Diabetes Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "40744520",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Packages\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import plotly.express as px\n",
    "import plotly.figure_factory as ff\n",
    "import plotly.graph_objects as go\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "38555a68",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data Source\n",
    "df = pd.read_csv(r'diabetes_health_indicators.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c265171d",
   "metadata": {},
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Diabetes_012</th>\n",
       "      <th>HighBP</th>\n",
       "      <th>HighChol</th>\n",
       "      <th>CholCheck</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Smoker</th>\n",
       "      <th>Stroke</th>\n",
       "      <th>HeartDiseaseorAttack</th>\n",
       "      <th>PhysActivity</th>\n",
       "      <th>Fruits</th>\n",
       "      <th>...</th>\n",
       "      <th>AnyHealthcare</th>\n",
       "      <th>NoDocbcCost</th>\n",
       "      <th>GenHlth</th>\n",
       "      <th>MentHlth</th>\n",
       "      <th>PhysHlth</th>\n",
       "      <th>DiffWalk</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>40.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Diabetes_012  HighBP  HighChol  CholCheck   BMI  Smoker  Stroke  \\\n",
       "0           0.0     1.0       1.0        1.0  40.0     1.0     0.0   \n",
       "1           0.0     0.0       0.0        0.0  25.0     1.0     0.0   \n",
       "2           0.0     1.0       1.0        1.0  28.0     0.0     0.0   \n",
       "3           0.0     1.0       0.0        1.0  27.0     0.0     0.0   \n",
       "4           0.0     1.0       1.0        1.0  24.0     0.0     0.0   \n",
       "\n",
       "   HeartDiseaseorAttack  PhysActivity  Fruits  ...  AnyHealthcare  \\\n",
       "0                   0.0           0.0     0.0  ...            1.0   \n",
       "1                   0.0           1.0     0.0  ...            0.0   \n",
       "2                   0.0           0.0     1.0  ...            1.0   \n",
       "3                   0.0           1.0     1.0  ...            1.0   \n",
       "4                   0.0           1.0     1.0  ...            1.0   \n",
       "\n",
       "   NoDocbcCost  GenHlth  MentHlth  PhysHlth  DiffWalk  Sex   Age  Education  \\\n",
       "0          0.0      5.0      18.0      15.0       1.0  0.0   9.0        4.0   \n",
       "1          1.0      3.0       0.0       0.0       0.0  0.0   7.0        6.0   \n",
       "2          1.0      5.0      30.0      30.0       1.0  0.0   9.0        4.0   \n",
       "3          0.0      2.0       0.0       0.0       0.0  0.0  11.0        3.0   \n",
       "4          0.0      2.0       3.0       0.0       0.0  0.0  11.0        5.0   \n",
       "\n",
       "   Income  \n",
       "0     3.0  \n",
       "1     1.0  \n",
       "2     8.0  \n",
       "3     6.0  \n",
       "4     4.0  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display data\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f56b933a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 253680 entries, 0 to 253679\n",
      "Data columns (total 22 columns):\n",
      " #   Column                Non-Null Count   Dtype  \n",
      "---  ------                --------------   -----  \n",
      " 0   Diabetes_012          253680 non-null  float64\n",
      " 1   HighBP                253680 non-null  float64\n",
      " 2   HighChol              253680 non-null  float64\n",
      " 3   CholCheck             253680 non-null  float64\n",
      " 4   BMI                   253680 non-null  float64\n",
      " 5   Smoker                253680 non-null  float64\n",
      " 6   Stroke                253680 non-null  float64\n",
      " 7   HeartDiseaseorAttack  253680 non-null  float64\n",
      " 8   PhysActivity          253680 non-null  float64\n",
      " 9   Fruits                253680 non-null  float64\n",
      " 10  Veggies               253680 non-null  float64\n",
      " 11  HvyAlcoholConsump     253680 non-null  float64\n",
      " 12  AnyHealthcare         253680 non-null  float64\n",
      " 13  NoDocbcCost           253680 non-null  float64\n",
      " 14  GenHlth               253680 non-null  float64\n",
      " 15  MentHlth              253680 non-null  float64\n",
      " 16  PhysHlth              253680 non-null  float64\n",
      " 17  DiffWalk              253680 non-null  float64\n",
      " 18  Sex                   253680 non-null  float64\n",
      " 19  Age                   253680 non-null  float64\n",
      " 20  Education             253680 non-null  float64\n",
      " 21  Income                253680 non-null  float64\n",
      "dtypes: float64(22)\n",
      "memory usage: 42.6 MB\n"
     ]
    }
   ],
   "source": [
    "# Display dataset information\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "54d5dbe2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Diabetes_012</th>\n",
       "      <th>HighBP</th>\n",
       "      <th>HighChol</th>\n",
       "      <th>CholCheck</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Smoker</th>\n",
       "      <th>Stroke</th>\n",
       "      <th>HeartDiseaseorAttack</th>\n",
       "      <th>PhysActivity</th>\n",
       "      <th>Fruits</th>\n",
       "      <th>...</th>\n",
       "      <th>AnyHealthcare</th>\n",
       "      <th>NoDocbcCost</th>\n",
       "      <th>GenHlth</th>\n",
       "      <th>MentHlth</th>\n",
       "      <th>PhysHlth</th>\n",
       "      <th>DiffWalk</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
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       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "      <td>253680.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.296921</td>\n",
       "      <td>0.429001</td>\n",
       "      <td>0.424121</td>\n",
       "      <td>0.962670</td>\n",
       "      <td>28.382364</td>\n",
       "      <td>0.443169</td>\n",
       "      <td>0.040571</td>\n",
       "      <td>0.094186</td>\n",
       "      <td>0.756544</td>\n",
       "      <td>0.634256</td>\n",
       "      <td>...</td>\n",
       "      <td>0.951053</td>\n",
       "      <td>0.084177</td>\n",
       "      <td>2.511392</td>\n",
       "      <td>3.184772</td>\n",
       "      <td>4.242081</td>\n",
       "      <td>0.168224</td>\n",
       "      <td>0.440342</td>\n",
       "      <td>8.032119</td>\n",
       "      <td>5.050434</td>\n",
       "      <td>6.053875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.698160</td>\n",
       "      <td>0.494934</td>\n",
       "      <td>0.494210</td>\n",
       "      <td>0.189571</td>\n",
       "      <td>6.608694</td>\n",
       "      <td>0.496761</td>\n",
       "      <td>0.197294</td>\n",
       "      <td>0.292087</td>\n",
       "      <td>0.429169</td>\n",
       "      <td>0.481639</td>\n",
       "      <td>...</td>\n",
       "      <td>0.215759</td>\n",
       "      <td>0.277654</td>\n",
       "      <td>1.068477</td>\n",
       "      <td>7.412847</td>\n",
       "      <td>8.717951</td>\n",
       "      <td>0.374066</td>\n",
       "      <td>0.496429</td>\n",
       "      <td>3.054220</td>\n",
       "      <td>0.985774</td>\n",
       "      <td>2.071148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Diabetes_012         HighBP       HighChol      CholCheck  \\\n",
       "count  253680.000000  253680.000000  253680.000000  253680.000000   \n",
       "mean        0.296921       0.429001       0.424121       0.962670   \n",
       "std         0.698160       0.494934       0.494210       0.189571   \n",
       "min         0.000000       0.000000       0.000000       0.000000   \n",
       "25%         0.000000       0.000000       0.000000       1.000000   \n",
       "50%         0.000000       0.000000       0.000000       1.000000   \n",
       "75%         0.000000       1.000000       1.000000       1.000000   \n",
       "max         2.000000       1.000000       1.000000       1.000000   \n",
       "\n",
       "                 BMI         Smoker         Stroke  HeartDiseaseorAttack  \\\n",
       "count  253680.000000  253680.000000  253680.000000         253680.000000   \n",
       "mean       28.382364       0.443169       0.040571              0.094186   \n",
       "std         6.608694       0.496761       0.197294              0.292087   \n",
       "min        12.000000       0.000000       0.000000              0.000000   \n",
       "25%        24.000000       0.000000       0.000000              0.000000   \n",
       "50%        27.000000       0.000000       0.000000              0.000000   \n",
       "75%        31.000000       1.000000       0.000000              0.000000   \n",
       "max        98.000000       1.000000       1.000000              1.000000   \n",
       "\n",
       "        PhysActivity         Fruits  ...  AnyHealthcare    NoDocbcCost  \\\n",
       "count  253680.000000  253680.000000  ...  253680.000000  253680.000000   \n",
       "mean        0.756544       0.634256  ...       0.951053       0.084177   \n",
       "std         0.429169       0.481639  ...       0.215759       0.277654   \n",
       "min         0.000000       0.000000  ...       0.000000       0.000000   \n",
       "25%         1.000000       0.000000  ...       1.000000       0.000000   \n",
       "50%         1.000000       1.000000  ...       1.000000       0.000000   \n",
       "75%         1.000000       1.000000  ...       1.000000       0.000000   \n",
       "max         1.000000       1.000000  ...       1.000000       1.000000   \n",
       "\n",
       "             GenHlth       MentHlth       PhysHlth       DiffWalk  \\\n",
       "count  253680.000000  253680.000000  253680.000000  253680.000000   \n",
       "mean        2.511392       3.184772       4.242081       0.168224   \n",
       "std         1.068477       7.412847       8.717951       0.374066   \n",
       "min         1.000000       0.000000       0.000000       0.000000   \n",
       "25%         2.000000       0.000000       0.000000       0.000000   \n",
       "50%         2.000000       0.000000       0.000000       0.000000   \n",
       "75%         3.000000       2.000000       3.000000       0.000000   \n",
       "max         5.000000      30.000000      30.000000       1.000000   \n",
       "\n",
       "                 Sex            Age      Education         Income  \n",
       "count  253680.000000  253680.000000  253680.000000  253680.000000  \n",
       "mean        0.440342       8.032119       5.050434       6.053875  \n",
       "std         0.496429       3.054220       0.985774       2.071148  \n",
       "min         0.000000       1.000000       1.000000       1.000000  \n",
       "25%         0.000000       6.000000       4.000000       5.000000  \n",
       "50%         0.000000       8.000000       5.000000       7.000000  \n",
       "75%         1.000000      10.000000       6.000000       8.000000  \n",
       "max         1.000000      13.000000       6.000000       8.000000  \n",
       "\n",
       "[8 rows x 22 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fd725666",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Diabetes_012</th>\n",
       "      <th>HighBP</th>\n",
       "      <th>HighChol</th>\n",
       "      <th>CholCheck</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Smoker</th>\n",
       "      <th>Stroke</th>\n",
       "      <th>HeartDiseaseorAttack</th>\n",
       "      <th>PhysActivity</th>\n",
       "      <th>Fruits</th>\n",
       "      <th>...</th>\n",
       "      <th>AnyHealthcare</th>\n",
       "      <th>NoDocbcCost</th>\n",
       "      <th>GenHlth</th>\n",
       "      <th>MentHlth</th>\n",
       "      <th>PhysHlth</th>\n",
       "      <th>DiffWalk</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Diabetes_012</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.271596</td>\n",
       "      <td>0.209085</td>\n",
       "      <td>0.067546</td>\n",
       "      <td>0.224379</td>\n",
       "      <td>0.062914</td>\n",
       "      <td>0.107179</td>\n",
       "      <td>0.180272</td>\n",
       "      <td>-0.121947</td>\n",
       "      <td>-0.042192</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015410</td>\n",
       "      <td>0.035436</td>\n",
       "      <td>0.302587</td>\n",
       "      <td>0.073507</td>\n",
       "      <td>0.176287</td>\n",
       "      <td>0.224239</td>\n",
       "      <td>0.031040</td>\n",
       "      <td>0.185026</td>\n",
       "      <td>-0.130517</td>\n",
       "      <td>-0.171483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HighBP</th>\n",
       "      <td>0.271596</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.298199</td>\n",
       "      <td>0.098508</td>\n",
       "      <td>0.213748</td>\n",
       "      <td>0.096991</td>\n",
       "      <td>0.129575</td>\n",
       "      <td>0.209361</td>\n",
       "      <td>-0.125267</td>\n",
       "      <td>-0.040555</td>\n",
       "      <td>...</td>\n",
       "      <td>0.038425</td>\n",
       "      <td>0.017358</td>\n",
       "      <td>0.300530</td>\n",
       "      <td>0.056456</td>\n",
       "      <td>0.161212</td>\n",
       "      <td>0.223618</td>\n",
       "      <td>0.052207</td>\n",
       "      <td>0.344452</td>\n",
       "      <td>-0.141358</td>\n",
       "      <td>-0.171235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HighChol</th>\n",
       "      <td>0.209085</td>\n",
       "      <td>0.298199</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.085642</td>\n",
       "      <td>0.106722</td>\n",
       "      <td>0.091299</td>\n",
       "      <td>0.092620</td>\n",
       "      <td>0.180765</td>\n",
       "      <td>-0.078046</td>\n",
       "      <td>-0.040859</td>\n",
       "      <td>...</td>\n",
       "      <td>0.042230</td>\n",
       "      <td>0.013310</td>\n",
       "      <td>0.208426</td>\n",
       "      <td>0.062069</td>\n",
       "      <td>0.121751</td>\n",
       "      <td>0.144672</td>\n",
       "      <td>0.031205</td>\n",
       "      <td>0.272318</td>\n",
       "      <td>-0.070802</td>\n",
       "      <td>-0.085459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CholCheck</th>\n",
       "      <td>0.067546</td>\n",
       "      <td>0.098508</td>\n",
       "      <td>0.085642</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.034495</td>\n",
       "      <td>-0.009929</td>\n",
       "      <td>0.024158</td>\n",
       "      <td>0.044206</td>\n",
       "      <td>0.004190</td>\n",
       "      <td>0.023849</td>\n",
       "      <td>...</td>\n",
       "      <td>0.117626</td>\n",
       "      <td>-0.058255</td>\n",
       "      <td>0.046589</td>\n",
       "      <td>-0.008366</td>\n",
       "      <td>0.031775</td>\n",
       "      <td>0.040585</td>\n",
       "      <td>-0.022115</td>\n",
       "      <td>0.090321</td>\n",
       "      <td>0.001510</td>\n",
       "      <td>0.014259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BMI</th>\n",
       "      <td>0.224379</td>\n",
       "      <td>0.213748</td>\n",
       "      <td>0.106722</td>\n",
       "      <td>0.034495</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.013804</td>\n",
       "      <td>0.020153</td>\n",
       "      <td>0.052904</td>\n",
       "      <td>-0.147294</td>\n",
       "      <td>-0.087518</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.018471</td>\n",
       "      <td>0.058206</td>\n",
       "      <td>0.239185</td>\n",
       "      <td>0.085310</td>\n",
       "      <td>0.121141</td>\n",
       "      <td>0.197078</td>\n",
       "      <td>0.042950</td>\n",
       "      <td>-0.036618</td>\n",
       "      <td>-0.103932</td>\n",
       "      <td>-0.100069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Smoker</th>\n",
       "      <td>0.062914</td>\n",
       "      <td>0.096991</td>\n",
       "      <td>0.091299</td>\n",
       "      <td>-0.009929</td>\n",
       "      <td>0.013804</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.061173</td>\n",
       "      <td>0.114441</td>\n",
       "      <td>-0.087401</td>\n",
       "      <td>-0.077666</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.023251</td>\n",
       "      <td>0.048946</td>\n",
       "      <td>0.163143</td>\n",
       "      <td>0.092196</td>\n",
       "      <td>0.116460</td>\n",
       "      <td>0.122463</td>\n",
       "      <td>0.093662</td>\n",
       "      <td>0.120641</td>\n",
       "      <td>-0.161955</td>\n",
       "      <td>-0.123937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stroke</th>\n",
       "      <td>0.107179</td>\n",
       "      <td>0.129575</td>\n",
       "      <td>0.092620</td>\n",
       "      <td>0.024158</td>\n",
       "      <td>0.020153</td>\n",
       "      <td>0.061173</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.203002</td>\n",
       "      <td>-0.069151</td>\n",
       "      <td>-0.013389</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008776</td>\n",
       "      <td>0.034804</td>\n",
       "      <td>0.177942</td>\n",
       "      <td>0.070172</td>\n",
       "      <td>0.148944</td>\n",
       "      <td>0.176567</td>\n",
       "      <td>0.002978</td>\n",
       "      <td>0.126974</td>\n",
       "      <td>-0.076009</td>\n",
       "      <td>-0.128599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HeartDiseaseorAttack</th>\n",
       "      <td>0.180272</td>\n",
       "      <td>0.209361</td>\n",
       "      <td>0.180765</td>\n",
       "      <td>0.044206</td>\n",
       "      <td>0.052904</td>\n",
       "      <td>0.114441</td>\n",
       "      <td>0.203002</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.087299</td>\n",
       "      <td>-0.019790</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018734</td>\n",
       "      <td>0.031000</td>\n",
       "      <td>0.258383</td>\n",
       "      <td>0.064621</td>\n",
       "      <td>0.181698</td>\n",
       "      <td>0.212709</td>\n",
       "      <td>0.086096</td>\n",
       "      <td>0.221618</td>\n",
       "      <td>-0.099600</td>\n",
       "      <td>-0.141011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PhysActivity</th>\n",
       "      <td>-0.121947</td>\n",
       "      <td>-0.125267</td>\n",
       "      <td>-0.078046</td>\n",
       "      <td>0.004190</td>\n",
       "      <td>-0.147294</td>\n",
       "      <td>-0.087401</td>\n",
       "      <td>-0.069151</td>\n",
       "      <td>-0.087299</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.142756</td>\n",
       "      <td>...</td>\n",
       "      <td>0.035505</td>\n",
       "      <td>-0.061638</td>\n",
       "      <td>-0.266186</td>\n",
       "      <td>-0.125587</td>\n",
       "      <td>-0.219230</td>\n",
       "      <td>-0.253174</td>\n",
       "      <td>0.032482</td>\n",
       "      <td>-0.092511</td>\n",
       "      <td>0.199658</td>\n",
       "      <td>0.198539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fruits</th>\n",
       "      <td>-0.042192</td>\n",
       "      <td>-0.040555</td>\n",
       "      <td>-0.040859</td>\n",
       "      <td>0.023849</td>\n",
       "      <td>-0.087518</td>\n",
       "      <td>-0.077666</td>\n",
       "      <td>-0.013389</td>\n",
       "      <td>-0.019790</td>\n",
       "      <td>0.142756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031544</td>\n",
       "      <td>-0.044243</td>\n",
       "      <td>-0.103854</td>\n",
       "      <td>-0.068217</td>\n",
       "      <td>-0.044633</td>\n",
       "      <td>-0.048352</td>\n",
       "      <td>-0.091175</td>\n",
       "      <td>0.064547</td>\n",
       "      <td>0.110187</td>\n",
       "      <td>0.079929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Veggies</th>\n",
       "      <td>-0.058972</td>\n",
       "      <td>-0.061266</td>\n",
       "      <td>-0.039874</td>\n",
       "      <td>0.006121</td>\n",
       "      <td>-0.062275</td>\n",
       "      <td>-0.030678</td>\n",
       "      <td>-0.041124</td>\n",
       "      <td>-0.039167</td>\n",
       "      <td>0.153150</td>\n",
       "      <td>0.254342</td>\n",
       "      <td>...</td>\n",
       "      <td>0.029584</td>\n",
       "      <td>-0.032232</td>\n",
       "      <td>-0.123066</td>\n",
       "      <td>-0.058884</td>\n",
       "      <td>-0.064290</td>\n",
       "      <td>-0.080506</td>\n",
       "      <td>-0.064765</td>\n",
       "      <td>-0.009771</td>\n",
       "      <td>0.154329</td>\n",
       "      <td>0.151087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HvyAlcoholConsump</th>\n",
       "      <td>-0.057882</td>\n",
       "      <td>-0.003972</td>\n",
       "      <td>-0.011543</td>\n",
       "      <td>-0.023730</td>\n",
       "      <td>-0.048736</td>\n",
       "      <td>0.101619</td>\n",
       "      <td>-0.016950</td>\n",
       "      <td>-0.028991</td>\n",
       "      <td>0.012392</td>\n",
       "      <td>-0.035288</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.010488</td>\n",
       "      <td>0.004684</td>\n",
       "      <td>-0.036724</td>\n",
       "      <td>0.024716</td>\n",
       "      <td>-0.026415</td>\n",
       "      <td>-0.037668</td>\n",
       "      <td>0.005740</td>\n",
       "      <td>-0.034578</td>\n",
       "      <td>0.023997</td>\n",
       "      <td>0.053619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AnyHealthcare</th>\n",
       "      <td>0.015410</td>\n",
       "      <td>0.038425</td>\n",
       "      <td>0.042230</td>\n",
       "      <td>0.117626</td>\n",
       "      <td>-0.018471</td>\n",
       "      <td>-0.023251</td>\n",
       "      <td>0.008776</td>\n",
       "      <td>0.018734</td>\n",
       "      <td>0.035505</td>\n",
       "      <td>0.031544</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.232532</td>\n",
       "      <td>-0.040817</td>\n",
       "      <td>-0.052707</td>\n",
       "      <td>-0.008276</td>\n",
       "      <td>0.007074</td>\n",
       "      <td>-0.019405</td>\n",
       "      <td>0.138046</td>\n",
       "      <td>0.122514</td>\n",
       "      <td>0.157999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NoDocbcCost</th>\n",
       "      <td>0.035436</td>\n",
       "      <td>0.017358</td>\n",
       "      <td>0.013310</td>\n",
       "      <td>-0.058255</td>\n",
       "      <td>0.058206</td>\n",
       "      <td>0.048946</td>\n",
       "      <td>0.034804</td>\n",
       "      <td>0.031000</td>\n",
       "      <td>-0.061638</td>\n",
       "      <td>-0.044243</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.232532</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.166397</td>\n",
       "      <td>0.192107</td>\n",
       "      <td>0.148998</td>\n",
       "      <td>0.118447</td>\n",
       "      <td>-0.044931</td>\n",
       "      <td>-0.119777</td>\n",
       "      <td>-0.100701</td>\n",
       "      <td>-0.203182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GenHlth</th>\n",
       "      <td>0.302587</td>\n",
       "      <td>0.300530</td>\n",
       "      <td>0.208426</td>\n",
       "      <td>0.046589</td>\n",
       "      <td>0.239185</td>\n",
       "      <td>0.163143</td>\n",
       "      <td>0.177942</td>\n",
       "      <td>0.258383</td>\n",
       "      <td>-0.266186</td>\n",
       "      <td>-0.103854</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.040817</td>\n",
       "      <td>0.166397</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.301674</td>\n",
       "      <td>0.524364</td>\n",
       "      <td>0.456920</td>\n",
       "      <td>-0.006091</td>\n",
       "      <td>0.152450</td>\n",
       "      <td>-0.284912</td>\n",
       "      <td>-0.370014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MentHlth</th>\n",
       "      <td>0.073507</td>\n",
       "      <td>0.056456</td>\n",
       "      <td>0.062069</td>\n",
       "      <td>-0.008366</td>\n",
       "      <td>0.085310</td>\n",
       "      <td>0.092196</td>\n",
       "      <td>0.070172</td>\n",
       "      <td>0.064621</td>\n",
       "      <td>-0.125587</td>\n",
       "      <td>-0.068217</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.052707</td>\n",
       "      <td>0.192107</td>\n",
       "      <td>0.301674</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.353619</td>\n",
       "      <td>0.233688</td>\n",
       "      <td>-0.080705</td>\n",
       "      <td>-0.092068</td>\n",
       "      <td>-0.101830</td>\n",
       "      <td>-0.209806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PhysHlth</th>\n",
       "      <td>0.176287</td>\n",
       "      <td>0.161212</td>\n",
       "      <td>0.121751</td>\n",
       "      <td>0.031775</td>\n",
       "      <td>0.121141</td>\n",
       "      <td>0.116460</td>\n",
       "      <td>0.148944</td>\n",
       "      <td>0.181698</td>\n",
       "      <td>-0.219230</td>\n",
       "      <td>-0.044633</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.008276</td>\n",
       "      <td>0.148998</td>\n",
       "      <td>0.524364</td>\n",
       "      <td>0.353619</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.478417</td>\n",
       "      <td>-0.043137</td>\n",
       "      <td>0.099130</td>\n",
       "      <td>-0.155093</td>\n",
       "      <td>-0.266799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DiffWalk</th>\n",
       "      <td>0.224239</td>\n",
       "      <td>0.223618</td>\n",
       "      <td>0.144672</td>\n",
       "      <td>0.040585</td>\n",
       "      <td>0.197078</td>\n",
       "      <td>0.122463</td>\n",
       "      <td>0.176567</td>\n",
       "      <td>0.212709</td>\n",
       "      <td>-0.253174</td>\n",
       "      <td>-0.048352</td>\n",
       "      <td>...</td>\n",
       "      <td>0.007074</td>\n",
       "      <td>0.118447</td>\n",
       "      <td>0.456920</td>\n",
       "      <td>0.233688</td>\n",
       "      <td>0.478417</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.070299</td>\n",
       "      <td>0.204450</td>\n",
       "      <td>-0.192642</td>\n",
       "      <td>-0.320124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sex</th>\n",
       "      <td>0.031040</td>\n",
       "      <td>0.052207</td>\n",
       "      <td>0.031205</td>\n",
       "      <td>-0.022115</td>\n",
       "      <td>0.042950</td>\n",
       "      <td>0.093662</td>\n",
       "      <td>0.002978</td>\n",
       "      <td>0.086096</td>\n",
       "      <td>0.032482</td>\n",
       "      <td>-0.091175</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.019405</td>\n",
       "      <td>-0.044931</td>\n",
       "      <td>-0.006091</td>\n",
       "      <td>-0.080705</td>\n",
       "      <td>-0.043137</td>\n",
       "      <td>-0.070299</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.027340</td>\n",
       "      <td>0.019480</td>\n",
       "      <td>0.127141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>0.185026</td>\n",
       "      <td>0.344452</td>\n",
       "      <td>0.272318</td>\n",
       "      <td>0.090321</td>\n",
       "      <td>-0.036618</td>\n",
       "      <td>0.120641</td>\n",
       "      <td>0.126974</td>\n",
       "      <td>0.221618</td>\n",
       "      <td>-0.092511</td>\n",
       "      <td>0.064547</td>\n",
       "      <td>...</td>\n",
       "      <td>0.138046</td>\n",
       "      <td>-0.119777</td>\n",
       "      <td>0.152450</td>\n",
       "      <td>-0.092068</td>\n",
       "      <td>0.099130</td>\n",
       "      <td>0.204450</td>\n",
       "      <td>-0.027340</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.101901</td>\n",
       "      <td>-0.127775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education</th>\n",
       "      <td>-0.130517</td>\n",
       "      <td>-0.141358</td>\n",
       "      <td>-0.070802</td>\n",
       "      <td>0.001510</td>\n",
       "      <td>-0.103932</td>\n",
       "      <td>-0.161955</td>\n",
       "      <td>-0.076009</td>\n",
       "      <td>-0.099600</td>\n",
       "      <td>0.199658</td>\n",
       "      <td>0.110187</td>\n",
       "      <td>...</td>\n",
       "      <td>0.122514</td>\n",
       "      <td>-0.100701</td>\n",
       "      <td>-0.284912</td>\n",
       "      <td>-0.101830</td>\n",
       "      <td>-0.155093</td>\n",
       "      <td>-0.192642</td>\n",
       "      <td>0.019480</td>\n",
       "      <td>-0.101901</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.449106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Income</th>\n",
       "      <td>-0.171483</td>\n",
       "      <td>-0.171235</td>\n",
       "      <td>-0.085459</td>\n",
       "      <td>0.014259</td>\n",
       "      <td>-0.100069</td>\n",
       "      <td>-0.123937</td>\n",
       "      <td>-0.128599</td>\n",
       "      <td>-0.141011</td>\n",
       "      <td>0.198539</td>\n",
       "      <td>0.079929</td>\n",
       "      <td>...</td>\n",
       "      <td>0.157999</td>\n",
       "      <td>-0.203182</td>\n",
       "      <td>-0.370014</td>\n",
       "      <td>-0.209806</td>\n",
       "      <td>-0.266799</td>\n",
       "      <td>-0.320124</td>\n",
       "      <td>0.127141</td>\n",
       "      <td>-0.127775</td>\n",
       "      <td>0.449106</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>22 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Diabetes_012    HighBP  HighChol  CholCheck       BMI  \\\n",
       "Diabetes_012              1.000000  0.271596  0.209085   0.067546  0.224379   \n",
       "HighBP                    0.271596  1.000000  0.298199   0.098508  0.213748   \n",
       "HighChol                  0.209085  0.298199  1.000000   0.085642  0.106722   \n",
       "CholCheck                 0.067546  0.098508  0.085642   1.000000  0.034495   \n",
       "BMI                       0.224379  0.213748  0.106722   0.034495  1.000000   \n",
       "Smoker                    0.062914  0.096991  0.091299  -0.009929  0.013804   \n",
       "Stroke                    0.107179  0.129575  0.092620   0.024158  0.020153   \n",
       "HeartDiseaseorAttack      0.180272  0.209361  0.180765   0.044206  0.052904   \n",
       "PhysActivity             -0.121947 -0.125267 -0.078046   0.004190 -0.147294   \n",
       "Fruits                   -0.042192 -0.040555 -0.040859   0.023849 -0.087518   \n",
       "Veggies                  -0.058972 -0.061266 -0.039874   0.006121 -0.062275   \n",
       "HvyAlcoholConsump        -0.057882 -0.003972 -0.011543  -0.023730 -0.048736   \n",
       "AnyHealthcare             0.015410  0.038425  0.042230   0.117626 -0.018471   \n",
       "NoDocbcCost               0.035436  0.017358  0.013310  -0.058255  0.058206   \n",
       "GenHlth                   0.302587  0.300530  0.208426   0.046589  0.239185   \n",
       "MentHlth                  0.073507  0.056456  0.062069  -0.008366  0.085310   \n",
       "PhysHlth                  0.176287  0.161212  0.121751   0.031775  0.121141   \n",
       "DiffWalk                  0.224239  0.223618  0.144672   0.040585  0.197078   \n",
       "Sex                       0.031040  0.052207  0.031205  -0.022115  0.042950   \n",
       "Age                       0.185026  0.344452  0.272318   0.090321 -0.036618   \n",
       "Education                -0.130517 -0.141358 -0.070802   0.001510 -0.103932   \n",
       "Income                   -0.171483 -0.171235 -0.085459   0.014259 -0.100069   \n",
       "\n",
       "                        Smoker    Stroke  HeartDiseaseorAttack  PhysActivity  \\\n",
       "Diabetes_012          0.062914  0.107179              0.180272     -0.121947   \n",
       "HighBP                0.096991  0.129575              0.209361     -0.125267   \n",
       "HighChol              0.091299  0.092620              0.180765     -0.078046   \n",
       "CholCheck            -0.009929  0.024158              0.044206      0.004190   \n",
       "BMI                   0.013804  0.020153              0.052904     -0.147294   \n",
       "Smoker                1.000000  0.061173              0.114441     -0.087401   \n",
       "Stroke                0.061173  1.000000              0.203002     -0.069151   \n",
       "HeartDiseaseorAttack  0.114441  0.203002              1.000000     -0.087299   \n",
       "PhysActivity         -0.087401 -0.069151             -0.087299      1.000000   \n",
       "Fruits               -0.077666 -0.013389             -0.019790      0.142756   \n",
       "Veggies              -0.030678 -0.041124             -0.039167      0.153150   \n",
       "HvyAlcoholConsump     0.101619 -0.016950             -0.028991      0.012392   \n",
       "AnyHealthcare        -0.023251  0.008776              0.018734      0.035505   \n",
       "NoDocbcCost           0.048946  0.034804              0.031000     -0.061638   \n",
       "GenHlth               0.163143  0.177942              0.258383     -0.266186   \n",
       "MentHlth              0.092196  0.070172              0.064621     -0.125587   \n",
       "PhysHlth              0.116460  0.148944              0.181698     -0.219230   \n",
       "DiffWalk              0.122463  0.176567              0.212709     -0.253174   \n",
       "Sex                   0.093662  0.002978              0.086096      0.032482   \n",
       "Age                   0.120641  0.126974              0.221618     -0.092511   \n",
       "Education            -0.161955 -0.076009             -0.099600      0.199658   \n",
       "Income               -0.123937 -0.128599             -0.141011      0.198539   \n",
       "\n",
       "                        Fruits  ...  AnyHealthcare  NoDocbcCost   GenHlth  \\\n",
       "Diabetes_012         -0.042192  ...       0.015410     0.035436  0.302587   \n",
       "HighBP               -0.040555  ...       0.038425     0.017358  0.300530   \n",
       "HighChol             -0.040859  ...       0.042230     0.013310  0.208426   \n",
       "CholCheck             0.023849  ...       0.117626    -0.058255  0.046589   \n",
       "BMI                  -0.087518  ...      -0.018471     0.058206  0.239185   \n",
       "Smoker               -0.077666  ...      -0.023251     0.048946  0.163143   \n",
       "Stroke               -0.013389  ...       0.008776     0.034804  0.177942   \n",
       "HeartDiseaseorAttack -0.019790  ...       0.018734     0.031000  0.258383   \n",
       "PhysActivity          0.142756  ...       0.035505    -0.061638 -0.266186   \n",
       "Fruits                1.000000  ...       0.031544    -0.044243 -0.103854   \n",
       "Veggies               0.254342  ...       0.029584    -0.032232 -0.123066   \n",
       "HvyAlcoholConsump    -0.035288  ...      -0.010488     0.004684 -0.036724   \n",
       "AnyHealthcare         0.031544  ...       1.000000    -0.232532 -0.040817   \n",
       "NoDocbcCost          -0.044243  ...      -0.232532     1.000000  0.166397   \n",
       "GenHlth              -0.103854  ...      -0.040817     0.166397  1.000000   \n",
       "MentHlth             -0.068217  ...      -0.052707     0.192107  0.301674   \n",
       "PhysHlth             -0.044633  ...      -0.008276     0.148998  0.524364   \n",
       "DiffWalk             -0.048352  ...       0.007074     0.118447  0.456920   \n",
       "Sex                  -0.091175  ...      -0.019405    -0.044931 -0.006091   \n",
       "Age                   0.064547  ...       0.138046    -0.119777  0.152450   \n",
       "Education             0.110187  ...       0.122514    -0.100701 -0.284912   \n",
       "Income                0.079929  ...       0.157999    -0.203182 -0.370014   \n",
       "\n",
       "                      MentHlth  PhysHlth  DiffWalk       Sex       Age  \\\n",
       "Diabetes_012          0.073507  0.176287  0.224239  0.031040  0.185026   \n",
       "HighBP                0.056456  0.161212  0.223618  0.052207  0.344452   \n",
       "HighChol              0.062069  0.121751  0.144672  0.031205  0.272318   \n",
       "CholCheck            -0.008366  0.031775  0.040585 -0.022115  0.090321   \n",
       "BMI                   0.085310  0.121141  0.197078  0.042950 -0.036618   \n",
       "Smoker                0.092196  0.116460  0.122463  0.093662  0.120641   \n",
       "Stroke                0.070172  0.148944  0.176567  0.002978  0.126974   \n",
       "HeartDiseaseorAttack  0.064621  0.181698  0.212709  0.086096  0.221618   \n",
       "PhysActivity         -0.125587 -0.219230 -0.253174  0.032482 -0.092511   \n",
       "Fruits               -0.068217 -0.044633 -0.048352 -0.091175  0.064547   \n",
       "Veggies              -0.058884 -0.064290 -0.080506 -0.064765 -0.009771   \n",
       "HvyAlcoholConsump     0.024716 -0.026415 -0.037668  0.005740 -0.034578   \n",
       "AnyHealthcare        -0.052707 -0.008276  0.007074 -0.019405  0.138046   \n",
       "NoDocbcCost           0.192107  0.148998  0.118447 -0.044931 -0.119777   \n",
       "GenHlth               0.301674  0.524364  0.456920 -0.006091  0.152450   \n",
       "MentHlth              1.000000  0.353619  0.233688 -0.080705 -0.092068   \n",
       "PhysHlth              0.353619  1.000000  0.478417 -0.043137  0.099130   \n",
       "DiffWalk              0.233688  0.478417  1.000000 -0.070299  0.204450   \n",
       "Sex                  -0.080705 -0.043137 -0.070299  1.000000 -0.027340   \n",
       "Age                  -0.092068  0.099130  0.204450 -0.027340  1.000000   \n",
       "Education            -0.101830 -0.155093 -0.192642  0.019480 -0.101901   \n",
       "Income               -0.209806 -0.266799 -0.320124  0.127141 -0.127775   \n",
       "\n",
       "                      Education    Income  \n",
       "Diabetes_012          -0.130517 -0.171483  \n",
       "HighBP                -0.141358 -0.171235  \n",
       "HighChol              -0.070802 -0.085459  \n",
       "CholCheck              0.001510  0.014259  \n",
       "BMI                   -0.103932 -0.100069  \n",
       "Smoker                -0.161955 -0.123937  \n",
       "Stroke                -0.076009 -0.128599  \n",
       "HeartDiseaseorAttack  -0.099600 -0.141011  \n",
       "PhysActivity           0.199658  0.198539  \n",
       "Fruits                 0.110187  0.079929  \n",
       "Veggies                0.154329  0.151087  \n",
       "HvyAlcoholConsump      0.023997  0.053619  \n",
       "AnyHealthcare          0.122514  0.157999  \n",
       "NoDocbcCost           -0.100701 -0.203182  \n",
       "GenHlth               -0.284912 -0.370014  \n",
       "MentHlth              -0.101830 -0.209806  \n",
       "PhysHlth              -0.155093 -0.266799  \n",
       "DiffWalk              -0.192642 -0.320124  \n",
       "Sex                    0.019480  0.127141  \n",
       "Age                   -0.101901 -0.127775  \n",
       "Education              1.000000  0.449106  \n",
       "Income                 0.449106  1.000000  \n",
       "\n",
       "[22 rows x 22 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "ce5f9d97",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20, 12))\n",
    "sns.heatmap(df.corr(), annot = True, cmap = \"Blues\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ce3efdcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# Check for null values\n",
    "sns.heatmap(df.isnull(), cmap = \"Blues\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "088a6467",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Diabetes_012            0\n",
       "HighBP                  0\n",
       "HighChol                0\n",
       "CholCheck               0\n",
       "BMI                     0\n",
       "Smoker                  0\n",
       "Stroke                  0\n",
       "HeartDiseaseorAttack    0\n",
       "PhysActivity            0\n",
       "Fruits                  0\n",
       "Veggies                 0\n",
       "HvyAlcoholConsump       0\n",
       "AnyHealthcare           0\n",
       "NoDocbcCost             0\n",
       "GenHlth                 0\n",
       "MentHlth                0\n",
       "PhysHlth                0\n",
       "DiffWalk                0\n",
       "Sex                     0\n",
       "Age                     0\n",
       "Education               0\n",
       "Income                  0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "511ad455",
   "metadata": {},
   "source": [
    "# No null values found!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0fdef499",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'Diabetes_012'}>,\n",
       "        <AxesSubplot:title={'center':'HighBP'}>,\n",
       "        <AxesSubplot:title={'center':'HighChol'}>,\n",
       "        <AxesSubplot:title={'center':'CholCheck'}>,\n",
       "        <AxesSubplot:title={'center':'BMI'}>],\n",
       "       [<AxesSubplot:title={'center':'Smoker'}>,\n",
       "        <AxesSubplot:title={'center':'Stroke'}>,\n",
       "        <AxesSubplot:title={'center':'HeartDiseaseorAttack'}>,\n",
       "        <AxesSubplot:title={'center':'PhysActivity'}>,\n",
       "        <AxesSubplot:title={'center':'Fruits'}>],\n",
       "       [<AxesSubplot:title={'center':'Veggies'}>,\n",
       "        <AxesSubplot:title={'center':'HvyAlcoholConsump'}>,\n",
       "        <AxesSubplot:title={'center':'AnyHealthcare'}>,\n",
       "        <AxesSubplot:title={'center':'NoDocbcCost'}>,\n",
       "        <AxesSubplot:title={'center':'GenHlth'}>],\n",
       "       [<AxesSubplot:title={'center':'MentHlth'}>,\n",
       "        <AxesSubplot:title={'center':'PhysHlth'}>,\n",
       "        <AxesSubplot:title={'center':'DiffWalk'}>,\n",
       "        <AxesSubplot:title={'center':'Sex'}>,\n",
       "        <AxesSubplot:title={'center':'Age'}>],\n",
       "       [<AxesSubplot:title={'center':'Education'}>,\n",
       "        <AxesSubplot:title={'center':'Income'}>, <AxesSubplot:>,\n",
       "        <AxesSubplot:>, <AxesSubplot:>]], dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 25 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# EDA\n",
    "# Display all columns in histogram format\n",
    "df.hist(figsize = (20,20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b733d337",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Checking distribution of target variable\n",
    "sns.countplot(data = df, x = 'Diabetes_012')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "dacc7748",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Diabetes_012'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qzeUaRqaYzYVsklJiU0o1pSuQXjgIUM7CYSaxGQOFSWw2SXWuaLGIVInIChHZYT0+tI4NSVOMnUqBNqfPPyLN5RpGpkwyE+Ltkepwj38CO4E5SqnhSqnh6G7uncC/Ug2uh4OBdkdegUlsxkDhRC+IamRZqoktoJS6Tim1pfOAUmqLUuo6YEKKZX/MV1ruA4qcRSPcZhlwY4AxzVEbpJrY1orIVSLy8X0vERklIj8B1qdYdlfDgbh76BgzzMMYaNK2tJbRe6kmtnPQSWe+iDSJSBPwCjCM9K4kOhxwOPL9BWks0zCyYS/LLhuZlGqv6E7gJ9Zjr0TkYqXU/SlcqhgQR16BSWzGQGMSmw2ytefBD1I8fygQc+T5fOkIxjCyaKTdAQxG2Upsqa6mOxSIiiff1NiMgcbU2GyQrcSW6tpIQ4Cow+01NTZjoDGJzQYDpcY2BIiKSWzGwDM8UFlj9lPMsmwltjdSPN8PRMXpzk9HMIaRRS70+9fIorQkNhH5gYj4RbtbRN4Vkc90Pq+UOuCt+KzlioqAqNlJ2BigUl1swuijdNXYvqaUagE+g76ncClQlaayXeipKYk0lWcY2WYSW5al6x+8syZ1OnCvUuo9MbWrAUUlYlFUyp08xm4CKHG6ImTvlo9hSVdie0dEnkfvSfBTESnC1LAGlPCmujdaah+fb3ccOSQfSATra39qdyCDUboS29eBGcBqpVRQRIajm6PGAJE3duqJ7pJAU7SxYc/doI0D4QBW2R3EYJWuxKbQyyB/HvgNUACkax0q0zzKAnE4HENOOG/SjuduqUh0tJjadnq02R3AYJWuxHYbuul5MjqxtQKPA7PSVL6WqU1QDQDE4Zox4vQrLmyoqrjO7ljSRUTuQX/gblNKTUvyfDHwd/QyWy7gT0qpe0XEC7wK5FnHH1NK/co65zrgNGCJUuoi69iFwDCl1E1Z+LWM/UhXYitXSh0lIotBT44XEU+ayv6Yikc70l2msYd5gcqapxqqKur6ctL0+6c70ftSjEcniWGkPjA7ZWPOH9Ps8Dnu2fLwloum3z99j2FHRUcVfSYRSngnXjXxztCGUOGqeatuOeyOw/yH33N4PNYce8Q91B1JhBKOjyo/+uG4S8cVFB5euMU9zH1W2fVlN6785cqLJ3xnwjUFUwsa3SPcl5X+rvTWZNdIg9eXXrx0SQbKzVnpSmxREXFiNRtFpIT0dR58XE4iGmpPU5nG3nmBewKVNZ9sqKrY7/+hf6Y/Dz2XFyCCvq+0Kn9ifn7B1IJxrmLXWIfXMc7hdowTp4zFyThxyFiEcSKS8QHXwz89nEhjBFexC+AvPZ/3TfIRbYqilDrVkefAPcyNI89xozgE91BrQzQBV7EL73jv/zkLnbiGuFBK/cVT4sF7kPeYppeaGHPeGBxeR6Zqa1cCSzJUdk5KV2K7GXgSGCkiv0fvXvWLdBQcrK9N+ErLg4BLRULBdJRp7NdxwPeA3vyhjkXvITsc3WzLA7wdazryOtZ0dA5zSKB3MwsC9dYDZ5Ezzz3MXegqdhW4il2FrkJXgbPAWej0OQsc+Y5CR57DJ47MDhsadsow1t20jror6kiEEoz/9njEoS+pEopVv1pFZFuEYacMw3eIntHnP8bPql+uouCwAhw+Bx2rOxh5RkYX8ehVJUFE4sBS9N/1h8DFSqkD+puxts/8JtCIvme+FPi5Umq59fxdwPWdP++ljAbgGKXU9l5ecw4Q6dzOU0QuA4JKqQf6Gn9aEptS6iEReQc4Bd38OFMp9WE6yrY0A55EJGhqbNlzTaCy5pn97WTesrhlDXCNf6a/c+pQcZfHSGC09XUEujaYQNfsJd4aj8Zb41vRSS9sPXb/ETsQzwhPkXu4u9g1xFXsKnL5nQXOYqfPWezwOoodXoff4XakNH+4bVkb3gleAj8JENkWoeGPDUwum4wz34k4hMm/nUy8Pc66v6wjtCGE9yAvJaeXUHK6ntu+8Z6NjPzSSJrmN+myxnsZOTftSS7ZhuTJdCilZgCIyEPAZcD1nU+KiFMpFe/DdW9QSv3JOvcc4CURma6UalRKfaMP5fTWHHSHy5sASqk7DrSgtCQ2EXlQKXUhsCLJsXRoBkarsElsWeQD7gxU1pzaUFWx706becWzWs4QgHVAA/Oa93i9f6Zf0LW5zqTnRzdhRwOj0DNWxqKHSejklsAR2RZRkW2REPo9EEY3dz8u35HncHlKPMXu4e5il9/ldxbpxGclP78jz1EM7HWT7Z2v7aSkogQRIW9UHp4SD+HNYXyTdudLZ4GTgkMLaFvahveg3Z39HWv1Ld+80Xlsfmgzk342ifW3rSe8JUze6LRuzXEgvauvAUdYtaBfAZuBGSIyHT0raA76/+NWpdRf91eYUupREakAzgNuEpFXgB8ppRaJyO3ojsJ8unSyWH4sIidZ35+nlFpp3aq6g937olwBbEQn4riIXIBuMZwCtCml/iQik61zSoA4cLZSaq/DadLVFO22YYV1v+3oNJUNsAsYHw+1mcSWXScD3wKSvvHnlrk9QKz6XF8B8BK6th5mXvEG9J4X6zq/tpwhnT+vY17z1mTlWcmvkN2Jrxhd0xuNfkOXoJOgsh6SCCccoQ2haGhDqBnYhq79xXoUPSraFD1n52s7n3MVu4qdBc5iZ4FOfK4i1+i2D9rcBWUFEmuOEd4cxlPiIdYSQ5yCs8BJIpKgbXkbI07vvkHatie2MfaSsaiY2l3PdEAikvbRMq19ebGIuNC9ts9Zh2YD05RSa0TkW0CzUmqWiOQBb4jI80qpNb0o+l3g0CTHr1ZKNVl/9y+KyBFKqfet51qUUrNF5CLgRnQP9U3o2uDrIjIB+K9SaqqI3IGVyKzf45Qu13gIqFJKPWn1WO9zNkdKiU1Efgr8DMgXkRZ294JFgL+lUnYPOwFPoqPFJLbs+0OgsubZhqqKZJvz/AA4bO7DwaZrTsmrnTbSeSy6FnCI9UhuXnEzPRIfsL7lDOn8eQPzmjckO7VLk7drs3cUurk7Cp0I89Gf6gTrgyfFQ/ExxMnbeN/GL7iHu18nQTOwy3uQd1G8I17UsqjlzB3/3eHHgbPoyKL60LpQc7QpOrrxmcYpOHAiOIccO0T8M3Yv0tHyTgv5E/M/7mDIn5xP/c/r8R7kJX9C2vtEejtoOl9Elljfvwbcjb5f+naXxPUZdE3uy9bPxeg9e3uT2PZ2v/MrVsJ0AWPQY1o7E9vDXb7eYH1/KnBYl1mXfmu2UvKL6ufGKaWeBFBKhfYXaKp7HlwLXCsi1yqlMjl1pAlwxXZt7tVNSCOt/Oga2+lJnpsPHAFEr3s9/M6tFfnT/HlS2IsyOxPSHuPKLIp5xVvpkfjoXvNbm6zJC+Cf6fdacRf7Sn13oJu8Xe/3DUd/4h/kzHdSMLVgProGGE6EEqEdL+wIA5G8sXkflx/aGHJteWyL3z3Uut9X6PL7j/EXR3ZEip1eZ/Hos0f75avpH+Jk6W1i+/geWycreXStEAjwPaXUf3u87vdABUDPMrqYCSzqcd5E4EfALGuY1310H5yvknzvAD6hlOo2fGsf08v73IGUrqbo1Va7eKJS6rciMh4Yo5R6O03ltwLE25qCKhbpEJfHrMuWXacFKmsubqiq6Lkhz0L0G/2w5jCbH10WfeqbR3suSMP1BJ2ERqObUclEujR5kye/ec31yU60mrwFdO/oGEb3+33dmrwqohzhDeFYeEO4Bd1TuEeT11nk9HpKPMXuodb9vkLrXl++1dHhcfjFIQcyIb7xAM7Zm/8C3xaRl5RSURGZAmxUSl0NXL23k0TkLHRt7/96POVHJ85maxvO09A71XU6B31P7xxggXXseeC7wB+tsmcopZag/873WLtOKdUiIhtE5Eyl1FNWE9q5rx7fdCW2W9k98+C36Judt5K+mQdNWNk+EW7f7nR5xqepXKP3bghU1vy3oari482xq+uiam6Z+0HgWiD/mY9iq46f4FxyWIlzRhbi8QCTrEdy84pb2Ffi003ejclOtZq8RXS/39ezl9dH915eR0drR7iDjkbrWt17eQVxD3cXekZ4il3FLr/Lb93v08nP78hzFItbCnrUXKLoe4fpchcQAN61VuBpBM7cy2uvtCosBcAy4GSlVLcka63ksxj4AFjNnovK5olILbqWdq517PvArSLyPjoHvYruOHgGeExEzkB3HnR1IfBXEfkN+t/kbOt6SUk6ZimJyLudMw+UUjOtY+8ppY5MuXDAV1o+FPgTsH7IiRfP9ZQcPDMd5Rp99mRDVcWXeh6cW+Y+Ht3JsGaET7y3nO79js/dqyap3RQ6aexxv6/L1837aPJ29vJ2Jr6h6JpeZ61vOPoPt0vXgm7ysnuIS7deXnGL0zPSU+wa4hrpHur2Fh9T/PLSi5eaaVp9lK7EVou+SbnQSnAlwPOdSS5VvtJyB7qrd2vRzIpj8icd/bl0lGsckHMaqir+2fXA3DK3Az06vhTYctZUV9nFMzxftSW69IuihyLsLfGtY17zrmQndmnydu3oGM7uWl8Jej+Pj5u86OQXQw9RebdlccvNmfm1clu6Etv56Db00cB96JkHP1dK/Svlwi2+0vJ5QJE3MHOY/+gvXJKuco0+2wYc3lBV0a0jZ26ZuwS4BtgOhP/0mbyzpgx37q1zINe0kqTJ2+3rvOakg2z9M/1Odjd5Ox8l6OT3dsvilkXJzjP2LS2JDUBEDkUPqAN4Kc0zD/CVlp8PnOjI9+8ccfoV+9x53si4hxuqKs7reXBumXsOeh2+NWMKxXfTad7veF1idhbTtbHO+277avKa5aLSJJ1rsfvQexMo9DiidFsDnJLoaAklQu3bHd6CEfs9w8iUcwOVNY80VFVU9zj+GnAscPDmNrX1qRWxZ786zf3lJOcPNoJueo5k7wPXo8wr3kT3ZPcc85pfyUqEOSZdu1T9Ergf3WU+ArhXRH6ejrK72IJ1kzXWsrU3gwmNzLo9UFkzpOuB6rpoHH0rwg14/rE0+sHqnYkVSc419uQGDgZOQE9b+gn6vrVxANK1ycS56AF686x5YscC56ep7E4b0YnNEdm+riHNZRt9N5YuE6w7VddFtwCPWM9z/YJwTTi2/5HiRlJmafEDlK7E1kD30cZ5pPk/JVhfGwZWAv7w+mUNZjHdfuHSQGXNZ5IcfwX9/1+yrlm11dTHnkvyGmP/9rmyirF3KSU2EfmLiNyMHo/zgYjcJyL3ogfzZWK993cAf7ytKZgItaVz0KJx4O4MVNZ0m+dXXReNAfeg77W671sSfW/trsRKW6Ib2ExiO0Cp1tgWoZPNk+jJ8C+jP62vBv6TYtnJrObj+2zbzH22/mECsMceCdV10Y3AY1hN0ptqI89E4iqS5dgGLKXUduY177A7joEq1UnwPecOZto69ChuZ7SxYU3eqEPKs3x9I7nLApU1jzZUVfTcl/QF9P3WESubEtufXxV74fNT3BU2xDfgiMiC/b/K2Jt09YqWishjIrJcRFZ3PtJRdlfB+too8BHg71izeLVKxKPpvoZxQAS4O1BZ023MWnVdNIqem1gAuO58J7poY0uiwYb4BqI37Q5gIEtX58G9wO3oqSAnAQ8AD6ap7J7eBYpUJBiN7dryUYauYfTdIcDveh6srouuA54Gxing5tpIdSyhzAfS/vWcTG70QboSW75S6kX0TIa1Sql56JU+MmEZ1vpM4U11yzJ0DePA/CBQWXNskuPPoschDvtwe2LnS2viL2U5rgFFKRVFLwllHKB0JbaQiDiAehH5roh8ET3KOhM6V2Pwd6x6u17Fo73d6MLIPAd6675uC/5X10UjwJ3oyeDO2xZGare0JZKtyGto7zKv2Yz9S0G6EtsV6ClV30dPGbkQuDhNZXcTrK9V6N7XISoWiUd3bjYj2/uXqejNQ7qprouuBmqAcQmFuvXtyNOxhOq5N4EBiIi5v5aitCQ2pdRCpVSbUmqDUupSpdSXlFJvpaPsvehcT13CGz80zdH+58eBypqjkhx/Br36x5D3tiZ2vLY23rMX1dDM/bUUpTpA90br6zMiUt3zkZYIkwjW1+5Aj2wv7li9aHUiFjGbvPQvLnSTtNu2d9V10RC6l3Qo4PzL25E3GtsTm+wIsJ8zNbYUpVpj6+z5/BPw5ySPTJoP+EnEE5Gtq97J8LWMvjsS2GODn+q66EfodffHxRKoOxZFno4nVK+X6/na0x2M/GMr027bPbHlFy+FOOL2Nmbc0cZnHmxnU2vy4m56K8y029o4/LY2bnwrvN/z31gX44jb25h1Zxsrm/SxXSHFZ//eTqam9CmlVjGveXNGCh9EUkpsSql3rK/zgeXAcqXU/M5HOgLch6XoWQjO9uWvLFSJRF92uDay4+pAZU2yxSafQu+85F+4KbFtwYb4a70t8JIZbp67oPsSbz8+Po/3v13IkssK+fwUF7+Zv2d/0rJtce58N8rb3yzgvcsK+PdHMep3xPd5/p8XRHj8K/lcc7KX2xfqSRO/nR/mZyfk7WtHpZSIyOMZKXiQSbUpKiIyT0S2o3eB/0hEGq1ljDIqWF/bjK6yj4y3NLZFd24099r6Hw+6SerserC6LhpE73k5HHDc+Fbk1aYO1au5vyce7GJYfvek4s/b/XN7JPlebR82Jjj2ICc+t+ByCJ862MWTK2L7PN/thI4YBKMKtxNWNSXY2JrgU4F0LmO4h4f3/xJjf1Jtil4BHI9esmi4UmooUA4cLyJXphpcL/wPvZIIHR8tyGRnhXHgZrHnlm1U10WXo3ePHxuJk7jznchTiRTad1e/GGL8Da08tDTKb07K2+P5aSMdvLo2zo5ggmBU8ezKGOu7LFib7PyfnpDHt54JcWNthO/O9nD1SyF+m6TsdInG1UrmNS/J2AUGkVQT20XAuV12mUYptRq4wHou09ahp1gNC29asSXW1rQ2C9c0+u7XgcqaKUmOP47ek7LojfXxzQs3xg/4pvnvT/Gy/soizp/u5pa395xrP7XEyU+O9/DpB4N87u9BjhzlwOWQfZ4/Y7STt75RwMsXF7B6Z4KxRQ4UcM5jQS54ooOtbeldydvl4O9pLXAQSzWxuZVSe+zObu096E7y+rSyxrTVoDfDINSw2Ewc7p+86CZpt/dbdV20Dd0kHQHIDW9FXtkV2vP91BfnTXfz+IfJh8d9/SgP7/6/Ql69tIBh+ULp8D3f/snOV0rxu1fD/OLEPH49P8yv5+RxwRFubq5N72IlImKaoWmSamLb1/9stpaoWYbeULkg+NGbHyVCbSn9YRgZczx69++elgKvA+OCUWL3Lo5U97VJ2tkJAFBdF+PQEcnf1tvadQ1rXXOCJz6Mce40d6/Ov/+9KBWlLobmC8EoOEQ/gmmc8RqNq6XMazZzn9MkpV2qRCSObkrs8RTgVUplvNYG4CstPwnd9F3rO/STUwsPP+kr2biu0WftwPSGqopua+nNLXP70Vv3dQDt8+bkfe6oMc6kS1Kd+3iQVxribA8qRhUIv56Tx7MrY9RtT+AQOHiIgzsqvIzzO9jUmuAb1SGePV/3on7y3nZ2BHVHwPWf8XLKJN0JcNY/g0nPB91xUPGPIM9f4MPtFF5bG+PyZ0N4nPDwWflMGe5MFmafKaWukl+3/DEthRnp237PTr7Sch/wR/SqvR3DT/vBN52+4rE2h2Uk92JDVcWpPQ/OLXMfhe6MWlPkwXX75/O/7c+ToVmPzgZKKSUiBzOv2cyfTZN0zRW1VbC+Ngg8gTXxPlj3xov2RmTswymByppvJjm+GKgFxrRGiP79/Wh1Lnzo9kYswVsmqaVXTiQ2y+tAC1DQsXrR6ljzNrPGfv/1p0BlzUFdD1TXRRXwEHpNP99zK2MNS7clBsWMErdTrrU7hlyTM4nN2sXqEaAEoG3pC8+rwfKRP/D4gTt6Hqyui+5C7087GpA/vxl+vi2iWrIcW1Z1RNUq4N92x5FrciaxWd4GNgBDI1tXNUa3rVlkd0DGXlUEKmsuTHL8bfQGQaN3hog8siz6TJbjyrbfMK/ZfACnWU4ltmB9bRzdnBkCSMuip19MREI5/Yk/wN0YqKwZ1fWA1STtHKiaX10XW7m8Mf5e9kPLvFBMbc53y0N2x5GLciqxWVZgfeInQq3h9g/n5/on/kA2DLit58HquugO9MoxowGuXxB5LhhVmdin1lbxBNcyr9ks3pABOZfYrNkInZ+C3o6VtSujO9a/v69zDFt9KVBZc3aS42+iB1+P3tauQo8tj9ZkOa6MisRVU4FH/mZ3HLkq5xIbfLwQ5YPAGIDmt5/4TyIazrlP/BxyS6CyZnjXA9V10QS6I8EJ5D22PLaifkf8A1uiy4BInBuZ12z268iQnExsls5P/FGJYHMoWPdGTn3i55iRwM09D1bXRbcB/8DaTf7PCyLPhmIqmOXY0i4aV+2FHrnB7jhyWc4mtmB9becnvgvIC9a9viLaZNZs68fOC1TWfCHJ8VfR901HbmpVwadXxP6T5bjSLhjleuY1mxZEBuVsYgMI1tduQy/cNxagecGjzyRC7TvsjcrYhzsClTXFXQ9U10XjwH3odfc8Dy2NLluzM1FnR3Dp0BZRW4u9ssfG0kZ65XRis8wHPgRGJ0JtkZZFTz2q4rFsrTxi9M1Y4PqeB6vropuBR4FxANcvCP87HFMDct/Nxnb1A+Y1m/dfhuV8YrPGtv0NiAL+yNZVjcG6NzK2g5aRsq8FKms+neT4S+idyUrWNqu2Z+tj/81yXCnb1p54e+JNrY/aHcdgkPOJDSBYX9sE/AU9bsrT/uH8D8Jb6s1S4v3XnYHKmsKuB6rrojHgHiAfcN+7JLpkXXNilS3RHYBoXMWC0aysKm0wSBIbQLC+9iP0+LaDAGle8M8XYm1N62wOy0juYOC6nger66Ib0MuJjwO46a3IM5G4GhDNuvUt6ubAja37vTcoInERWSIiH4jIeyLyQxFxWM8dIyJ79B73OP8SEbmlL7GJyM96/Dzg9zUdNInN8iJ6GMhBJOKJ5jcf+WciHNxpd1BGUt8OVNacmOT488B6YER9U6L5hVWxF7IcV5/tCCbWt0fUVb18eYdSaoZS6nDg08DpwK8AlFKLlFLfz0CI3RKbUuq4DFwjqwZVYrOGgDwAbAVGxFu3tzcvePRBM3i3XxLg7kBlTX7Xg9V10Sh6N/lCwPW3d6KLNrUmGmyIr1fiCaUadqmLpt/e1uepU0qpbcC3gO9aW13OEZF/A4jIbBF5U0QWW1/Lupw6XkSeE5E6EflV50ERuUBE3rZqhH8VEaeIVAH51rGHrNe1dTnnKhFZatUeqw703yHbBlVig48XpfwL+g9nSHTH+p0tC5/8u4pHB2QvW46bDOwxNKK6LroWvenyOAXcXBupjiVUGncgSJ+VTYn7j/5b2ysHer6165sDaxHVLlYAJyqlZgK/RC+t3mk2cD4wAzjbasJOBc4BjldKzQDiwPlKqUp21xLP73oBETkNOBMoV0odCfzhQH+PbBt0iQ0gWF+7Gb2UuA8oimz+aGvr4mf/oRLx5NsbGXa6IlBZk2z/g/8AW4BhyxsTO19eE38py3Ht19pdiY/uWBRNtlpwXyXbA7oY+JeILANuAA7v8twLSqkdSqkO9MrSJwCnAEcDC0VkifXzpP1c91TgXqX0bA+lVFNKv0UWDcrEBhCsr21Aj5kaCvhCa99b37bsxX8qlUjvZpFGqhzorfu67VRcXRcNo5ukxYDz1oWR2q1tiQ12BJjMrpBq/fdHsS/e8FY4pQ9LEZmErl1t6/HUb4GXlVLTgC+gtzjs1HN9N4VOjvdbNbMZSqkypdS8/V0+SVkDwqBNbADB+toVwC3oan5eR/1b9cEVbzxpVt7tdw5DN7e6qa6Ldq4+Oy6hULcujDwdTyjblwGKxlX8f6tjl3/n2Y7lqZQjIiXolYZvSfKeLAY2Wt9f0uO5T4vIMBHJRzcl30B3nH1ZREZaZQ8TkYM7QxaRZDvKPQ98TUR8neek8vtk06BObADB+tp30Zv2jgPc7ctfXta+/JV/qUTC9j8Qo5urApU1M5McfwbYAQxZsiWx/bV18VeyG9aeXlsXv/OB96IHuoBk5438D4D/oZPLr5O87g/AtSLyBnoFlK5eR69uswR43OpNXQ78HHheRN4HXsBa/QY9gP39zs6DTkqp54BqYJHVfP3RAf5OWZcT2++lg6+0/HPAeeilxSP5h8w+pPCIT58jDmdW9kY1euU9YFZDVUW3joK5Ze4p6CEL690O1B2f936jpMAxJmkJGbZsW3zhz14MH2/13ho2GfQ1ti7+C9yLHsDr7Vj19qqWRdUPqFikw+a4jN2OBCp7Hqyui36ErtmMjSZI/PWd6NPxhMr6vdItbYltjy2PzjVJzX4msVmC9bUqWF/7MvqexhjAF16/dMOuNx+9OxHp2GVvdEYXPw9U1hye5PhT6O0X/W9vjG99a0P8tWwGFYyq8POrYl+Z90p4SzavayRnElsPwfraN9G9pcOB4mjjmh075993d7x9V7/pcRvkPOhe0m73larrokHgTvT/m+OGtyKvNnWonj2JGdERVZF/fhC98qInO+Zn43rG/pnElkSwvvY94Fr0GmAj4i2NbU0v3H5fZOvqhTaHZmizgSt7Hqyuiy4HXgbGReIk7n438nQiwzeRwzEVvevdyA1PfBj7ayavY/SNSWx7EayvXYke9R4Exqt4NLHr9b8/277i9SdUIm7uodjvN4HKmtIkxx8D2oGi19bFNy3alFiQqQAicRW7893IHS+sjv/K2qPB6CdMYtuHYH3tJnRX+2JgIuBu/+Clpc0LHr0rEW4fMKOwc1Q+ei5pt1H51XXRNvTwnRJArl8Qfrk5pNK+anI0ruJ3vxu9+/lV8auswcJGP2IS234E62vb0XtfPowe6+aPbFm5rel/f/tbdOfmD+2NbtD7JPCdJMffRw9KHRuMErt3SXqbpLGEit+3JPrAf1bGflhdZ+YY90dmHFsf+ErLD0X/IbnR8xQpOPzk6b7Js08Tlyd/nycbmdIGTG+oqmjoenBumduPvk8aBNp/PSfvtJljnLNTvVg8oRL3vxf9x1MrYpdV10XbUy3PyAxTY+sDawrWr4B1QADwtH/w0tKmF++8Jdq0MWf2vBxgCoFf9DxYXRdtQY9LHAXInxeE/9caVrtSuVAsoeJ/fz/6r6dWxC43Sa1/M4mtj6xlxv+AbpqOAkbG23YEd75892Nty158xKztlj1KJRKJSOhGkjdHAd4BaoGxLWGiD74fPeC9LtoiKnj9gsgDj38Y+1Z1XbT1QMsxssM0RVPgKy0fg56AfCiwCQg78v1e/6wvfto9YsJMEUm23IyRBrG2HRtb3/n3+9Hta38drK+t3dvr5pa5h6LXKmsFgr8/Oe8L00c5j+rLtTa3JrZf+3r4Hw271K+q66K7UovcyAaT2FLkKy13om9inwcksO69ecaUjSqcdvKpLn/JZDvjyzWJUNv29hWvLelYtfBD9H6ji4P1tft8E88tcx8LXA6sHpYvebee7r28wCP+3lxv6db4mqrXw7e3RrjNND8HDpPY0sRXWl4CXAgcAeyyHngnHh0oOPSETzt9xWPti27gS0TDbR2rFr7TvvyVBlTiJeCJYH1tr5r9c8vcAvwAmApsPqPMVfr1ozzn7escpRTPrYwtuX1R9BrgCWvjZmOAMIktjXyl5YJeyfRc9GT6RnSvHb6pJx7mO2TWKY68ggGzplV/oOKxSGj9snfb3v/vShUNLwb+FayvXd/XcuaWuYejm6Q7gdB1p+Z9cWqJ84hkr43EVfTexdFXa+pjvwQWVNdFzR/JAGMSWwZYzdNjgK+iV+jdAoRwOB0Fh82Z7p1wxHHO/KKea9gbXSSiodbwxhXvtX/w8oZEqLUOeASo21+zc1/mlrk/CXwTWD2yQLw3n+b9js8t3fYv3RVSLTcsCNcs3pL4ZXVddGVqv4VhF5PYMshXWp6HXm/+y+h5p9uAEED+5NmH5E88+hPOohGHmD6G3eLB5k0dDYvfC9a9sY1EfDu693mxtcNYSuaWuR3A/6HX+t969mGuQy880nNO5/Nvb4ytuLk28mRLmOur66LbU72eYR+T2LLAV1peCHwKqEBPBWpC99LhLgkM95UdP8sz4uAZ4nTl7aOYnKWUUrFdW1YEP3pzRXjDB83AZvTKuO8E62vTuiHy3DL3SOD3wHYgfP1n884eU+gYf9e7kbdfXBN/HLivui5q1uAb4ExiyyJfabkXvVPQGeh9FoLo+3BKPPlu3+TZUzxjpkxz+UdOFofTZWesmaaUIhHctT68ZeXyjvq3tsfbd0bRU6GeQzc5MzapfG6Z+2TgYmBNiU8OjiVgZ0jdibmfljNMYrOBr7TcAZShd/qeid4JaCdWLc7hLcrLnzy7LG906TSnf8QhIo6cGUgd72jZEtm6elnHytr1seatAsSAV4CXrUUHMm5umdsJ/ATdg/0OcK9peuYWk9hsZg0TmQmcBIxGJ7kd6KV3cPiKvfmTZpV5Royf5PSXBBxub6/GX/UXKhGPxdua1kabNq4KrV2yObp9XWdNrA6YD3wQrK/N+kj+uWXuEehpce+aJYdyj0ls/YQ1VGQMOsl9ChiBTnK70ENGFIB7+ISheeMODbiHHTTR6R8RcLi9RTaFnJRKxKPx9p0bYs1b10a2rVkXXre0VcWjPuvpBnQyez9YX7vTviiNXGcSWz9kJbnx6M1LjrG+V9ajma6JbthBQ9wjJox0+ktKXIXDRjry/SUOb8EIcbgyuruWUkqpcLAp3tGyLd6+szHe2rgt2rSxMbJtTZhEvIjdm+2uBBaik1ljJmMyjE4msQ0AvtLyAuBgYApwFHrwb+fu3iF0s7UDPaUL0AnPNWzcCKevuMjhLSxyeHyF4vEWiMvjFac7X5xuLyKd9+66vwmUUioRi6hopF3FQu2JSKhdRYLtiXAwmAi1tcdad+yKNq7ZqWIRL1CA3ocgYcXTgN4m7yNgTbC+1qxXZmSdSWwDkDV8ZAL6ntxE9L2iMejEAnrVligQBiLW91Ggt9OCBL3mnMf62vm90yqj86b/BmA1OpltAzYE62vNUAnDdiax5QhrtsNw9JLYI63HcGAYevZDIXqQ8P6SW2cTsg3d7N3Z5dGEHp6yDdiVySEZhpEKk9gGESv55aNrXl11fRPEgI5Upi4Zht1MYjMMI+fkzMBPwzCMTiaxGYaRc0xiMwwj55jEZhhGzjGJzTCMnGMSm2EYOcckNsMwco5JbIZh5ByT2AzDyDkmsRmGkXNMYjMMI+eYxGYYRs4xic0wjJxjEpthGDnHJDbDMHKOSWyGYeQck9gMw8g5JrEZhpFzTGIzDCPnmMRmGEbOMYnNMIycYxKbYRg5xyQ2wzByjklshmHkHJPYDMPIOSaxGYaRc0xiMwwj55jEZhhGzjGJzTCMnPP/AUWXFUzDo+/rAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = 'Healthy', 'Diabetic', 'Pre-Diabetic'\n",
    "ex = [0.1, 0.1, 0.1]\n",
    "df.Diabetes_012.value_counts().plot.pie(labels = labels, autopct = '%1.2f%%', shadow = True, explode = ex)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "95162bd5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Duplicates:  23899\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "        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>Diabetes_012</th>\n",
       "      <th>HighBP</th>\n",
       "      <th>HighChol</th>\n",
       "      <th>CholCheck</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Smoker</th>\n",
       "      <th>Stroke</th>\n",
       "      <th>HeartDiseaseorAttack</th>\n",
       "      <th>PhysActivity</th>\n",
       "      <th>Fruits</th>\n",
       "      <th>...</th>\n",
       "      <th>AnyHealthcare</th>\n",
       "      <th>NoDocbcCost</th>\n",
       "      <th>GenHlth</th>\n",
       "      <th>MentHlth</th>\n",
       "      <th>PhysHlth</th>\n",
       "      <th>DiffWalk</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1242</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>27.0</td>\n",
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       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
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       "      <td>5.0</td>\n",
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       "      <td>21.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
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       "    <tr>\n",
       "      <th>2700</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3160</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3332</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253492</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253550</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253563</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253597</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253638</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23899 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Diabetes_012  HighBP  HighChol  CholCheck   BMI  Smoker  Stroke  \\\n",
       "1242             2.0     1.0       1.0        1.0  27.0     1.0     0.0   \n",
       "1563             0.0     0.0       0.0        1.0  21.0     1.0     0.0   \n",
       "2700             0.0     0.0       0.0        1.0  32.0     0.0     0.0   \n",
       "3160             0.0     0.0       0.0        1.0  21.0     0.0     0.0   \n",
       "3332             0.0     0.0       0.0        1.0  24.0     0.0     0.0   \n",
       "...              ...     ...       ...        ...   ...     ...     ...   \n",
       "253492           2.0     1.0       1.0        1.0  33.0     0.0     0.0   \n",
       "253550           0.0     0.0       0.0        1.0  25.0     0.0     0.0   \n",
       "253563           0.0     0.0       1.0        1.0  24.0     1.0     0.0   \n",
       "253597           0.0     0.0       0.0        1.0  24.0     0.0     0.0   \n",
       "253638           0.0     0.0       0.0        1.0  24.0     0.0     0.0   \n",
       "\n",
       "        HeartDiseaseorAttack  PhysActivity  Fruits  ...  AnyHealthcare  \\\n",
       "1242                     0.0           0.0     0.0  ...            1.0   \n",
       "1563                     0.0           1.0     1.0  ...            1.0   \n",
       "2700                     0.0           1.0     1.0  ...            1.0   \n",
       "3160                     0.0           1.0     1.0  ...            1.0   \n",
       "3332                     0.0           1.0     1.0  ...            1.0   \n",
       "...                      ...           ...     ...  ...            ...   \n",
       "253492                   0.0           1.0     1.0  ...            1.0   \n",
       "253550                   0.0           1.0     1.0  ...            1.0   \n",
       "253563                   0.0           1.0     1.0  ...            1.0   \n",
       "253597                   0.0           1.0     1.0  ...            1.0   \n",
       "253638                   0.0           1.0     1.0  ...            1.0   \n",
       "\n",
       "        NoDocbcCost  GenHlth  MentHlth  PhysHlth  DiffWalk  Sex   Age  \\\n",
       "1242            0.0      5.0       0.0      30.0       1.0  0.0  10.0   \n",
       "1563            0.0      1.0       0.0       0.0       0.0  0.0   4.0   \n",
       "2700            0.0      2.0       0.0       0.0       0.0  0.0   5.0   \n",
       "3160            0.0      1.0       0.0       0.0       0.0  0.0   4.0   \n",
       "3332            0.0      1.0       0.0       0.0       0.0  1.0   9.0   \n",
       "...             ...      ...       ...       ...       ...  ...   ...   \n",
       "253492          0.0      3.0       0.0       0.0       0.0  1.0   9.0   \n",
       "253550          0.0      1.0       0.0       0.0       0.0  0.0   7.0   \n",
       "253563          0.0      2.0       0.0       0.0       0.0  1.0   8.0   \n",
       "253597          0.0      2.0       0.0       0.0       0.0  0.0   5.0   \n",
       "253638          0.0      2.0       0.0       0.0       0.0  1.0   1.0   \n",
       "\n",
       "        Education  Income  \n",
       "1242          4.0     5.0  \n",
       "1563          6.0     8.0  \n",
       "2700          6.0     8.0  \n",
       "3160          6.0     8.0  \n",
       "3332          6.0     8.0  \n",
       "...           ...     ...  \n",
       "253492        6.0     6.0  \n",
       "253550        6.0     8.0  \n",
       "253563        6.0     8.0  \n",
       "253597        6.0     8.0  \n",
       "253638        4.0     6.0  \n",
       "\n",
       "[23899 rows x 22 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking duplicates\n",
    "duplicates = df[df.duplicated()]\n",
    "print(\"Duplicates: \", len(duplicates))\n",
    "duplicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "22c12683",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop duplicates\n",
    "df.drop_duplicates(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6698ff21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(229781, 22)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fd301d96",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing PhysHlth as it has a high correlation similar to GenHlth.\n",
    "df.drop('PhysHlth', inplace = True, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7b6b1adc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(229781, 21)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6f341b01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Counts of the target variable\n",
    "sns.countplot(data = df, y = 'Diabetes_012')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "39fbcf4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Checking number of records (samples)\n",
    "non_diabetic = df[df['Diabetes_012'] == 0]\n",
    "pre_diabetic = df[df['Diabetes_012'] == 1]\n",
    "diabetic = df[df['Diabetes_012'] == 2]\n",
    "\n",
    "# Cloning samples (oversampling) to balance the dataset to train model correctly\n",
    "pre_diabetic_os = pre_diabetic.sample(len(non_diabetic), replace = True)\n",
    "diabetic_os = diabetic.sample(len(non_diabetic), replace = True)\n",
    "\n",
    "df_new = pd.concat([pre_diabetic_os, diabetic_os, non_diabetic], axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "14c31dea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0    190055\n",
       "2.0    190055\n",
       "0.0    190055\n",
       "Name: Diabetes_012, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new['Diabetes_012'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6d92d794",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(570165, 21)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9f6e5c0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Counts of the oversampled target variable\n",
    "sns.countplot(data = df_new, y = 'Diabetes_012')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "65d47770",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Train-test split\n",
    "\n",
    "# input\n",
    "x = df_new.iloc[:, 1:].values\n",
    "# output\n",
    "y = df_new.iloc[:, 0].values\n",
    "\n",
    "# Split data into 80:20\n",
    "from sklearn.model_selection import train_test_split\n",
    "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.2, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "450d1de7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature Scaling using MinMaxScalar\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler = MinMaxScaler()\n",
    "x_train = scaler.fit_transform(x_train)\n",
    "x_test = scaler.transform(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "ee4f9f42",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.16693814 0.11379463 0.10879219 0.09205941 0.07848564 0.06783754\n",
      " 0.06295699 0.05700294 0.04479551 0.04213737 0.03083714 0.02662434\n",
      " 0.02082814 0.01741698 0.01704606 0.01589471 0.01426487 0.01167811\n",
      " 0.00827561 0.00233367]\n"
     ]
    }
   ],
   "source": [
    "# Principal Component Ananlysis\n",
    "from sklearn.decomposition import PCA\n",
    "pca = PCA(n_components = 20)\n",
    "\n",
    "x_train = pca.fit_transform(x_train)\n",
    "x_test = pca.transform(x_test)\n",
    "\n",
    "explained_variance = pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cd9e758",
   "metadata": {},
   "source": [
    "# Applying ML Algorithms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "568fc9b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(random_state=0)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LogisticRegression</label><div class=\"sk-toggleable__content\"><pre>LogisticRegression(random_state=0)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression(random_state=0)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Logistic Regression Algorithm\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "classifier = LogisticRegression(random_state = 0)\n",
    "classifier.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "59578e51",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = classifier.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ac605f95",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix:\n",
      " [[24446  6808  6815]\n",
      " [11009 11685 15310]\n",
      " [ 6820  8786 22354]]\n"
     ]
    }
   ],
   "source": [
    "# Performance Evaluation\n",
    "from sklearn.metrics import confusion_matrix\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "print(\"Confusion Matrix:\\n\", cm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d9e948d5",
   "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": [
    "# Plotting Confusion Matrix\n",
    "\n",
    "from sklearn.metrics import ConfusionMatrixDisplay\n",
    "display = ConfusionMatrixDisplay(cm)\n",
    "display.plot(cmap = \"Reds\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c89b89d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Logistic Regression model is  51.28778511483518 %.\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "print(\"Accuracy of Logistic Regression model is \", accuracy_score(y_test, y_pred) * 100, \"%.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ac917d52",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       0.58      0.64      0.61     38069\n",
      "         1.0       0.43      0.31      0.36     38004\n",
      "         2.0       0.50      0.59      0.54     37960\n",
      "\n",
      "    accuracy                           0.51    114033\n",
      "   macro avg       0.50      0.51      0.50    114033\n",
      "weighted avg       0.50      0.51      0.50    114033\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "961e0f8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GaussianNB()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GaussianNB</label><div class=\"sk-toggleable__content\"><pre>GaussianNB()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "GaussianNB()"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Naive-Bayes Classifier Algorithm\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "gnb = GaussianNB()\n",
    "gnb.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e78e749d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Gaussian Naive Bayes model is  48.909526189787165 %.\n"
     ]
    }
   ],
   "source": [
    "y_pred = gnb.predict(x_test)\n",
    "\n",
    "from sklearn import metrics\n",
    "print(\"Accuracy of Gaussian Naive Bayes model is \", metrics.accuracy_score(y_test, y_pred) * 100, \"%.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "a24bb62e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix:\n",
      " [[20680  7026 10363]\n",
      " [ 8927  9495 19582]\n",
      " [ 5372  6990 25598]]\n"
     ]
    }
   ],
   "source": [
    "# Performance Evaluation\n",
    "from sklearn.metrics import confusion_matrix\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "print(\"Confusion Matrix:\\n\", cm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "b493140a",
   "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": [
    "# Plotting Confusion Matrix\n",
    "\n",
    "from sklearn.metrics import ConfusionMatrixDisplay\n",
    "display = ConfusionMatrixDisplay(cm)\n",
    "display.plot(cmap = \"Reds\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "31eafb86",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       0.59      0.54      0.57     38069\n",
      "         1.0       0.40      0.25      0.31     38004\n",
      "         2.0       0.46      0.67      0.55     37960\n",
      "\n",
      "    accuracy                           0.49    114033\n",
      "   macro avg       0.49      0.49      0.47    114033\n",
      "weighted avg       0.49      0.49      0.47    114033\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c5a3780c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n",
      "[Parallel(n_jobs=1)]: Done 300 out of 300 | elapsed: 15.6min finished\n",
      "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n",
      "[Parallel(n_jobs=1)]: Done 300 out of 300 | elapsed:    9.2s finished\n"
     ]
    }
   ],
   "source": [
    "# Random Forest Classifier Algorithm\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "RFCmodel = RandomForestClassifier(n_estimators = 300, criterion = 'entropy',\n",
    "                                  min_samples_split = 10, random_state = 0, verbose = True)\n",
    "\n",
    "RFCmodel.fit(x_train, y_train)\n",
    "\n",
    "y_pred = RFCmodel.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "bea9d1b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Random Forest model is  94.99530837564565 %.\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "print(\"Accuracy of Random Forest model is \", metrics.accuracy_score(y_test, y_pred) * 100, \"%.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "9332dcbb",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix:\n",
      " [[33260   320  4489]\n",
      " [    0 38004     0]\n",
      " [  788   110 37062]]\n"
     ]
    }
   ],
   "source": [
    "# Performance Evaluation\n",
    "from sklearn.metrics import confusion_matrix\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "print(\"Confusion Matrix:\\n\", cm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "d975d4f1",
   "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": [
    "# Plotting Confusion Matrix\n",
    "\n",
    "from sklearn.metrics import ConfusionMatrixDisplay\n",
    "display = ConfusionMatrixDisplay(cm)\n",
    "display.plot(cmap = \"Reds\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "8c167fcd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       0.98      0.87      0.92     38069\n",
      "         1.0       0.99      1.00      0.99     38004\n",
      "         2.0       0.89      0.98      0.93     37960\n",
      "\n",
      "    accuracy                           0.95    114033\n",
      "   macro avg       0.95      0.95      0.95    114033\n",
      "weighted avg       0.95      0.95      0.95    114033\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_test, y_pred))"
   ]
  }
 ],
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