Heart_attack_prediction (1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from pandas import Series,DataFrame\n",
    "from numpy.random import randn\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "heartattack_df = pd.read_csv(\"heartdata.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>120.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>170.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>100.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps   chol  fbs  restecg  thalach  exang  oldpeak  \\\n",
       "0   28    1   2     130.0  132.0  0.0      2.0    185.0    0.0      0.0   \n",
       "1   29    1   2     120.0  243.0  0.0      0.0    160.0    0.0      0.0   \n",
       "2   29    1   2     140.0    NaN  0.0      0.0    170.0    0.0      0.0   \n",
       "3   30    0   1     170.0  237.0  0.0      1.0    170.0    0.0      0.0   \n",
       "4   31    0   2     100.0  219.0  0.0      1.0    150.0    0.0      0.0   \n",
       "\n",
       "   slope  ca  thal  num         \n",
       "0    NaN NaN   NaN           0  \n",
       "1    NaN NaN   NaN           0  \n",
       "2    NaN NaN   NaN           0  \n",
       "3    NaN NaN   6.0           0  \n",
       "4    NaN NaN   NaN           0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heartattack_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 294 entries, 0 to 293\n",
      "Data columns (total 14 columns):\n",
      "age           294 non-null int64\n",
      "sex           294 non-null int64\n",
      "cp            294 non-null int64\n",
      "trestbps      293 non-null float64\n",
      "chol          271 non-null float64\n",
      "fbs           286 non-null float64\n",
      "restecg       293 non-null float64\n",
      "thalach       293 non-null float64\n",
      "exang         293 non-null float64\n",
      "oldpeak       294 non-null float64\n",
      "slope         104 non-null float64\n",
      "ca            3 non-null float64\n",
      "thal          28 non-null float64\n",
      "num           294 non-null int64\n",
      "dtypes: float64(10), int64(4)\n",
      "memory usage: 32.2 KB\n"
     ]
    }
   ],
   "source": [
    "heartattack_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "heartattack_df = heartattack_df.drop(columns='slope')\n",
    "heartattack_df = heartattack_df.drop(columns=\"ca\")\n",
    "heartattack_df = heartattack_df.drop(columns=\"thal\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>120.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>170.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>100.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps   chol  fbs  restecg  thalach  exang  oldpeak  \\\n",
       "0   28    1   2     130.0  132.0  0.0      2.0    185.0    0.0      0.0   \n",
       "1   29    1   2     120.0  243.0  0.0      0.0    160.0    0.0      0.0   \n",
       "2   29    1   2     140.0    NaN  0.0      0.0    170.0    0.0      0.0   \n",
       "3   30    0   1     170.0  237.0  0.0      1.0    170.0    0.0      0.0   \n",
       "4   31    0   2     100.0  219.0  0.0      1.0    150.0    0.0      0.0   \n",
       "\n",
       "   num         \n",
       "0           0  \n",
       "1           0  \n",
       "2           0  \n",
       "3           0  \n",
       "4           0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heartattack_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def male_female(pateints):\n",
    "    sex=pateints\n",
    "    if sex == 1:\n",
    "        return \"Male\"\n",
    "    else:\n",
    "        return \"Female\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>120.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>170.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>100.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>105.0</td>\n",
       "      <td>198.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>110.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>184.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>125.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>120.0</td>\n",
       "      <td>298.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>150.0</td>\n",
       "      <td>214.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    age  sex  cp  trestbps   chol  fbs  restecg  thalach  exang  oldpeak  \\\n",
       "0    28    1   2     130.0  132.0  0.0      2.0    185.0    0.0      0.0   \n",
       "1    29    1   2     120.0  243.0  0.0      0.0    160.0    0.0      0.0   \n",
       "2    29    1   2     140.0    NaN  0.0      0.0    170.0    0.0      0.0   \n",
       "3    30    0   1     170.0  237.0  0.0      1.0    170.0    0.0      0.0   \n",
       "4    31    0   2     100.0  219.0  0.0      1.0    150.0    0.0      0.0   \n",
       "5    32    0   2     105.0  198.0  0.0      0.0    165.0    0.0      0.0   \n",
       "6    32    1   2     110.0  225.0  0.0      0.0    184.0    0.0      0.0   \n",
       "7    32    1   2     125.0  254.0  0.0      0.0    155.0    0.0      0.0   \n",
       "8    33    1   3     120.0  298.0  0.0      0.0    185.0    0.0      0.0   \n",
       "9    34    0   2     130.0  161.0  0.0      0.0    190.0    0.0      0.0   \n",
       "10   34    1   2     150.0  214.0  0.0      1.0    168.0    0.0      0.0   \n",
       "\n",
       "    num         \n",
       "0            0  \n",
       "1            0  \n",
       "2            0  \n",
       "3            0  \n",
       "4            0  \n",
       "5            0  \n",
       "6            0  \n",
       "7            0  \n",
       "8            0  \n",
       "9            0  \n",
       "10           0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heartattack_df[0:11]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "heartattack_df['Gender'] = heartattack_df['sex'].apply(male_female)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>num</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>120.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>170.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>100.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>105.0</td>\n",
       "      <td>198.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>110.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>184.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>125.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>120.0</td>\n",
       "      <td>298.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>150.0</td>\n",
       "      <td>214.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    age  sex  cp  trestbps   chol  fbs  restecg  thalach  exang  oldpeak  \\\n",
       "0    28    1   2     130.0  132.0  0.0      2.0    185.0    0.0      0.0   \n",
       "1    29    1   2     120.0  243.0  0.0      0.0    160.0    0.0      0.0   \n",
       "2    29    1   2     140.0    NaN  0.0      0.0    170.0    0.0      0.0   \n",
       "3    30    0   1     170.0  237.0  0.0      1.0    170.0    0.0      0.0   \n",
       "4    31    0   2     100.0  219.0  0.0      1.0    150.0    0.0      0.0   \n",
       "5    32    0   2     105.0  198.0  0.0      0.0    165.0    0.0      0.0   \n",
       "6    32    1   2     110.0  225.0  0.0      0.0    184.0    0.0      0.0   \n",
       "7    32    1   2     125.0  254.0  0.0      0.0    155.0    0.0      0.0   \n",
       "8    33    1   3     120.0  298.0  0.0      0.0    185.0    0.0      0.0   \n",
       "9    34    0   2     130.0  161.0  0.0      0.0    190.0    0.0      0.0   \n",
       "10   34    1   2     150.0  214.0  0.0      1.0    168.0    0.0      0.0   \n",
       "\n",
       "    num         Gender  \n",
       "0            0    Male  \n",
       "1            0    Male  \n",
       "2            0    Male  \n",
       "3            0  Female  \n",
       "4            0  Female  \n",
       "5            0  Female  \n",
       "6            0    Male  \n",
       "7            0    Male  \n",
       "8            0    Male  \n",
       "9            0  Female  \n",
       "10           0    Male  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heartattack_df[0:11]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "hrt1 = heartattack_df['chol'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    132.0\n",
       "1    243.0\n",
       "3    237.0\n",
       "4    219.0\n",
       "5    198.0\n",
       "Name: chol, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hrt1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x15ce4e53668>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#cholestrol level of every age group\n",
    "sns.lmplot('age','chol',heartattack_df,palette=\"bright\",aspect=2,order=5,\n",
    "          scatter_kws={'marker':'o','color':'yellow'},\n",
    "          line_kws={'linewidth':1,'color':'orange'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x15ce4e8c048>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#percentage of people consulting doctors for heart disease categorised on the basis of age\n",
    "sns.catplot('age',data=heartattack_df,kind=\"count\",aspect=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def chestpain_type(value):\n",
    "    cp = value\n",
    "    if cp == 1:\n",
    "        return \"Typical Angina\"\n",
    "    elif cp == 2:\n",
    "        return \"Atypical Angina\"\n",
    "    elif cp == 3:\n",
    "        return \"Non-anginal Pain\"\n",
    "    else:\n",
    "        return \"Asymptomatic\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "heartattack_df['Chest_Pain_Type'] = heartattack_df['cp'].apply(chestpain_type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>num</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Chest_Pain_Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Atypical Angina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>120.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Atypical Angina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Atypical Angina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>170.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Typical Angina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>100.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Atypical Angina</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps   chol  fbs  restecg  thalach  exang  oldpeak  \\\n",
       "0   28    1   2     130.0  132.0  0.0      2.0    185.0    0.0      0.0   \n",
       "1   29    1   2     120.0  243.0  0.0      0.0    160.0    0.0      0.0   \n",
       "2   29    1   2     140.0    NaN  0.0      0.0    170.0    0.0      0.0   \n",
       "3   30    0   1     170.0  237.0  0.0      1.0    170.0    0.0      0.0   \n",
       "4   31    0   2     100.0  219.0  0.0      1.0    150.0    0.0      0.0   \n",
       "\n",
       "   num         Gender  Chest_Pain_Type  \n",
       "0           0    Male  Atypical Angina  \n",
       "1           0    Male  Atypical Angina  \n",
       "2           0    Male  Atypical Angina  \n",
       "3           0  Female   Typical Angina  \n",
       "4           0  Female  Atypical Angina  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heartattack_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x15ce51a3668>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 429.375x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot('cp',data=heartattack_df,hue='Gender',kind=\"count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x15ce4ef5588>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1149.38x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot('Chest_Pain_Type',data=heartattack_df,hue='Gender',kind=\"count\",aspect=3,palette=\"summer\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>num</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Chest_Pain_Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Atypical Angina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>120.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Atypical Angina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Atypical Angina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>170.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Typical Angina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>100.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Atypical Angina</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps   chol  fbs  restecg  thalach  exang  oldpeak  \\\n",
       "0   28    1   2     130.0  132.0  0.0      2.0    185.0    0.0      0.0   \n",
       "1   29    1   2     120.0  243.0  0.0      0.0    160.0    0.0      0.0   \n",
       "2   29    1   2     140.0    NaN  0.0      0.0    170.0    0.0      0.0   \n",
       "3   30    0   1     170.0  237.0  0.0      1.0    170.0    0.0      0.0   \n",
       "4   31    0   2     100.0  219.0  0.0      1.0    150.0    0.0      0.0   \n",
       "\n",
       "   num         Gender  Chest_Pain_Type  \n",
       "0           0    Male  Atypical Angina  \n",
       "1           0    Male  Atypical Angina  \n",
       "2           0    Male  Atypical Angina  \n",
       "3           0  Female   Typical Angina  \n",
       "4           0  Female  Atypical Angina  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heartattack_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def diabetic(Diabetes):\n",
    "    fbs = Diabetes\n",
    "    if fbs == 1:\n",
    "        return \"Diabetic\"\n",
    "    else:\n",
    "        return \"Non-Diabetic\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "heartattack_df['Diabetes']=heartattack_df['fbs'].apply(diabetic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x15ce4bac358>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 905.625x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sns.FacetGrid(heartattack_df,hue='cp',aspect=4)\n",
    "fig.map(sns.kdeplot,'age',shade=True)\n",
    "\n",
    "\n",
    "\n",
    "fig.add_legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x15ce4a6f2b0>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 958x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sns.FacetGrid(heartattack_df,hue='Diabetes',aspect=4)\n",
    "fig.map(sns.kdeplot,'age',shade=True)\n",
    "\n",
    "\n",
    "\n",
    "fig.add_legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x15ce4a82940>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('age','trestbps',data=heartattack_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x15ce7631be0>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot('trestbps',data=heartattack_df,kind=\"count\",aspect=4)\n",
    "plt.legend(title='Resting Blood Pressure details of Pateints', loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "g = sns.lmplot(\n",
    "    x=\"age\", \n",
    "    y=\"trestbps\", \n",
    "    hue=\"Gender\", \n",
    "    data=heartattack_df,  \n",
    "    legend=False\n",
    ")\n",
    "\n",
    "plt.legend(title='''Resting Blood Pressure categorised to see differences\n",
    "           in gender''', loc='upper left', labels=['Below Normal', 'Above Normal'])\n",
    "plt.show(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}