Alua_Onayeva_BD2008_Final_Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0e615936",
   "metadata": {},
   "source": [
    "# Final project\n",
    "## 1. Dataset\n",
    "My dataset is [Stroke Prediction Dataset](https://www.kaggle.com/fedesoriano/stroke-prediction-dataset).<br>\n",
    "Link to the GitHub [see](https://raw.githubusercontent.com/loopiiu/datasets/main/healthcare-dataset-stroke-data.csv)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c1d23cb2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "afdf8d02",
   "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>id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>hypertension</th>\n",
       "      <th>heart_disease</th>\n",
       "      <th>ever_married</th>\n",
       "      <th>work_type</th>\n",
       "      <th>Residence_type</th>\n",
       "      <th>avg_glucose_level</th>\n",
       "      <th>bmi</th>\n",
       "      <th>smoking_status</th>\n",
       "      <th>stroke</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9046</td>\n",
       "      <td>Male</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>228.69</td>\n",
       "      <td>36.6</td>\n",
       "      <td>formerly smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51676</td>\n",
       "      <td>Female</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Self-employed</td>\n",
       "      <td>Rural</td>\n",
       "      <td>202.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>31112</td>\n",
       "      <td>Male</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Rural</td>\n",
       "      <td>105.92</td>\n",
       "      <td>32.5</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60182</td>\n",
       "      <td>Female</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>171.23</td>\n",
       "      <td>34.4</td>\n",
       "      <td>smokes</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1665</td>\n",
       "      <td>Female</td>\n",
       "      <td>79.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Self-employed</td>\n",
       "      <td>Rural</td>\n",
       "      <td>174.12</td>\n",
       "      <td>24.0</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>56669</td>\n",
       "      <td>Male</td>\n",
       "      <td>81.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>186.21</td>\n",
       "      <td>29.0</td>\n",
       "      <td>formerly smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>53882</td>\n",
       "      <td>Male</td>\n",
       "      <td>74.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Rural</td>\n",
       "      <td>70.09</td>\n",
       "      <td>27.4</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10434</td>\n",
       "      <td>Female</td>\n",
       "      <td>69.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>94.39</td>\n",
       "      <td>22.8</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>27419</td>\n",
       "      <td>Female</td>\n",
       "      <td>59.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Rural</td>\n",
       "      <td>76.15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>60491</td>\n",
       "      <td>Female</td>\n",
       "      <td>78.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>58.57</td>\n",
       "      <td>24.2</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  gender   age  hypertension  heart_disease ever_married  \\\n",
       "0   9046    Male  67.0             0              1          Yes   \n",
       "1  51676  Female  61.0             0              0          Yes   \n",
       "2  31112    Male  80.0             0              1          Yes   \n",
       "3  60182  Female  49.0             0              0          Yes   \n",
       "4   1665  Female  79.0             1              0          Yes   \n",
       "5  56669    Male  81.0             0              0          Yes   \n",
       "6  53882    Male  74.0             1              1          Yes   \n",
       "7  10434  Female  69.0             0              0           No   \n",
       "8  27419  Female  59.0             0              0          Yes   \n",
       "9  60491  Female  78.0             0              0          Yes   \n",
       "\n",
       "       work_type Residence_type  avg_glucose_level   bmi   smoking_status  \\\n",
       "0        Private          Urban             228.69  36.6  formerly smoked   \n",
       "1  Self-employed          Rural             202.21   NaN     never smoked   \n",
       "2        Private          Rural             105.92  32.5     never smoked   \n",
       "3        Private          Urban             171.23  34.4           smokes   \n",
       "4  Self-employed          Rural             174.12  24.0     never smoked   \n",
       "5        Private          Urban             186.21  29.0  formerly smoked   \n",
       "6        Private          Rural              70.09  27.4     never smoked   \n",
       "7        Private          Urban              94.39  22.8     never smoked   \n",
       "8        Private          Rural              76.15   NaN          Unknown   \n",
       "9        Private          Urban              58.57  24.2          Unknown   \n",
       "\n",
       "   stroke  \n",
       "0       1  \n",
       "1       1  \n",
       "2       1  \n",
       "3       1  \n",
       "4       1  \n",
       "5       1  \n",
       "6       1  \n",
       "7       1  \n",
       "8       1  \n",
       "9       1  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data = pd.read_csv('C:\\\\Users\\\\Acer\\\\Desktop\\\\finals\\\\healthcare-dataset-stroke-data.csv')\n",
    "data=pd.read_csv('https://raw.githubusercontent.com/loopiiu/datasets/main/healthcare-dataset-stroke-data.csv')\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d456734a",
   "metadata": {},
   "source": [
    "## 2. Introduction\n",
    "**Stroke** is the second by frequency leading cause of death out of diseases worldwide.<br>\n",
    "5.5 million people die of stroke every year, and due to statistics, every 4th person aged over 25 \n",
    "will suffer a stroke in their lifetime.\n",
    "\n",
    "**More common among:**\n",
    "<ul>\n",
    "    <li>men</li>\n",
    "    <li>women using birth control</li>\n",
    "    <li>people with diabetes</li>\n",
    "    <li>people with high blood pressure</li>\n",
    "    <li>people with heart disease</li>\n",
    "    <li>people who smoke</li>\n",
    "</ul>\n",
    "<h3>Objectives </h3>\n",
    "<br>\n",
    "In this dataset we are given the data about patient personal information, such as gender, age, occupation ans etc.<br>\n",
    "With a help of this information, I am going to predict who is more likely to get stroke."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6b5c6f3",
   "metadata": {},
   "source": [
    "## 3. Data description"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ce61a89",
   "metadata": {},
   "source": [
    "This dataset consists of 5110 rows and 12 columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d562ac58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5110, 12)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f13220a7",
   "metadata": {},
   "source": [
    "Given columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2207dbd2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'gender', 'age', 'hypertension', 'heart_disease', 'ever_married',\n",
       "       'work_type', 'Residence_type', 'avg_glucose_level', 'bmi',\n",
       "       'smoking_status', 'stroke'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "119b025e",
   "metadata": {},
   "source": [
    "<h3>Attributes:</h3>\n",
    "<ol>\n",
    "    <li> <b>id:</b> Identification number</li>\n",
    "<li> <b>gender:</b> \"Male\", \"Female\", \"Other\"</li>\n",
    "<li> <b>age:</b> Patient age</li>\n",
    "<li> <b>hypertension:</b> 0 - absense, 1 - presense</li>\n",
    "<li> <b>heart_disease:</b> 0 - absense, 1 - presense</li>\n",
    "<li> <b>ever_married:</b> \"No\", \"Yes\"</li>\n",
    "<li> <b>work_type:</b> Occupation type<br>\"Govt_jov\", \"Never_worked\", \"Private\", \"Self-employed\", \"children\"\n",
    "    <li><b>Residence_type:</b> \"Rural\", \"Urban\"</li>\n",
    "<li> <b>avg_glucose_level:</b> Average glucose level in blood</li>\n",
    "<li> <b>bmi:</b> Body Mass Index(BMI)</li>\n",
    "<li> <b>smoking_status:</b> \"smokes\", \"never smoked\", \"formerly smoked\", \"Unknown\"</li>\n",
    "<li> <b>stroke:</b> 0 - if hadn't, 1 - if had</li>The most important column in the dataset.\n",
    "</ol>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3acf5968",
   "metadata": {},
   "source": [
    "We have got 7 numerical and 5 categorical variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "abf678ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5110 entries, 0 to 5109\n",
      "Data columns (total 12 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   id                 5110 non-null   int64  \n",
      " 1   gender             5110 non-null   object \n",
      " 2   age                5110 non-null   float64\n",
      " 3   hypertension       5110 non-null   int64  \n",
      " 4   heart_disease      5110 non-null   int64  \n",
      " 5   ever_married       5110 non-null   object \n",
      " 6   work_type          5110 non-null   object \n",
      " 7   Residence_type     5110 non-null   object \n",
      " 8   avg_glucose_level  5110 non-null   float64\n",
      " 9   bmi                4909 non-null   float64\n",
      " 10  smoking_status     5110 non-null   object \n",
      " 11  stroke             5110 non-null   int64  \n",
      "dtypes: float64(3), int64(4), object(5)\n",
      "memory usage: 479.2+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6f045e8",
   "metadata": {},
   "source": [
    "Find the number of unique values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6526db13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                   5110\n",
       "gender                  3\n",
       "age                   104\n",
       "hypertension            2\n",
       "heart_disease           2\n",
       "ever_married            2\n",
       "work_type               5\n",
       "Residence_type          2\n",
       "avg_glucose_level    3979\n",
       "bmi                   418\n",
       "smoking_status          4\n",
       "stroke                  2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b0ca143",
   "metadata": {},
   "source": [
    "I urge you to see the correlation between columns via heatmap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e0c96e68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(data.corr(), cmap=\"YlGnBu\", annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae0a008a",
   "metadata": {},
   "source": [
    "From correlation graph, it is seen that there is a interconnection between age and bmi."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3471c9d4",
   "metadata": {},
   "source": [
    "## 4. Research questions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26e707e4",
   "metadata": {},
   "source": [
    "<b>Q1:</b> Is there any impact of an **age** in getting a stroke? (what about the gender distribution?)<br>\n",
    "<b>Q2:</b> What about other factors, such as **hypertension, heart diseases, and maritial status** statistics among those who had a stroke?<br>\n",
    "<b>Q3:</b> Impact of the features, as **bmi** and **average glucose level** on stroke, and correlation between them. <br>\n",
    "<b>Q4:</b> **Smoking habits** and **residence type** as a factor of getting a stroke.<br>\n",
    "<b>Q5:</b> Which **type of workers** are more likely to be under the risk of a stroke?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b32b7fb",
   "metadata": {},
   "source": [
    "## 5. Data prepartion"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb30d4d7",
   "metadata": {},
   "source": [
    "Change column names to lower case. Because \"Residence_type\" starts from uppercase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "85aa2567",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'gender', 'age', 'hypertension', 'heart_disease', 'ever_married',\n",
       "       'work_type', 'residence_type', 'avg_glucose_level', 'bmi',\n",
       "       'smoking_status', 'stroke'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns = data.columns.str.lower()\n",
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1afa771",
   "metadata": {},
   "source": [
    "Checking for null values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2ab81df6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                     0\n",
       "gender                 0\n",
       "age                    0\n",
       "hypertension           0\n",
       "heart_disease          0\n",
       "ever_married           0\n",
       "work_type              0\n",
       "residence_type         0\n",
       "avg_glucose_level      0\n",
       "bmi                  201\n",
       "smoking_status         0\n",
       "stroke                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e13a7e72",
   "metadata": {},
   "source": [
    "We can see that there is only \"bmi\" column's values are missing. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8e8591f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.9334637964774952"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of missing column's percentage\n",
    "(201/5110)*100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0be3f5d6",
   "metadata": {},
   "source": [
    "In statistical methods, If the percentage is lower than 5%, it means that we can replace missing values with the mean value.\n",
    "We need this kind of way, due to the fact that our dataset is not big enough, and dropping these values will be a lost for our analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "453f526b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean: 28.893236911794673\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "id                   0\n",
       "gender               0\n",
       "age                  0\n",
       "hypertension         0\n",
       "heart_disease        0\n",
       "ever_married         0\n",
       "work_type            0\n",
       "residence_type       0\n",
       "avg_glucose_level    0\n",
       "bmi                  0\n",
       "smoking_status       0\n",
       "stroke               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean = data.bmi.mean() #mean age value\n",
    "print('Mean:', mean)\n",
    "data.bmi.fillna(value=mean, inplace=True) # filling missing values with a mean\n",
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6ff52e3",
   "metadata": {},
   "source": [
    "Check for duplicated values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "620d9804",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e20dedcc",
   "metadata": {},
   "source": [
    "We have got only one instance where gender is 'Other'. Thus we can drop it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "acfa2fdf",
   "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>id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>hypertension</th>\n",
       "      <th>heart_disease</th>\n",
       "      <th>ever_married</th>\n",
       "      <th>work_type</th>\n",
       "      <th>residence_type</th>\n",
       "      <th>avg_glucose_level</th>\n",
       "      <th>bmi</th>\n",
       "      <th>smoking_status</th>\n",
       "      <th>stroke</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3116</th>\n",
       "      <td>56156</td>\n",
       "      <td>Other</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Private</td>\n",
       "      <td>Rural</td>\n",
       "      <td>143.33</td>\n",
       "      <td>22.4</td>\n",
       "      <td>formerly smoked</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         id gender   age  hypertension  heart_disease ever_married work_type  \\\n",
       "3116  56156  Other  26.0             0              0           No   Private   \n",
       "\n",
       "     residence_type  avg_glucose_level   bmi   smoking_status  stroke  \n",
       "3116          Rural             143.33  22.4  formerly smoked       0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.gender=='Other']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2dde03be",
   "metadata": {},
   "source": [
    "Checking whether row was dropped."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "06975573",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5109, 12)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.drop(data[data.gender=='Other'].index, inplace=True)\n",
    "data.shape "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec293cef",
   "metadata": {},
   "source": [
    "We can drop **id** column. Because values are not so importanat. They do not give us any additional information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "646c62e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5109, 11)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.drop(columns=['id'], inplace=True)\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01312263",
   "metadata": {},
   "source": [
    "## 6. Data Analysis and Visualisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "83f9631c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAIEAAABICAYAAADRR5YsAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAABOElEQVR4nO3dMUpcUQCG0e+KAQurwTQBmTIbyLbssgtXoBtxCWmyAbu0oggh9jcbmCke+Hhmck57p/gffHCnu2POGf+3s60HsD0RIAJEQCIgEVCdL/nx5dVu7vbXa23Z3MXzp60nrObp9Ve/317GobNFEez2133/8fA+qz6gr3dftp6wmpvbb0fPXAeIABGQCEgEJAISAYmAREAiIBGQCEgEJAISAYmAREAiIBGQCEgEJAISAYmAREAiIBGQCEgEJAISAYmAREAiIBGQCEgEJAISAYmAREAiIBGQCEgEJAISAYmAREAiIBGQCKjGkgezxxh/qsf15mzuqnrZesRK9nPOz4cOFr2GVj3OOY8/q/WPG2P8POXvO8Z1gAhYHsH9Kis+jlP/voMW/THkNLkOEAEiIBGQCKj+AlrjJQ/y1cGEAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 144x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 144x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 216x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# some color palettes for my graphics\n",
    "colors1=['#91F9E5','#B892FF']\n",
    "colors2=['#FFC2E2','#C4FFF9']\n",
    "colors3 = ['#B7C3F3', '#DD7596', '#8EB897']\n",
    "colors4=['#118AB2','#06D6A0','#FFD166','#EF476F']\n",
    "colors5=['#50C9CE','#72A1E5','#9883E5','#FCD3DE']\n",
    "\n",
    "sns.palplot(sns.color_palette(colors1))\n",
    "sns.palplot(sns.color_palette(colors2))\n",
    "sns.palplot(sns.color_palette(colors3))\n",
    "sns.palplot(sns.color_palette(colors4))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6669e0e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating separate dataframe for those who had and hadn't stroke\n",
    "had=data[data.stroke==1]\n",
    "hadnot=data[data.stroke==0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5b972a81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    4860\n",
       "1     249\n",
       "Name: stroke, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.stroke.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67185a0b",
   "metadata": {},
   "source": [
    "<h3><b>6.1 Q1:</b></h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cfff00ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "# some values for analysis\n",
    "r1 = round(data[data.stroke==0].age.mean(), 2)\n",
    "r2 = round(data[data.stroke==1].age.mean(), 2)\n",
    "r3 = round(had[had.gender=='Female'].age.mean(), 2)\n",
    "r4 = round(had[had.gender=='Male'].age.mean(), 2)\n",
    "\n",
    "labels=['No Stroke', 'Stroke']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a68ce8d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean age for those who had not stroke:  41.97\n",
      "Mean age for those who had stroke:  67.73\n"
     ]
    }
   ],
   "source": [
    "fig, ((axes1,axes2)) = plt.subplots(1,2, figsize=(15,5))\n",
    "\n",
    "# 1st graph\n",
    "sns.histplot(data = data, \n",
    "             x = 'age', \n",
    "             hue='stroke', \n",
    "             ax = axes1, \n",
    "             palette=colors1\n",
    "            )\n",
    "axes1.set_title('Frequency of people by age', fontsize=15)\n",
    "axes1.legend(labels=['Stroke', 'No Stroke'])\n",
    "\n",
    "#2nd graph\n",
    "sns.violinplot(x=data['stroke'], \n",
    "               y=data['age'], \n",
    "               ax = axes2, \n",
    "               palette=colors1\n",
    "              )\n",
    "axes2.set_title('Distribution by age', fontsize=15)\n",
    "axes2.set_xticklabels(labels)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "# mean values\n",
    "print('Mean age for those who had not stroke: ', r1)\n",
    "print('Mean age for those who had stroke: ', r2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71e02eca",
   "metadata": {},
   "source": [
    "From the graph above, there is an obvious illustration that people who had stroke are appoximately older than 40 years old, and the mean age for that people is **67.73**. Moreover from the right and left graphs, we can clearly see a consistent pattern, that the older you are, the more likely for you to get a stroke. The highest amount of strokes fall on 70-80 years old people, **88** person, nearly **35%** of all people who had a stroke."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "2674cac3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "88"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of people who is older than 70 and younger than 80, and had stroke\n",
    "data[(data.stroke==1) & (data.age>70) & (data.age<80)].stroke.count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a1e2a56",
   "metadata": {},
   "source": [
    "Let's go further and see any regularity by gender spread."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ed767fd1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean age for those who had stroke (Female):  67.14\n",
      "Mean age for those who had stroke (Male):  68.5\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "\n",
    "ax = sns.violinplot(data = data, \n",
    "                    x = 'gender', \n",
    "                    y = 'age',\n",
    "                    hue='stroke', \n",
    "                    palette=colors2)\n",
    "\n",
    "ax.set_title('Age distribution by gender', fontsize=16)\n",
    "plt.show()\n",
    "\n",
    "print('Mean age for those who had stroke (Female): ', r3)\n",
    "print('Mean age for those who had stroke (Male): ', r4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07b25b46",
   "metadata": {},
   "source": [
    "Let's take a deeper look at the same graph as a second one, but with one additional parameter - **gender**. There is seen that men under the risk of stroke are approximately older than 40, while in women there exists cases(8 female) earlier than 40. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3c5b78ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "# number of people younger than 40 by gender\n",
    "print(had[(had.age<40) & (had.gender=='Female')].stroke.count())\n",
    "print(had[(had.age<40) & (had.gender=='Male')].stroke.count())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cbf5d5f",
   "metadata": {},
   "source": [
    "<h3><b>6.1 Q2:</b></h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6d864b01",
   "metadata": {},
   "outputs": [],
   "source": [
    "# data preparation for Q2\n",
    "label1 = ['No hypertension', 'Hypertension']\n",
    "label2 = ['No heart disease', 'Heart disease']\n",
    "label3 = ['Ever married', 'Not married']\n",
    "\n",
    "hypertension = had.hypertension.value_counts()\n",
    "heart_disease = had.heart_disease.value_counts()\n",
    "ever_married = had.ever_married.value_counts()\n",
    "\n",
    "exp = (0, 0.1) # separates two parts of the pie chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a5f9221c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 3, figsize=(20,7))\n",
    "\n",
    "# 1st graph\n",
    "axes[0].pie(hypertension, \n",
    "            labels=label1, \n",
    "            colors=colors3, \n",
    "            explode=exp, \n",
    "            autopct='%1.1f%%')\n",
    "\n",
    "# 2nd graph\n",
    "axes[1].pie(heart_disease, \n",
    "            labels=label2, \n",
    "            colors=colors3,  \n",
    "            explode=exp, \n",
    "            autopct='%1.1f%%')\n",
    "\n",
    "# 3rd graph\n",
    "axes[2].pie(ever_married, \n",
    "            labels=label3, \n",
    "            colors=colors3,  \n",
    "            explode=exp,\n",
    "            autopct='%1.1f%%')\n",
    "\n",
    "axes[1].set_title('Distribution by several factors', fontsize=20)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b089caf2",
   "metadata": {},
   "source": [
    "In the pie charts upwards, we can seeminlgy state the fact of hypertension and heart disease don't affect on getting a stroke in any ways. However, the high percentage of the people who have been married had a stroke. Thus, if you have ever been married, you are more likely to be under the risk of a stroke, unlike when you are not married."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc29eaf0",
   "metadata": {},
   "source": [
    "<h3><b>6.1 Q3:</b></h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "170f7fb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# see a correlation between columns where stroke=1\n",
    "sns.heatmap(had.corr(), cmap=\"YlGnBu\", annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82790a6c",
   "metadata": {},
   "source": [
    "The heatmap shows that there is a relation between **'avg_glucose_level'** and **'bmi'** columns. Let's check this relation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a461e838",
   "metadata": {},
   "outputs": [],
   "source": [
    "# colors\n",
    "c1='#94d2bd'\n",
    "c2='#7b2cbf'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0c1c2820",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1),(ax2)) = plt.subplots(2,1, figsize=(17,12))\n",
    "\n",
    "# 1st row\n",
    "sns.histplot(data=had, \n",
    "             x=\"avg_glucose_level\", \n",
    "             color=c2, label=\"Stroke\", \n",
    "             kde=True, \n",
    "             ax=ax1)\n",
    "\n",
    "sns.histplot(data=hadnot, \n",
    "             x=\"avg_glucose_level\", \n",
    "             color=c1, \n",
    "             label=\"No stroke\", \n",
    "             kde=True, \n",
    "             ax=ax1)\n",
    "\n",
    "ax1.legend()\n",
    "ax1.set_title('Distribution by glucose level')\n",
    "\n",
    "# 2nd row\n",
    "sns.histplot(data=had, \n",
    "             x=\"bmi\", \n",
    "             color=c2, \n",
    "             label=\"Stroke\", \n",
    "             kde=True, \n",
    "             ax=ax2)\n",
    "\n",
    "sns.histplot(data=hadnot, \n",
    "             x=\"bmi\", \n",
    "             color=c1, \n",
    "             label=\"No stroke\", \n",
    "             kde=True, \n",
    "             ax=ax2)\n",
    "\n",
    "ax2.legend()\n",
    "ax2.set_title('Distribution by BMI')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "470270a8",
   "metadata": {},
   "source": [
    "The graphs above depict average glucose level and bmi parameters distributed by the presense of a stroke. The lines of ups and downs in both charts for those who had and had not a stroke resemble each other.<br>\n",
    "In the first graph, the most recurring glucose levels are between 50 and 100, for both parameters.<br>\n",
    "In the second graph, the most freguent bmi values are between 25 and 35."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c1a3e951",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# the relationship between 2 columns mentioned above\n",
    "a = sns.jointplot(data=had, \n",
    "              x='bmi', \n",
    "              y='avg_glucose_level', \n",
    "              kind='hex')\n",
    "\n",
    "a.fig.suptitle('Correlation between bmi and glucose level', fontsize=15)\n",
    "a.fig.subplots_adjust(top=0.9)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01a4d28a",
   "metadata": {},
   "source": [
    "So the graph provides data on correlation of two graphs, and the most frequent value is painted dark blue.<br>\n",
    "**'bmi'**  between 25 and 35<br>\n",
    "**'avg_glucose level'**  between 50 and 100<br>\n",
    "<h4>Let's make some calculations.</h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "de05f11c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "67.68828402366864\n",
      "66.46714285714286\n"
     ]
    }
   ],
   "source": [
    "print(had[(had.bmi>25) & (had.bmi<35)].age.mean())\n",
    "print(had[(had.avg_glucose_level<100)].age.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d92c9990",
   "metadata": {},
   "source": [
    "The average age for both of those range of values is 66-67 y.o. It is the most frequent age occurence in cases where stroke is 1. Correlation is justified."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a13bdc18",
   "metadata": {},
   "source": [
    "<h3><b>6.1 Q4:</b></h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b9eed362",
   "metadata": {},
   "outputs": [],
   "source": [
    "# data preparation for Q4\n",
    "\n",
    "size = had.smoking_status.value_counts() #smoking status of the people with their corresponding value where stroke=1\n",
    "label = had.smoking_status.value_counts().index # smoking status indexes\n",
    "urban = had[had.residence_type=='Urban'].smoking_status.value_counts().tolist() # number of people with 'Urban' residence type\n",
    "rural = had[had.residence_type=='Rural'].smoking_status.value_counts().tolist() # number of people with 'Rural' residence type\n",
    "x = np.arange(len(label)) # arranging by labels [0, 1, 2, 3]\n",
    "width=0.37 # width"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "8a07bdbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(20,7))\n",
    "\n",
    "# 1st graph\n",
    "axes[0].pie(size, \n",
    "            colors=colors4, \n",
    "            labels=label, \n",
    "            explode=(0.1, 0.1, 0.1, 0.1),\n",
    "            autopct='%1.1f%%')\n",
    "\n",
    "axes[0].set_title('Smoking status of people who had stroke', fontsize=15)\n",
    "\n",
    "# 2nd graph\n",
    "axes[1].bar(x-0.19, urban, width, label='Urban', color='#118AB2')\n",
    "axes[1].bar(x+0.19, rural, width, label='Rural', color='#06D6A0')\n",
    "plt.title('Smoking status with an area distribution where stroke=1', fontsize=15)\n",
    "plt.xticks(x, label)\n",
    "plt.ylabel(\"Number of people\", fontsize=12)\n",
    "plt.xlabel(\"Smoking Status\", fontsize=12)\n",
    "axes[1].legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b019e48e",
   "metadata": {},
   "source": [
    "Unknown category is for those people, where we don't know anything about their smoking habits.<br>For those who had a stroke, it is about **19%**. However, we can see that the percentage of the people who have never smoked is more that 1/3 of the people who had a stroke. Consequently, we are able to draw a conclusion that **smoking habits are not so important in predicting a stroke**.<br>\n",
    "In the second bar graph, I wanted to see a difference between the place of living and smoking habits. Because of the fact that urban and rural people are evenly distributed, there is no any significant changes in the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "9f62ab17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Urban    135\n",
       "Rural    114\n",
       "Name: residence_type, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "had.residence_type.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cf98ff2",
   "metadata": {},
   "source": [
    "<h3><b>6.1 Q5:</b></h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "111e8c35",
   "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>work_type</th>\n",
       "      <th>stroke</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Private</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Self-employed</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Govt_job</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>children</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       work_type  stroke\n",
       "1        Private     149\n",
       "2  Self-employed      65\n",
       "0       Govt_job      33\n",
       "3       children       2"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# grouping people by work_type where stroke=1\n",
    "had[['stroke', 'work_type']].groupby(by='work_type', as_index=False).count().sort_values(by='stroke', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7914dc6a",
   "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>work_type</th>\n",
       "      <th>stroke</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Private</td>\n",
       "      <td>2775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Self-employed</td>\n",
       "      <td>754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>children</td>\n",
       "      <td>685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Govt_job</td>\n",
       "      <td>624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Never_worked</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       work_type  stroke\n",
       "2        Private    2775\n",
       "3  Self-employed     754\n",
       "4       children     685\n",
       "0       Govt_job     624\n",
       "1   Never_worked      22"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# grouping people by work_type where stroke=0\n",
    "hadnot[['stroke', 'work_type']].groupby(by='work_type', as_index=False).count().sort_values(by='stroke', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "66b983ee",
   "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>work_type</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Self-employed</td>\n",
       "      <td>71.338462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Private</td>\n",
       "      <td>67.241611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Govt_job</td>\n",
       "      <td>66.454545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>children</td>\n",
       "      <td>7.660000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       work_type        age\n",
       "2  Self-employed  71.338462\n",
       "1        Private  67.241611\n",
       "0       Govt_job  66.454545\n",
       "3       children   7.660000"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean age of people from different work sectors who had a stroke\n",
    "had[['stroke', 'work_type', 'age']].groupby(by='work_type', as_index=False).age.mean().sort_values(by='age', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "6c8b9b44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1,ax2)) = plt.subplots(1,2, figsize=(15,5))\n",
    "\n",
    "# 1st graph\n",
    "sns.histplot(data=had, \n",
    "             x=\"age\", \n",
    "             hue=\"work_type\", \n",
    "             multiple=\"stack\", \n",
    "             ax=ax1)\n",
    "\n",
    "ax1.set_title('Had a stroke', fontsize=16)\n",
    "\n",
    "# 2nd graph\n",
    "sns.histplot(data=hadnot, \n",
    "             x=\"age\", \n",
    "             hue=\"work_type\", \n",
    "             multiple=\"stack\", \n",
    "             ax=ax2)\n",
    "\n",
    "ax2.set_title('Had not a stroke', fontsize=16)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30753b2a",
   "metadata": {},
   "source": [
    "There is a clear illustration of that people who had a stroke are more likely to be from the private work sector, on the second place is self-employed, on the third govermental job. In the second graph, where stroke=0, private sector also dominate. In addition to that, in the fisrt graph there is no 'never_worked' category, unlike in the first one."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7a67326",
   "metadata": {},
   "source": [
    "## 7. Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9593a7b",
   "metadata": {},
   "source": [
    "To conclude all the things said above, we covered all the parameters in dataset. So we can came to conclusion, that there are mainly 3 crucial factors in determining stroke, they are: **age**, **bmi**, and **average glucose level**. <br>Another factors, such as presense of heart disease, hypertension, or smoking habits can not be so important in determing a stroke. <br>However, this dataset is not big enough for making that kind of desicions, and for proper analysis the bigger dataset is needed."
   ]
  }
 ],
 "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}