Diabetes classification-Logistic_Regression.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://www.kaggle.com/salihacur/diabetes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import python libraries\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set_theme()\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn import preprocessing\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#load and read data\n",
    "\n",
    "df=pd.read_csv('diabetes.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>History</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  History  \\\n",
       "0            6      148             72             35        0  33.6    0.627   \n",
       "1            1       85             66             29        0  26.6    0.351   \n",
       "2            8      183             64              0        0  23.3    0.672   \n",
       "3            1       89             66             23       94  28.1    0.167   \n",
       "4            0      137             40             35      168  43.1    2.288   \n",
       "\n",
       "   Age  Outcome  \n",
       "0   50        1  \n",
       "1   31        0  \n",
       "2   32        1  \n",
       "3   21        0  \n",
       "4   33        1  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# display the first 5 rows of data\n",
    "\n",
    "df.rename(columns={'DiabetesPedigreeFunction':'History'},inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>History</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.845052  120.894531      69.105469      20.536458   79.799479   \n",
       "std       3.369578   31.972618      19.355807      15.952218  115.244002   \n",
       "min       0.000000    0.000000       0.000000       0.000000    0.000000   \n",
       "25%       1.000000   99.000000      62.000000       0.000000    0.000000   \n",
       "50%       3.000000  117.000000      72.000000      23.000000   30.500000   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
       "max      17.000000  199.000000     122.000000      99.000000  846.000000   \n",
       "\n",
       "              BMI     History         Age     Outcome  \n",
       "count  768.000000  768.000000  768.000000  768.000000  \n",
       "mean    31.992578    0.471876   33.240885    0.348958  \n",
       "std      7.884160    0.331329   11.760232    0.476951  \n",
       "min      0.000000    0.078000   21.000000    0.000000  \n",
       "25%     27.300000    0.243750   24.000000    0.000000  \n",
       "50%     32.000000    0.372500   29.000000    0.000000  \n",
       "75%     36.600000    0.626250   41.000000    1.000000  \n",
       "max     67.100000    2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# gives a brief statistical view of the dataset\n",
    "# gives a summary of the correlations between each data feature. Shows many zeros which could be used to \n",
    "# ....replace missing values\n",
    "\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#set display dimension for the graphs\n",
    "\n",
    "#plt.rcParams['figure.figsize']=[8,5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PREPROCESSING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAEXCAYAAAAOS5e9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAWdElEQVR4nO3de3BU5f3H8c/mRoxBAgKRUidVBKlAgUqGhgQiUGmAZLiqgOVSRIpDIYIaLgUphHCTGS4yZWiFiIDcQjCVSgnlIhBSnRGUtA6IIglM0yQKgUAC2ew+vz8c9tdoCwnNPofI+/UXu5t9zjeH5J2Tze5ZlzHGCABgRYDTAwDA3YToAoBFRBcALCK6AGAR0QUAi4guAFhEdO9i58+f16OPPqrt27dXu37t2rWaPn26X7ZZWFioxMREDRgwQMePH69228iRI9WrVy8NGDBAAwcOVP/+/TVt2jRVVFT4ZZb/1b59+zR//nynx0A9Q3TvcgEBAVq8eLHOnDljZXsffPCBmjZtqqysLHXu3Pk7t6ekpCgrK0vvvPOOdu3apYqKCq1cudLKbLXVu3dvzZo1y+kxUM8EOT0AnBUaGqpf/epXevnll7VlyxaFhIRUu72srExz587VyZMn5XK51L17d02dOlVBQTf/0tm6das2bNiggIAANW3aVLNnz1ZRUZGWL1+usrIyjRw5Uhs2bLjpGi6XS127dtWhQ4ckSe3bt1fv3r118uRJLV26VGFhYUpLS1Npaak8Ho9GjhypoUOHSpL+8Ic/KCMjQ/fee6+6dOmiffv2af/+/fryyy81b948Xb16VSUlJWrbtq2WL1+uBg0aqEOHDho/frxycnJUXFyscePGacSIEZKkNWvWaOfOnQoKClJUVJQWLVqkvXv3as+ePVqzZo3KysqUlpamzz77TG63WzExMUpJSVFQUJBWrlypvXv3Kjg4WI0bN9bChQvVvHnz2/0vQz3HkS70wgsvKCwsTMuWLfvObfPnz1dERITeffdd7dixQ6dOndK6detuul5ubq7eeOMNvfXWW/rTn/6kxMRETZw4UV27dtXkyZPVpUuXWwZXki5duqTdu3era9eukiS3262ePXtqz549+vGPf6zJkyfrpZdeUmZmpjZu3Kh169bp448/1uHDh5WZmamMjAxlZmbq6tWrvjW3bdumgQMHatu2bcrOztb58+d18OBBSVJlZaUaN26sLVu2aOXKlVq4cKGuX7+uffv2KTMzU1u3btWuXbv0wx/+UBs3bqw264IFC9SuXTtlZmbqnXfe0cWLF5Wenq7CwkKtX79eO3bsUGZmpmJjY3XixIlbfu74/uJIFwoICNBrr72mgQMHKi4urtpthw4d0ubNm+VyuRQSEqJhw4Zp/fr1Gj9+/H9d7/Dhw+rXr5+aNGkiSRo8eLDS0tJ0/vz5W86yZMkSrV69Wjdend6zZ0+NGjXKd3uXLl0kSWfPnlVBQYFmzpzpu+3atWv69NNPdebMGSUkJOi+++6TJD377LP629/+Jkl65ZVXlJOToz/+8Y86e/asiouLVV5e7lujd+/ekqR27dqpsrJS5eXlys3NVUJCgho1aiRJmjFjhiQpMzPTd7+DBw8qLy9PGRkZvlkkKTIyUm3bttWgQYPUo0cP9ejRQzExMbfcD/j+IrqQJLVo0UJz587VtGnTNHDgQN/1Xq9XLper2uWqqqqbruX1er9znTHmlveTvnlMNyEh4b/eHhYWJknyeDxq2LChsrKyfLd99dVXatiwoZYtW6Z/P6VIYGCg799Tp06Vx+NR37599cQTT6iwsLDaxzZo0ECSfJ+zMUaBgYHV9sHly5d1+fLl73zOK1asUKtWrXwf43K5FBAQoI0bNyovL0+5ublasGCBunfvrpSUlFvuC3w/8fACfBISEtSjRw+tX7/ed11cXJw2btwoY4wqKyu1bds2devW7abrdO/eXe+9954uXLggSdqxY4ciIiIUFRVVZ7M+9NBDCg0N9UX3xrMi/v73vys+Pl7Z2dkqKyuTJN/RpyQdOXJEEydOVL9+/SRJn3zyiTwez0231a1bN+3du1dXrlyRJL3++ut68803q31MXFyc3nzzTd9+euGFF7Rx40adPHlSiYmJatWqlX79619rzJgxysvLq6vdgHqII11UM2vWLH300UfVLs+fP19JSUlyu93q3r27JkyYIElasWKFJCk5ObnaGrGxsRozZoxGjx4tr9erJk2aaM2aNQoIqLuf8SEhIfr973+vtLQ0vfHGG6qqqlJycrIef/xxSdLTTz+tZ555RqGhoWrdurXuueceSdKUKVM0ceJEhYWFKTw8XNHR0SooKLjptuLj4/X5559r+PDhkqRHHnlEqampys7O9n3Mb3/7W6Wlpfn2U7du3TRu3DgFBwerb9++GjJkiMLCwhQaGsozHu5yLk7tiO+bvLw8HT9+3PdYcHp6uj755BMtX77c2cEAEV18D125ckUzZ87UmTNn5HK51KJFC6WmpioyMtLp0QCiCwA28Yc0ALCI6AKARUQXACwiugBg0S2fp3vx4lV5vbX/W9v994fr66+v3NZQTmN2ZzC7M+rr7Hfq3AEBLjVufO9/vf2W0fV6zW1F98Z96ytmdwazO6O+zl4f5+bhBQCwiOgCgEVEFwAsIroAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUQXACwiugBgEdEFAIuILgBYRHQBwCKiCwAWEV0AsIjoAoBFt3y7njvR22+/pXPn8v22fnBwoNxuj1/WvnSpVJLUqFGEX9b35+z+9uijrTVw4DCnxwD8ql5G99y5fJ06/bkCQyOcHqXWPNdKJUkll6ucHeQO47lWquDgQKfHAPyuXkZXkgJDIxQW1dvpMWqtPH+fJNXL2f3pxn4Bvu94TBcALCK6AGAR0QUAi4guAFhEdAHAIqILABYRXQCwiOgCgEVEFwAsIroAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUQXACwiugBgEdEFAIuILgBYRHQBwCKiCwAWEV0AsIjoAoBFRBcALCK6AGAR0QUAi4guAFhEdAHAIqILABYRXQCwiOgCgEVEFwAsIroAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUH+WDQn55Duu+8edegQ7Y/lAcCvcnIOSZJiY3vU+dp+ie6RI+8rODiQ6AKol44ceV+Sf6LLwwsAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUQXACwiugBgEdEFAIuILgBYRHQBwCKiCwAWEV0AsIjoAoBFRBcALCK6AGAR0QUAi4guAFhEdAHAIqILABYRXQCwiOgCgEVEFwAsIroAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUQXACwiugBgEdEFAIuILgBYRHQBwCKiCwAWEV0AsIjoAoBFRBcALCK6AGAR0QUAi4L8seilS6W6fPmSFi9O9cfyKijIl9cT6Je14Qxv1TWdOXPGb18z/hYcHCi32+P0GLelvs7uz7kLCvLVqFEjv6zNkS4AWOSXI91GjSLUtOn9mjp1pj+W1+LFqfr83Fd+WRvOCAgK1cMPR/rta8bfmjVrqJKSMqfHuC31dXZ/zu3P37g40gUAi4guAFhEdAHAIqILABYRXQCwiOgCgEVEFwAsIroAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUQXACwiugBgEdEFAIuILgBYRHQBwCKiCwAWEV0AsIjoAoBFRBcALCK6AGAR0QUAi4guAFhEdAHAIqILABYRXQCwiOgCgEVEFwAsIroAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUQXACwiugBgEdEFAIuC/LFoXFy87rvvHn8sDQB+FxcX77e1/RLd2NgeatasoUpKyvyxPAD4VWxsD7+tzcMLAGAR0QUAi4guAFhEdAHAIqILABYRXQCwiOgCgEVEFwAsIroAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUQXACwiugBgEdEFAIuILgBYRHQBwCKiCwAWEV0AsIjoAoBFRBcALCK6AGAR0QUAi4guAFhEdAHAIqILABYRXQCwiOgCgEVEFwAsIroAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUQXACwiugBgUZDTA9wuz7VSlefvc3qMWvNcK5Wkejm7P32zXyKdHgPwu3oZ3QcfjPLr+sHBgXK7PX5Z+9Klb3Z5o0YRflnfn7P7V1M9/PDDTg8B+F29jO6IEaP8un6zZg1VUlLm1234C7MDdzYe0wUAi4guAFhEdAHAIqILABYRXQCwiOgCgEVEFwAsIroAYBHRBQCLiC4AWER0AcAiogsAFhFdALCI6AKARUQXACwiugBgEdEFAIuILgBYdMu36wkIcN324v/LfZ3G7M5gdmfU19nvxLlvNZPLGGMszQIAdz0eXgAAi4guAFhEdAHAIqILABYRXQCwiOgCgEVEFwAsIroAYBHRBQCL/BLdd999V/369VOfPn20adMmf2zCL1atWqX+/furf//+WrJkidPj3JbFixdr+vTpTo9RK/v379fgwYPVt29fzZ8/3+lxaiUrK8v3NbN48WKnx6mRK1euKDExUefPn5ckHT16VElJSerTp4+WLVvm8HT/3bfn3rp1qxITE5WUlKQZM2aosrLS4QlryNSxf/3rX6Znz57m4sWL5urVqyYpKcmcPn26rjdT53Jycswzzzxjrl+/biorK82oUaNMdna202PVytGjR03Xrl3NtGnTnB6lxgoKCkxcXJwpLCw0lZWVZvjw4ebgwYNOj1Uj5eXlJjo62nz99dfG7XaboUOHmpycHKfHuqmPP/7YJCYmmnbt2plz586ZiooKEx8fbwoKCozb7TZjx469I/f/t+c+c+aMefLJJ01ZWZnxer0mJSXFpKenOz1mjdT5ke7Ro0f1s5/9TBEREQoLC9MvfvEL/eUvf6nrzdS5Zs2aafr06QoJCVFwcLBatWqlf/7zn06PVWOlpaVatmyZJkyY4PQotbJ3717169dPDzzwgIKDg7Vs2TJ17NjR6bFqxOPxyOv1qqKiQlVVVaqqqlKDBg2cHuumtm3bpjlz5qh58+aSpBMnTigqKkoPPviggoKClJSUdEd+v3577pCQEM2ZM0fh4eFyuVxq06ZNvfl+veVZxmqruLhYzZo1811u3ry5Tpw4UdebqXOtW7f2/fvs2bPavXu3Nm/e7OBEtfPqq69qypQpKiwsdHqUWsnPz1dwcLAmTJigwsJCPfHEE3rxxRedHqtGwsPDlZycrL59++qee+5RdHS0fvrTnzo91k2lpaVVu/yfvl+Liopsj3VL3567ZcuWatmypSTpwoUL2rRpkxYuXOjEaLVW50e6Xq9XLtf/n9rMGFPt8p3u9OnTGjt2rFJSUvSjH/3I6XFqZPv27WrRooViYmKcHqXWPB6PcnNztWDBAm3dulUnTpzQzp07nR6rRk6ePKkdO3bowIEDOnz4sAICArR27Vqnx6qV+v79WlRUpNGjR2vIkCHq2rWr0+PUSJ1H94EHHlBJSYnvcklJie9XgjvdRx99pDFjxuill17SoEGDnB6nxt577z3l5ORowIABWrlypfbv368FCxY4PVaNNG3aVDExMWrSpIlCQ0P185//vF78ZiRJR44cUUxMjO6//36FhIRo8ODB+vDDD50eq1bq8/frF198oWHDhmnQoEGaOHGi0+PUWJ1Ht1u3bsrNzdWFCxdUUVGh7Oxs9ejRo643U+cKCws1ceJELV26VP3793d6nFpJT0/Xrl27lJWVpcmTJ6tXr16aOXOm02PVSM+ePXXkyBFdvnxZHo9Hhw8fVrt27Zweq0batm2ro0ePqry8XMYY7d+/Xx06dHB6rFrp2LGjvvzyS+Xn58vj8WjXrl314vv1ypUreu6555ScnKyxY8c6PU6t1PljupGRkZoyZYpGjRolt9utoUOH6ic/+Uldb6bOrV27VtevX9eiRYt81w0bNkzDhw93cKrvv44dO2rcuHEaMWKE3G63YmNjNWTIEKfHqpG4uDh9+umnGjx4sIKDg9WhQweNHz/e6bFqpUGDBlq0aJEmTZqk69evKz4+XgkJCU6PdUsZGRn66quvlJ6ervT0dElSr169lJyc7PBkt8Y7RwCARbwiDQAsIroAYBHRBQCLiC4AWER0AcCiOn/KGO4O58+f15NPPqk2bdr4rjPGaNSoURo6dKiDk9VOUVGRkpOTtWXLFqdHwV2C6OK2hYaGKisry3e5qKhIiYmJat++vdq2bevgZDUXGRlJcGEV0UWdiYyMVFRUlHJycjRv3jxVVFQoPDxcGzZs0Pbt27V582Z5vV5FRERo9uzZatWqlS5cuKAZM2aooKBAERERatasmVq3bq1Jkyb5XmyQk5Oj4uJi34soysvL9bvf/U75+fkqLS3Vvffeq6VLl+rhhx/WyJEj1alTJx07dkyFhYWKiYlRamqqAgICdODAAS1fvlxer1dhYWGaO3euwsPDlZSUpOPHj0uSVq9erezsbHm9XrVs2VJz5sxRZGSksrOztXr1arlcLgUGBiolJUXR0dEO73HUS06eVxL117lz50ynTp2qXXfs2DETHR1tVq1aZaKjo01ZWZkxxpgPPvjAjBgxwpSXlxtjjDl8+LBJSEgwxhgzZcoUs2TJEmOMMUVFRSY2NtasXLnSGGNMmzZtzIYNG4wxxuTl5Zn27duba9eumd27d5vU1FTfdmfPnm3mzZtnjDHml7/8pZk8ebLxeDymrKzMxMXFmdzcXFNSUmIef/xx849//MMYY8yePXvMc889V+3z2Llzp3nxxReN2+02xhizZcsWM27cOGOMMb179zbHjx/3zf/666/X4d7E3YQjXdy2a9euacCAAZK+OVtY48aN9dprr+nrr7/Wo48+qvDwcEnSwYMHlZ+fr2HDhvnue/nyZZWWlur999/3nVWsefPm33kJau/evSVJ7dq1U2VlpcrLy5WQkKAHH3xQGzZsUH5+vj788EN17tzZd5+ePXsqICBA4eHhioqK0qVLl3Ts2DG1bt1ajz32mCSpT58+6tOnj+9dCCTpwIEDysvL870M+ca5ciWpf//++s1vfqP4+HjFxsbq+eefr9N9ibsH0cVt+/ZjujdkZmYqLCzMd9nr9WrAgAF65ZVXfJeLi4vVqFEjBQUFyfzbK9EDAqo/oebGScFvnG7QGKO3335b27Zt07PPPqukpCRFRERUi2doaKjv3y6XS8YYBQUFfecUhqdOnfL9YLgx142HMCSpsrJSly5dkiRNmTJFQ4YMUU5OjjIzM7Vu3TplZGTUco8BPGUMFsTFxenPf/6ziouLJUmbN2/W6NGjJUnx8fG+eF28eFF//etfb3k+1yNHjmjQoEF66qmn9NBDD2n//v3yeDw3vU/Hjh31xRdf6PTp05Kkffv2+X4I/PucGRkZunLliiRpxYoVSklJUVVVlXr16qWKigoNHz5cc+bM0alTp+rPe3LhjsKRLvwuLi5Ozz//vMaOHSuXy6Xw8HCtWrVKLpdLM2bM0KxZs3xHrD/4wQ+qHan+J2PHjtWrr77qi3WnTp302Wef3fQ+TZs21dKlSzVt2jR5PB6Fh4d/500Yn3rqKRUVFenpp5+Wy+VSixYttGjRIgUFBWnmzJl6+eWXfUfMCxYsUEhIyP+2Y3BX4ixjcNSmTZv02GOPqXPnzqqsrNSIESM0adIkxcfHOz0a4Bcc6cJRjzzyiFJTU+X1euV2u5WQkEBw8b3GkS4AWMQf0gDAIqILABYRXQCwiOgCgEVEFwAsIroAYNH/AYa7gVTcZrRTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#identify outliers. Q3 + IQR*1.5 = 13 (IQR = 5). Remove outliers > 13\n",
    "#display plot\n",
    "\n",
    "m=df['Pregnancies'].median()\n",
    "df['Pregnancies']=df['Pregnancies'].apply(lambda x: m if x > 13 else x)\n",
    "sns.boxplot(x=df['Pregnancies']);\n",
    "plt.xlabel('Pregnancies');\n",
    "plt.title('No. of Pregancies');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    763\n",
       "True       5\n",
       "Name: Glucose, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#identify count of zeros in the dataset\n",
    "\n",
    "(df['Glucose']==0).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>History</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.782552</td>\n",
       "      <td>121.681605</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.270644</td>\n",
       "      <td>30.436016</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.750000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.782552  121.681605      69.105469      20.536458   79.799479   \n",
       "std       3.270644   30.436016      19.355807      15.952218  115.244002   \n",
       "min       0.000000   44.000000       0.000000       0.000000    0.000000   \n",
       "25%       1.000000   99.750000      62.000000       0.000000    0.000000   \n",
       "50%       3.000000  117.000000      72.000000      23.000000   30.500000   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
       "max      13.000000  199.000000     122.000000      99.000000  846.000000   \n",
       "\n",
       "              BMI     History         Age     Outcome  \n",
       "count  768.000000  768.000000  768.000000  768.000000  \n",
       "mean    31.992578    0.471876   33.240885    0.348958  \n",
       "std      7.884160    0.331329   11.760232    0.476951  \n",
       "min      0.000000    0.078000   21.000000    0.000000  \n",
       "25%     27.300000    0.243750   24.000000    0.000000  \n",
       "50%     32.000000    0.372500   29.000000    0.000000  \n",
       "75%     36.600000    0.626250   41.000000    1.000000  \n",
       "max     67.100000    2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Replacing zero values with mean\n",
    "\n",
    "m=df['Glucose'].mean()\n",
    "df['Glucose']=df['Glucose'].apply(lambda x: m if x==0 else x)\n",
    "df.describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#identify outliers. Q3+IQR*1.5=201 (IQR = 40), and Q1-IQR*1.5 = 39. Remove outliers < 39\n",
    "#display plot\n",
    "\n",
    "df['Glucose']=df['Glucose'].apply(lambda x: m if x<39 else x)\n",
    "sns.boxplot(x=df['Glucose']);\n",
    "plt.title('Glucose level');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    733\n",
       "True      35\n",
       "Name: BloodPressure, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#identify count of zeros in the dataset\n",
    "\n",
    "(df['BloodPressure']==0).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>History</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.782552</td>\n",
       "      <td>121.681605</td>\n",
       "      <td>72.254807</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.270644</td>\n",
       "      <td>30.436016</td>\n",
       "      <td>12.115932</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.750000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.782552  121.681605      72.254807      20.536458   79.799479   \n",
       "std       3.270644   30.436016      12.115932      15.952218  115.244002   \n",
       "min       0.000000   44.000000      24.000000       0.000000    0.000000   \n",
       "25%       1.000000   99.750000      64.000000       0.000000    0.000000   \n",
       "50%       3.000000  117.000000      72.000000      23.000000   30.500000   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
       "max      13.000000  199.000000     122.000000      99.000000  846.000000   \n",
       "\n",
       "              BMI     History         Age     Outcome  \n",
       "count  768.000000  768.000000  768.000000  768.000000  \n",
       "mean    31.992578    0.471876   33.240885    0.348958  \n",
       "std      7.884160    0.331329   11.760232    0.476951  \n",
       "min      0.000000    0.078000   21.000000    0.000000  \n",
       "25%     27.300000    0.243750   24.000000    0.000000  \n",
       "50%     32.000000    0.372500   29.000000    0.000000  \n",
       "75%     36.600000    0.626250   41.000000    1.000000  \n",
       "max     67.100000    2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Replacing zero values with mean\n",
    "\n",
    "m=df['BloodPressure'].mean()\n",
    "df['BloodPressure']=df['BloodPressure'].apply(lambda x: m if x == 0 else x )\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#identify outliers. Q3 + IQR*1.5 = 104 (IQR = 16), and Q1 - IQR*1.5 = 40. Remove outliers > 104 and < 40\n",
    "#display plot\n",
    "\n",
    "df['BloodPressure']=df['BloodPressure'].apply(lambda x: m if x > 104 or x < 40 else x )\n",
    "sns.boxplot(x=df['BloodPressure']);\n",
    "plt.title('Blood Pressure');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    541\n",
       "True     227\n",
       "Name: SkinThickness, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#identify count of zeros in the dataset \n",
    "\n",
    "(df['SkinThickness']==0).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>History</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.782552</td>\n",
       "      <td>121.681605</td>\n",
       "      <td>71.923396</td>\n",
       "      <td>26.606479</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.270644</td>\n",
       "      <td>30.436016</td>\n",
       "      <td>10.899029</td>\n",
       "      <td>9.631241</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.750000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.782552  121.681605      71.923396      26.606479   79.799479   \n",
       "std       3.270644   30.436016      10.899029       9.631241  115.244002   \n",
       "min       0.000000   44.000000      40.000000       7.000000    0.000000   \n",
       "25%       1.000000   99.750000      64.000000      20.536458    0.000000   \n",
       "50%       3.000000  117.000000      70.000000      23.000000   30.500000   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
       "max      13.000000  199.000000     104.000000      99.000000  846.000000   \n",
       "\n",
       "              BMI     History         Age     Outcome  \n",
       "count  768.000000  768.000000  768.000000  768.000000  \n",
       "mean    31.992578    0.471876   33.240885    0.348958  \n",
       "std      7.884160    0.331329   11.760232    0.476951  \n",
       "min      0.000000    0.078000   21.000000    0.000000  \n",
       "25%     27.300000    0.243750   24.000000    0.000000  \n",
       "50%     32.000000    0.372500   29.000000    0.000000  \n",
       "75%     36.600000    0.626250   41.000000    1.000000  \n",
       "max     67.100000    2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#replacing zero values with mean\n",
    "\n",
    "m=df['SkinThickness'].mean()\n",
    "df['SkinThickness']=df['SkinThickness'].apply(lambda x: m if x==0 else x)\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#identify outliers. Q3 + IQR*1.5 = 49 (IQR = 11.5). Remove outliers ie. > 49\n",
    "#display boxplot\n",
    "\n",
    "m=df['SkinThickness'].mean()\n",
    "df['SkinThickness']=df['SkinThickness'].apply(lambda x: m if x > 49 else x )\n",
    "sns.boxplot(x=df['SkinThickness']);\n",
    "plt.title('Skin Thickness');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    394\n",
       "True     374\n",
       "Name: Insulin, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#identify count of zeros in the dataset \n",
    "\n",
    "(df['Insulin']==0).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>History</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.782552</td>\n",
       "      <td>121.681605</td>\n",
       "      <td>71.923396</td>\n",
       "      <td>26.122466</td>\n",
       "      <td>118.660163</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.270644</td>\n",
       "      <td>30.436016</td>\n",
       "      <td>10.899029</td>\n",
       "      <td>8.650532</td>\n",
       "      <td>93.080358</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.750000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.782552  121.681605      71.923396      26.122466  118.660163   \n",
       "std       3.270644   30.436016      10.899029       8.650532   93.080358   \n",
       "min       0.000000   44.000000      40.000000       7.000000   14.000000   \n",
       "25%       1.000000   99.750000      64.000000      20.536458   79.799479   \n",
       "50%       3.000000  117.000000      70.000000      23.000000   79.799479   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
       "max      13.000000  199.000000     104.000000      49.000000  846.000000   \n",
       "\n",
       "              BMI     History         Age     Outcome  \n",
       "count  768.000000  768.000000  768.000000  768.000000  \n",
       "mean    31.992578    0.471876   33.240885    0.348958  \n",
       "std      7.884160    0.331329   11.760232    0.476951  \n",
       "min      0.000000    0.078000   21.000000    0.000000  \n",
       "25%     27.300000    0.243750   24.000000    0.000000  \n",
       "50%     32.000000    0.372500   29.000000    0.000000  \n",
       "75%     36.600000    0.626250   41.000000    1.000000  \n",
       "max     67.100000    2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#replacing zero values with mean and identify outliers\n",
    "\n",
    "m=df['Insulin'].mean()\n",
    "df['Insulin']=df['Insulin'].apply(lambda x: m if x ==0 else x)\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#identify outliers. Q3 + IQR*1.5 = 197 (IQR = 47). Remove outliers > 197\n",
    "m=df['Insulin'].mean()\n",
    "df['Insulin']=df['Insulin'].apply(lambda x: m if x > 197 else x )\n",
    "sns.boxplot(x=df['Insulin']);\n",
    "plt.title('Insulin level');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    757\n",
       "True      11\n",
       "Name: BMI, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#identify count of zeros in the dataset \n",
    "\n",
    "(df['BMI']==0).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>History</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.782552</td>\n",
       "      <td>121.681605</td>\n",
       "      <td>71.923396</td>\n",
       "      <td>26.122466</td>\n",
       "      <td>94.652031</td>\n",
       "      <td>32.450805</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.270644</td>\n",
       "      <td>30.436016</td>\n",
       "      <td>10.899029</td>\n",
       "      <td>8.650532</td>\n",
       "      <td>33.032290</td>\n",
       "      <td>6.875374</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>18.200000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.750000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>27.500000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>118.660163</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>196.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.782552  121.681605      71.923396      26.122466   94.652031   \n",
       "std       3.270644   30.436016      10.899029       8.650532   33.032290   \n",
       "min       0.000000   44.000000      40.000000       7.000000   14.000000   \n",
       "25%       1.000000   99.750000      64.000000      20.536458   79.799479   \n",
       "50%       3.000000  117.000000      70.000000      23.000000   79.799479   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  118.660163   \n",
       "max      13.000000  199.000000     104.000000      49.000000  196.000000   \n",
       "\n",
       "              BMI     History         Age     Outcome  \n",
       "count  768.000000  768.000000  768.000000  768.000000  \n",
       "mean    32.450805    0.471876   33.240885    0.348958  \n",
       "std      6.875374    0.331329   11.760232    0.476951  \n",
       "min     18.200000    0.078000   21.000000    0.000000  \n",
       "25%     27.500000    0.243750   24.000000    0.000000  \n",
       "50%     32.000000    0.372500   29.000000    0.000000  \n",
       "75%     36.600000    0.626250   41.000000    1.000000  \n",
       "max     67.100000    2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#replacing zero values with mean and identify outliers\n",
    "\n",
    "m=df['BMI'].mean()\n",
    "df['BMI']=df['BMI'].apply(lambda x: m if x==0 else x)\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#identify outliers. Q3 + IQR*1.5 = 50.25 (IQR = 9).Removing outliers > 50.25\n",
    "\n",
    "df['BMI']=df['BMI'].apply(lambda x: m if x>50 else x)\n",
    "sns.boxplot(df['BMI']);\n",
    "plt.title('Body Mass Index');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#identify outliers. Q3 + IQR*1.5 = 1.2 (IQR = 0.3825).Removing outliers > 1.2\n",
    "\n",
    "m=df['History'].mean()\n",
    "df['History']=df['History'].apply(lambda x: m if x>=1.2 else x)\n",
    "sns.boxplot(df['History']);\n",
    "plt.title('Family history of diabetes');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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k0qVLde7cOUlSXV2d/H6/GhoaJN2/Jzxq1KiYnQPwKEQXcScQCKimpkZDhw7V7NmzJUmdnZ06cOCAvF6vfn1H7NfPVhWJRFRWVqbc3FxJUldXl7q7u22HBx6D2wuIO0ePHlV6errq6+vl8/nk8/l06tQpBQIBZWVl6cSJE/L7/ZKkqqqq3o/LycnRwYMHFQwGFYlEtGHDBm3bti1WpwE8EtFF3KmsrNTy5cv7XMWmpqaquLhY+/fv14IFC7Rw4ULNnz9ffr9fycnJkqSVK1dq3LhxmjdvngoKCuQ4Tu8vyQTiBd+9gEHl4sWLamxs1LJlyyTdfy7fpqYm7dixI7aDAf1EdDGodHZ2qqysTK2trUpISNDYsWO1adMmjRkzJtajAf1CdAHAEPd0AcAQ0QUAQ0QXAAwRXQAwRHQBwBDRBQBD/wVotL1WwLeI8wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#identify outliers. Q3 + IQR*1.5 = 66.5 (IQR = 17).Removing outliers > 66.5\n",
    "\n",
    "m=df['Age'].mean()\n",
    "df['Age']=df['Age'].apply(lambda x: m if x>=66.5 else x)\n",
    "sns.boxplot(df['Age']);\n",
    "plt.title('Age');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EXPLORATORY DATA ANALYSIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Admin\\anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#set subplots parameters for pie and histogram total count of positive diabetes vs negative diabetes\n",
    "\n",
    "fig, ax = plt.subplots(1,2, figsize=(15,5))\n",
    "df['Outcome'].value_counts().plot.pie(explode= (0,0.1),autopct='%1.1f%%',ax=ax[0], shadow=True)\n",
    "ax[0].set_title('Percentage of Diabetes')\n",
    "ax[0].set_ylabel('')\n",
    "sns.countplot('Outcome', data=df,ax=ax[1]);\n",
    "ax[1].set_title('Number of Diabetes');\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pregnancies      0.202492\n",
       "Glucose          0.492908\n",
       "BloodPressure    0.152696\n",
       "SkinThickness    0.072914\n",
       "Insulin          0.050583\n",
       "BMI              0.281021\n",
       "History          0.159691\n",
       "Age              0.264841\n",
       "Name: Outcome, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#display correlations\n",
    "\n",
    "df1=df.corr()\n",
    "df1=df1.iloc[:8,-1]\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#customizing stylesheet and creating pie chart\n",
    "\n",
    "plt.rcParams['figure.figsize']=[8,8]\n",
    "labels=['Pregnancies','Glucose','BloodPressure','SkinThickness','Insulin','BMI','DiabetesPedigreeFunction','Age']\n",
    "plt.pie(df1,labels=labels,autopct='%1.0f%%');\n",
    "plt.title('How much does each factor contributes to diabetes?');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#assigning x and y values \n",
    "\n",
    "x = df[['Pregnancies','Glucose','BloodPressure','SkinThickness','Insulin','BMI','History','Age']]\n",
    "y = df['Outcome']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#collect 100 samples of LogisticRegression for prediction test to arrive at mean score (positive test)\n",
    "#convert x values to a standard normal distribution thru StandardScaler\n",
    "#transform x values to a range between 0,1\n",
    "\n",
    "# for i in range(100):\n",
    "#     x_train, x_test, y_train, y_test = train_test_split(x,y, test_size=.25,  shuffle=True)\n",
    "#     pipe = make_pipeline(StandardScaler(),MinMaxScaler(), LogisticRegression())\n",
    "#     pipe.fit(x_train,y_train)\n",
    "#     k=pipe.predict(x_test).tolist()\n",
    "    \n",
    "# print(sum(k)/len(k))\n",
    "# pipe.score(x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#displays the correlation using heatmap\n",
    "\n",
    "plt.rcParams['figure.figsize']=[10,6]\n",
    "sns.heatmap(df.corr(),annot=True);\n",
    "plt.title('Correlation between each factor of diabetes');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create distribution of Age comparing between those without and with Diabetes\n",
    "\n",
    "df5=df.loc[df['Outcome']==0,'Age']\n",
    "df5_1=df.loc[df['Outcome']==1,'Age']\n",
    "sns.kdeplot(df5);\n",
    "sns.kdeplot(df5_1);\n",
    "plt.legend(['Age without Diabetes','Age with Diabetes']);\n",
    "plt.title('Comparing Age without & with diabetes');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Avg BMI of those tested negative: 30.4\n",
      " Avg BMI of those tested positive: 35.66\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create distribution of BMI comparing between those without and with Diabetes\n",
    "\n",
    "print(f\" Avg BMI of those tested negative: {round(df.loc[df['Outcome']==0,'BMI'].mean(),2)}\")\n",
    "print(f\" Avg BMI of those tested positive: {round(df.loc[df['Outcome']==1,'BMI'].mean(),2)}\")\n",
    "\n",
    "df14=df.loc[df['Outcome']==0,'BMI'];\n",
    "df15=df.loc[df['Outcome']==1,'BMI'];\n",
    "sns.kdeplot(df14);\n",
    "sns.kdeplot(df15);\n",
    "plt.legend(['BMI without Diabetes (mean 30)','BMI with Diabetes (mean 35)']);\n",
    "plt.title('Comparing BMI without & with diabetes');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create distribution of Glucose level comparing between those without and with Diabetes\n",
    "\n",
    "\n",
    "df7=df.loc[df['Outcome']==0,'Glucose']\n",
    "df7_1=df.loc[df['Outcome']==1,'Glucose']\n",
    "sns.kdeplot(df7);\n",
    "sns.kdeplot(df7_1);\n",
    "plt.legend(['Glucose without Diabetes','Glucose with Diabetes']);\n",
    "plt.title('Comparing Glucose levels without & with diabetes');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create distribution of no. of pregnancies comparing between those without and with Diabetes\n",
    "\n",
    "\n",
    "df8=df.loc[df['Outcome']==0,'Pregnancies']\n",
    "df8_1=df.loc[df['Outcome']==1,'Pregnancies']\n",
    "sns.kdeplot(df8);\n",
    "sns.kdeplot(df8_1);\n",
    "plt.legend(['Pregnancies without Diabetes','Pregnancies with Diabetes']);\n",
    "plt.title('Comparing No.of pregnancies without & with diabetes');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create distribution of Diabetes history comparing between those without and with Diabetes\n",
    "\n",
    "df16=df.loc[df['Outcome']==0, 'History']\n",
    "df16_1=df.loc[df['Outcome']==1, 'History']\n",
    "sns.kdeplot(df16);\n",
    "sns.kdeplot(df16_1);\n",
    "plt.legend(['DiabetesPedigreeFunction without Diabetes','DiabetesPedigreeFunction with Diabetes']);\n",
    "plt.title('Comparing Family history of diabetes without & with diabetes');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create a scatter plot comparing BMI with Glucose\n",
    "\n",
    "plt.scatter(x=df['BMI'], y=df['Glucose'], marker='o', s=3, c='g');\n",
    "plt.xlabel('BMI');\n",
    "plt.ylabel('Glucose');\n",
    "plt.title('Data visualization of BMI vs Glucose');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#creating 2 boxplots comparing BMI between 2 sets of pregnant females, without and with Diabetes\n",
    "\n",
    "df12=df.loc[df['Outcome']==0,['Glucose','BMI']]\n",
    "df12.rename(columns={'Glucose':'Glucose without Diabetes'},inplace=True)\n",
    "df13=df.loc[df['Outcome']==1,['Glucose','BMI']]\n",
    "df13.rename(columns={'Glucose':'Glucose with Diabetes'},inplace=True)\n",
    "fig, axes=plt.subplots(1,2, figsize=(15,7), sharey=True);\n",
    "fig.suptitle('Glucose vs BMI');\n",
    "sns.boxplot(ax=axes[0],x='Glucose without Diabetes', y='BMI', data=df12);\n",
    "sns.boxplot(ax=axes[1],x='Glucose with Diabetes', y='BMI', data=df13);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creating a dataframe of BMI of pregnant females without and with diabetes\n",
    "\n",
    "df10=df.loc[df['Outcome']==0,['Pregnancies','BMI']]\n",
    "df10.reset_index(inplace=True)\n",
    "del df10['index']\n",
    "df10.rename(columns={'Pregnancies':'Pregnancies without diabetes'},inplace=True)\n",
    "\n",
    "df11=df.loc[df['Outcome']==1,['Pregnancies','BMI']]\n",
    "df11.reset_index(inplace=True)\n",
    "del df11['index']\n",
    "df11.rename(columns={'Pregnancies':'Pregnancies with Diabetes'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#creating 2 boxplots comparing BMI readings between pregnant females without and with diabetes\n",
    "\n",
    "fig, axes = plt.subplots(1,2,figsize=(15,5),sharey=True)\n",
    "fig.suptitle('Number of pregnancies vs BMI')\n",
    "sns.boxplot(ax=axes[0],x='Pregnancies without diabetes', y='BMI', data=df10);\n",
    "sns.boxplot(ax=axes[1],x='Pregnancies with Diabetes', y='BMI', data=df11);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PREDICTOR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#split the x, y values between training and testing sets (testing 25%)\n",
    "#convert x values to a standard normal distribution thru StandardScaler\n",
    "#transform x values to a range between 0,1\n",
    "#KEY in according to the order: No.of Pregnancies,Glucose,BloodPressure,SkinThickness,Insulin,BMI,DiabetesPedigree,Age\n",
    "\n",
    "p=np.array([[4,100,90,20,90,20,0.1,30]])\n",
    "f=np.array([[7,140,80,35,120,27,1,30]])\n",
    "a=np.array([[3,200,60,15,80,20,0.5,70]])\n",
    "b=np.array([[5,250,30,30,60,30,2,25]])\n",
    "h=np.array([[2,80,70,20,25,15,0.1,30]])\n",
    "\n",
    "\n",
    "x_train, x_test, y_train, y_test = train_test_split(x,y, test_size=.25,  shuffle=True)\n",
    "lmx = make_pipeline(StandardScaler(),MinMaxScaler(), LogisticRegression())\n",
    "lmx.fit(x_train,y_train)\n",
    "y_pred=lmx.predict(x_test) \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[108,  22],\n",
       "       [ 21,  41]], dtype=int64)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#import sklearn confusion matrix\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import classification_report\n",
    "conf_mat=confusion_matrix(y_test, y_pred)\n",
    "report=classification_report(y_test, y_pred)\n",
    "conf_mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.78"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Classification Accuracy - use float to perform true division, not integer division\n",
    "tp = conf_mat[0,0]\n",
    "tn = conf_mat[1,1]\n",
    "fp = conf_mat[0,1]\n",
    "fn = conf_mat[1,0]\n",
    "ca = round((tp+tn) / (float(tp+tn+fp+fn)),2)\n",
    "ca"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification report: \n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.84      0.83      0.83       130\n",
      "           1       0.65      0.66      0.66        62\n",
      "\n",
      "    accuracy                           0.78       192\n",
      "   macro avg       0.74      0.75      0.74       192\n",
      "weighted avg       0.78      0.78      0.78       192\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('Classification report: \\n',report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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