     "execution_count": 50,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1914,7 +1888,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 33,
    "id": "c5eee98a",
    "metadata": {},
    "outputs": [
@@ -2066,7 +2040,7 @@
        "Scandinavie                       75        185        611        322"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2079,7 +2053,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 34,
    "id": "8b105e03",
    "metadata": {},
    "outputs": [
@@ -2103,7 +2077,7 @@
        " 'Total']"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2114,7 +2088,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 35,
    "id": "5f3f4422",
    "metadata": {},
    "outputs": [],
@@ -2128,7 +2102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 36,
    "id": "4c95f8cf",
    "metadata": {},
    "outputs": [],
@@ -2138,7 +2112,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 37,
    "id": "e78f60e1",
    "metadata": {},
    "outputs": [
@@ -2274,7 +2248,7 @@
        "Scandinavie                   75        185        611        322"
       ]
      },
-     "execution_count": 60,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2285,145 +2259,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 38,
    "id": "2aedec8f",
    "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>periodes</th>\n",
-       "      <th>1801-1850</th>\n",
-       "      <th>1851-1900</th>\n",
-       "      <th>1901-1950</th>\n",
-       "      <th>1951-2000</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>origines_geog</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>Amérique_latine</th>\n",
-       "      <td>8</td>\n",
-       "      <td>34</td>\n",
-       "      <td>255</td>\n",
-       "      <td>143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Amérique_nord</th>\n",
-       "      <td>139</td>\n",
-       "      <td>500</td>\n",
-       "      <td>2490</td>\n",
-       "      <td>770</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Asie_méridionale_Inde</th>\n",
-       "      <td>11</td>\n",
-       "      <td>61</td>\n",
-       "      <td>390</td>\n",
-       "      <td>177</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Asie_orientale_Chine</th>\n",
-       "      <td>8</td>\n",
-       "      <td>80</td>\n",
-       "      <td>741</td>\n",
-       "      <td>329</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Espace_germanique</th>\n",
-       "      <td>312</td>\n",
-       "      <td>762</td>\n",
-       "      <td>1634</td>\n",
-       "      <td>709</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Europe_centrale</th>\n",
-       "      <td>49</td>\n",
-       "      <td>261</td>\n",
-       "      <td>1315</td>\n",
-       "      <td>634</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Europe_méridionale</th>\n",
-       "      <td>131</td>\n",
-       "      <td>235</td>\n",
-       "      <td>648</td>\n",
-       "      <td>649</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>France_Benelux</th>\n",
-       "      <td>217</td>\n",
-       "      <td>408</td>\n",
-       "      <td>840</td>\n",
-       "      <td>446</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Iles_britanniques</th>\n",
-       "      <td>190</td>\n",
-       "      <td>236</td>\n",
-       "      <td>648</td>\n",
-       "      <td>200</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Russie</th>\n",
-       "      <td>105</td>\n",
-       "      <td>327</td>\n",
-       "      <td>1682</td>\n",
-       "      <td>310</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Scandinavie</th>\n",
-       "      <td>75</td>\n",
-       "      <td>185</td>\n",
-       "      <td>611</td>\n",
-       "      <td>322</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "periodes               1801-1850  1851-1900  1901-1950  1951-2000\n",
-       "origines_geog                                                    \n",
-       "Amérique_latine                8         34        255        143\n",
-       "Amérique_nord                139        500       2490        770\n",
-       "Asie_méridionale_Inde         11         61        390        177\n",
-       "Asie_orientale_Chine           8         80        741        329\n",
-       "Espace_germanique            312        762       1634        709\n",
-       "Europe_centrale               49        261       1315        634\n",
-       "Europe_méridionale           131        235        648        649\n",
-       "France_Benelux               217        408        840        446\n",
-       "Iles_britanniques            190        236        648        200\n",
-       "Russie                       105        327       1682        310\n",
-       "Scandinavie                   75        185        611        322"
-      ]
-     },
-     "execution_count": 62,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "NameError",
+     "evalue": "name 'll' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[38], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m### Production du tableau à analyser\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m D \u001b[38;5;241m=\u001b[39m ddf\u001b[38;5;241m.\u001b[39mloc[\u001b[43mll\u001b[49m,lc]\u001b[38;5;241m.\u001b[39mcopy(deep\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m      3\u001b[0m D\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'll' is not defined"
+     ]
     }
    ],
    "source": [
@@ -2434,7 +2283,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": null,
    "id": "977f1f4a",
    "metadata": {},
    "outputs": [
@@ -2461,7 +2310,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": null,
    "id": "57add623",
    "metadata": {},
    "outputs": [
@@ -2472,7 +2321,7 @@
       "Chi2 : 1545.0591441905447 , dof : 30\n",
       "p-value : 9.84022478336198e-307\n",
       "phi2 = inertie (variance totale) : 0.07619762017017037\n",
-      "Cramer:  0.18405803379765892\n"
+      "Cramer:  0.15937128575559062\n"
      ]
     }
    ],
@@ -2493,7 +2342,7 @@
     "### Coéfficient de Cramer\n",
     "# https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.contingency.association.html\n",
     "\n",
-    "vc = stats.contingency.association(D.iloc[:-1,:-1], method='cramer')\n",
+    "vc = stats.contingency.association(D, method='cramer')\n",
     "print('Cramer: ', vc)"
    ]
   },
@@ -2511,7 +2360,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": null,
    "id": "a41f9cde",
    "metadata": {},
    "outputs": [
@@ -2551,7 +2400,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": null,
    "id": "2a605cc2",
    "metadata": {},
    "outputs": [
@@ -2610,7 +2459,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": null,
    "id": "70221995",
    "metadata": {},
    "outputs": [
@@ -2648,7 +2497,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": null,
    "id": "e1b6236f",
    "metadata": {},
    "outputs": [
@@ -2698,7 +2547,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": null,
    "id": "0a5ccc8e",
    "metadata": {},
    "outputs": [
@@ -2728,7 +2577,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": null,
    "id": "f710efd7",
    "metadata": {},
    "outputs": [
@@ -2781,7 +2630,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": null,
    "id": "c0e729a2",
    "metadata": {},
    "outputs": [
@@ -2803,7 +2652,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": null,
    "id": "b81b7d4b",
    "metadata": {},
    "outputs": [
diff --git a/notebooks_jupyter/wikidata_exploration/wdt_occupations_analyse.ipynb b/notebooks_jupyter/wikidata_exploration/wdt_occupations_analyse.ipynb
index c7dfff3..4741ad6 100644
--- a/notebooks_jupyter/wikidata_exploration/wdt_occupations_analyse.ipynb
+++ b/notebooks_jupyter/wikidata_exploration/wdt_occupations_analyse.ipynb
@@ -7,7 +7,7 @@
    "source": [
     "# Analyse des occupations et leur évolution dans le temps \n",
     "\n",
-    "Dans ce carnet est proposée...\n",
+    "Dans ce carnet est première approche\n",
     "\n",
     "On met aussi en évidence l'évolution dans le temps ..."
    ]