telecom_customer_churn.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3d2ed906",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "c4fa7fc5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\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>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>...</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0  7590-VHVEG  Female              0     Yes         No       1           No   \n",
       "1  5575-GNVDE    Male              0      No         No      34          Yes   \n",
       "2  3668-QPYBK    Male              0      No         No       2          Yes   \n",
       "3  7795-CFOCW    Male              0      No         No      45           No   \n",
       "4  9237-HQITU  Female              0      No         No       2          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
       "0  No phone service             DSL             No  ...               No   \n",
       "1                No             DSL            Yes  ...              Yes   \n",
       "2                No             DSL            Yes  ...               No   \n",
       "3  No phone service             DSL            Yes  ...              Yes   \n",
       "4                No     Fiber optic             No  ...               No   \n",
       "\n",
       "  TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
       "0          No          No              No  Month-to-month              Yes   \n",
       "1          No          No              No        One year               No   \n",
       "2          No          No              No  Month-to-month              Yes   \n",
       "3         Yes          No              No        One year               No   \n",
       "4          No          No              No  Month-to-month              Yes   \n",
       "\n",
       "               PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
       "0           Electronic check          29.85         29.85    No  \n",
       "1               Mailed check          56.95        1889.5    No  \n",
       "2               Mailed check          53.85        108.15   Yes  \n",
       "3  Bank transfer (automatic)          42.30       1840.75    No  \n",
       "4           Electronic check          70.70        151.65   Yes  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.read_csv('telecom_customer_churn.csv')\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "80f76b5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7043, 21)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d49cf49",
   "metadata": {},
   "source": [
    "### Drop irrelevant columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "cf9095b0",
   "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>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0  Female              0     Yes         No       1           No   \n",
       "1    Male              0      No         No      34          Yes   \n",
       "2    Male              0      No         No       2          Yes   \n",
       "3    Male              0      No         No      45           No   \n",
       "4  Female              0      No         No       2          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
       "0  No phone service             DSL             No          Yes   \n",
       "1                No             DSL            Yes           No   \n",
       "2                No             DSL            Yes          Yes   \n",
       "3  No phone service             DSL            Yes           No   \n",
       "4                No     Fiber optic             No           No   \n",
       "\n",
       "  DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
       "0               No          No          No              No  Month-to-month   \n",
       "1              Yes          No          No              No        One year   \n",
       "2               No          No          No              No  Month-to-month   \n",
       "3              Yes         Yes          No              No        One year   \n",
       "4               No          No          No              No  Month-to-month   \n",
       "\n",
       "  PaperlessBilling              PaymentMethod  MonthlyCharges TotalCharges  \\\n",
       "0              Yes           Electronic check           29.85        29.85   \n",
       "1               No               Mailed check           56.95       1889.5   \n",
       "2              Yes               Mailed check           53.85       108.15   \n",
       "3               No  Bank transfer (automatic)           42.30      1840.75   \n",
       "4              Yes           Electronic check           70.70       151.65   \n",
       "\n",
       "  Churn  \n",
       "0    No  \n",
       "1    No  \n",
       "2   Yes  \n",
       "3    No  \n",
       "4   Yes  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df1.drop({'customerID'}, axis='columns')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "86f59af2",
   "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>SeniorCitizen</th>\n",
       "      <th>tenure</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7043.000000</td>\n",
       "      <td>7043.000000</td>\n",
       "      <td>7043.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.162147</td>\n",
       "      <td>32.371149</td>\n",
       "      <td>64.761692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.368612</td>\n",
       "      <td>24.559481</td>\n",
       "      <td>30.090047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>35.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>70.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>89.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>118.750000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       SeniorCitizen       tenure  MonthlyCharges\n",
       "count    7043.000000  7043.000000     7043.000000\n",
       "mean        0.162147    32.371149       64.761692\n",
       "std         0.368612    24.559481       30.090047\n",
       "min         0.000000     0.000000       18.250000\n",
       "25%         0.000000     9.000000       35.500000\n",
       "50%         0.000000    29.000000       70.350000\n",
       "75%         0.000000    55.000000       89.850000\n",
       "max         1.000000    72.000000      118.750000"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "95766734",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' '"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['TotalCharges'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "dbf5b570",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .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>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>52.55</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.25</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>936</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>80.85</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1082</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>25.75</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1340</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>56.05</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3331</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>19.85</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3826</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>25.35</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4380</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.00</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5218</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>19.70</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6670</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>73.35</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6754</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>61.90</td>\n",
       "      <td></td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "488   Female              0     Yes        Yes       0           No   \n",
       "753     Male              0      No        Yes       0          Yes   \n",
       "936   Female              0     Yes        Yes       0          Yes   \n",
       "1082    Male              0     Yes        Yes       0          Yes   \n",
       "1340  Female              0     Yes        Yes       0           No   \n",
       "3331    Male              0     Yes        Yes       0          Yes   \n",
       "3826    Male              0     Yes        Yes       0          Yes   \n",
       "4380  Female              0     Yes        Yes       0          Yes   \n",
       "5218    Male              0     Yes        Yes       0          Yes   \n",
       "6670  Female              0     Yes        Yes       0          Yes   \n",
       "6754    Male              0      No        Yes       0          Yes   \n",
       "\n",
       "         MultipleLines InternetService       OnlineSecurity  \\\n",
       "488   No phone service             DSL                  Yes   \n",
       "753                 No              No  No internet service   \n",
       "936                 No             DSL                  Yes   \n",
       "1082               Yes              No  No internet service   \n",
       "1340  No phone service             DSL                  Yes   \n",
       "3331                No              No  No internet service   \n",
       "3826               Yes              No  No internet service   \n",
       "4380                No              No  No internet service   \n",
       "5218                No              No  No internet service   \n",
       "6670               Yes             DSL                   No   \n",
       "6754               Yes             DSL                  Yes   \n",
       "\n",
       "             OnlineBackup     DeviceProtection          TechSupport  \\\n",
       "488                    No                  Yes                  Yes   \n",
       "753   No internet service  No internet service  No internet service   \n",
       "936                   Yes                  Yes                   No   \n",
       "1082  No internet service  No internet service  No internet service   \n",
       "1340                  Yes                  Yes                  Yes   \n",
       "3331  No internet service  No internet service  No internet service   \n",
       "3826  No internet service  No internet service  No internet service   \n",
       "4380  No internet service  No internet service  No internet service   \n",
       "5218  No internet service  No internet service  No internet service   \n",
       "6670                  Yes                  Yes                  Yes   \n",
       "6754                  Yes                   No                  Yes   \n",
       "\n",
       "              StreamingTV      StreamingMovies  Contract PaperlessBilling  \\\n",
       "488                   Yes                   No  Two year              Yes   \n",
       "753   No internet service  No internet service  Two year               No   \n",
       "936                   Yes                  Yes  Two year               No   \n",
       "1082  No internet service  No internet service  Two year               No   \n",
       "1340                  Yes                   No  Two year               No   \n",
       "3331  No internet service  No internet service  Two year               No   \n",
       "3826  No internet service  No internet service  Two year               No   \n",
       "4380  No internet service  No internet service  Two year               No   \n",
       "5218  No internet service  No internet service  One year              Yes   \n",
       "6670                  Yes                   No  Two year               No   \n",
       "6754                   No                   No  Two year              Yes   \n",
       "\n",
       "                  PaymentMethod  MonthlyCharges TotalCharges Churn  \n",
       "488   Bank transfer (automatic)           52.55                 No  \n",
       "753                Mailed check           20.25                 No  \n",
       "936                Mailed check           80.85                 No  \n",
       "1082               Mailed check           25.75                 No  \n",
       "1340    Credit card (automatic)           56.05                 No  \n",
       "3331               Mailed check           19.85                 No  \n",
       "3826               Mailed check           25.35                 No  \n",
       "4380               Mailed check           20.00                 No  \n",
       "5218               Mailed check           19.70                 No  \n",
       "6670               Mailed check           73.35                 No  \n",
       "6754  Bank transfer (automatic)           61.90                 No  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['TotalCharges'] == ' ']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "570b47ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
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       "        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>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0  Female              0     Yes         No       1           No   \n",
       "1    Male              0      No         No      34          Yes   \n",
       "2    Male              0      No         No       2          Yes   \n",
       "3    Male              0      No         No      45           No   \n",
       "4  Female              0      No         No       2          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
       "0  No phone service             DSL             No          Yes   \n",
       "1                No             DSL            Yes           No   \n",
       "2                No             DSL            Yes          Yes   \n",
       "3  No phone service             DSL            Yes           No   \n",
       "4                No     Fiber optic             No           No   \n",
       "\n",
       "  DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
       "0               No          No          No              No  Month-to-month   \n",
       "1              Yes          No          No              No        One year   \n",
       "2               No          No          No              No  Month-to-month   \n",
       "3              Yes         Yes          No              No        One year   \n",
       "4               No          No          No              No  Month-to-month   \n",
       "\n",
       "  PaperlessBilling              PaymentMethod  MonthlyCharges TotalCharges  \\\n",
       "0              Yes           Electronic check           29.85        29.85   \n",
       "1               No               Mailed check           56.95       1889.5   \n",
       "2              Yes               Mailed check           53.85       108.15   \n",
       "3               No  Bank transfer (automatic)           42.30      1840.75   \n",
       "4              Yes           Electronic check           70.70       151.65   \n",
       "\n",
       "  Churn  \n",
       "0    No  \n",
       "1    No  \n",
       "2   Yes  \n",
       "3    No  \n",
       "4   Yes  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df['TotalCharges'] != ' ']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "fd62bc68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gender               object\n",
       "SeniorCitizen         int64\n",
       "Partner              object\n",
       "Dependents           object\n",
       "tenure                int64\n",
       "PhoneService         object\n",
       "MultipleLines        object\n",
       "InternetService      object\n",
       "OnlineSecurity       object\n",
       "OnlineBackup         object\n",
       "DeviceProtection     object\n",
       "TechSupport          object\n",
       "StreamingTV          object\n",
       "StreamingMovies      object\n",
       "Contract             object\n",
       "PaperlessBilling     object\n",
       "PaymentMethod        object\n",
       "MonthlyCharges      float64\n",
       "TotalCharges         object\n",
       "Churn                object\n",
       "dtype: object"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "49eb4ee1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['TotalCharges'] = df['TotalCharges'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "65f9548d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gender               object\n",
       "SeniorCitizen         int64\n",
       "Partner              object\n",
       "Dependents           object\n",
       "tenure                int64\n",
       "PhoneService         object\n",
       "MultipleLines        object\n",
       "InternetService      object\n",
       "OnlineSecurity       object\n",
       "OnlineBackup         object\n",
       "DeviceProtection     object\n",
       "TechSupport          object\n",
       "StreamingTV          object\n",
       "StreamingMovies      object\n",
       "Contract             object\n",
       "PaperlessBilling     object\n",
       "PaymentMethod        object\n",
       "MonthlyCharges      float64\n",
       "TotalCharges        float64\n",
       "Churn                object\n",
       "dtype: object"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e4c29ae",
   "metadata": {},
   "source": [
    "### Customer Churn Prediction Based on Customer Tenure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "9fc1582f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1477b44c160>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "tenure_churn_no = df[df.Churn=='No'].tenure\n",
    "tenure_churn_yes  = df[df.Churn=='Yes'].tenure\n",
    "\n",
    "plt.hist([tenure_churn_yes, tenure_churn_no], color=['green', 'red'], label=['Churn=Yes', 'Churn=No'])\n",
    "plt.xlabel('Tenure')\n",
    "plt.ylabel('Number of Customers')\n",
    "plt.title('Customer Churn Prediction Based on Customer Tenure')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbcc6e74",
   "metadata": {},
   "source": [
    "### Customer Churn Prediction Based on Monthly Charges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "2c9563d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1477b4e0100>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "mc_churn_no = df[df.Churn=='No'].MonthlyCharges\n",
    "mc_churn_yes  = df[df.Churn=='Yes'].MonthlyCharges\n",
    "\n",
    "plt.hist([mc_churn_yes, mc_churn_no], color=['green', 'red'], label=['Churn=Yes', 'Churn=No'])\n",
    "plt.xlabel('Monthly Charges')\n",
    "plt.ylabel('Number of Customers')\n",
    "plt.title('Customer Churn Prediction Based on Customer Tenure')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "d6184ffa",
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_unique_col_values(data_frame):\n",
    "    for column in df:\n",
    "        if df[column].dtypes=='object': \n",
    "            print(f'{column} : {df[column].unique()}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "7e0e2080",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gender : ['Female' 'Male']\n",
      "Partner : ['Yes' 'No']\n",
      "Dependents : ['No' 'Yes']\n",
      "PhoneService : ['No' 'Yes']\n",
      "MultipleLines : ['No' 'Yes']\n",
      "InternetService : ['DSL' 'Fiber optic' 'No']\n",
      "OnlineSecurity : ['No' 'Yes']\n",
      "OnlineBackup : ['Yes' 'No']\n",
      "DeviceProtection : ['No' 'Yes']\n",
      "TechSupport : ['No' 'Yes']\n",
      "StreamingTV : ['No' 'Yes']\n",
      "StreamingMovies : ['No' 'Yes']\n",
      "Contract : ['Month-to-month' 'One year' 'Two year']\n",
      "PaperlessBilling : ['Yes' 'No']\n",
      "PaymentMethod : ['Electronic check' 'Mailed check' 'Bank transfer (automatic)'\n",
      " 'Credit card (automatic)']\n",
      "Churn : ['No' 'Yes']\n"
     ]
    }
   ],
   "source": [
    "print_unique_col_values(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "468819ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.replace('No internet service', 'No', inplace=True)\n",
    "df.replace('No phone service', 'No', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "fb7914bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gender : ['Female' 'Male']\n",
      "Partner : ['Yes' 'No']\n",
      "Dependents : ['No' 'Yes']\n",
      "PhoneService : ['No' 'Yes']\n",
      "MultipleLines : ['No' 'Yes']\n",
      "InternetService : ['DSL' 'Fiber optic' 'No']\n",
      "OnlineSecurity : ['No' 'Yes']\n",
      "OnlineBackup : ['Yes' 'No']\n",
      "DeviceProtection : ['No' 'Yes']\n",
      "TechSupport : ['No' 'Yes']\n",
      "StreamingTV : ['No' 'Yes']\n",
      "StreamingMovies : ['No' 'Yes']\n",
      "Contract : ['Month-to-month' 'One year' 'Two year']\n",
      "PaperlessBilling : ['Yes' 'No']\n",
      "PaymentMethod : ['Electronic check' 'Mailed check' 'Bank transfer (automatic)'\n",
      " 'Credit card (automatic)']\n",
      "Churn : ['No' 'Yes']\n"
     ]
    }
   ],
   "source": [
    "print_unique_col_values(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "db672c4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "yes_no_columns = ['Partner','Dependents','PhoneService','MultipleLines','OnlineSecurity','OnlineBackup',\n",
    "                  'DeviceProtection','TechSupport','StreamingTV','StreamingMovies','PaperlessBilling','Churn']\n",
    "\n",
    "for col in yes_no_columns:\n",
    "    df[col].replace({'Yes' : 1,\n",
    "                     'No' : 0}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "f4e15b43",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['gender'].replace({'Female' : 1,\n",
    "                     'Male' : 0}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "6c86221c",
   "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>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
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       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>...</th>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender  SeniorCitizen  Partner  Dependents  tenure  PhoneService  \\\n",
       "0       1              0        1           0       1             0   \n",
       "1       0              0        0           0      34             1   \n",
       "2       0              0        0           0       2             1   \n",
       "3       0              0        0           0      45             0   \n",
       "4       1              0        0           0       2             1   \n",
       "\n",
       "   MultipleLines  OnlineSecurity  OnlineBackup  DeviceProtection  ...  \\\n",
       "0              0               0             1                 0  ...   \n",
       "1              0               1             0                 1  ...   \n",
       "2              0               1             1                 0  ...   \n",
       "3              0               1             0                 1  ...   \n",
       "4              0               0             0                 0  ...   \n",
       "\n",
       "   InternetService_DSL  InternetService_Fiber optic  InternetService_No  \\\n",
       "0                    1                            0                   0   \n",
       "1                    1                            0                   0   \n",
       "2                    1                            0                   0   \n",
       "3                    1                            0                   0   \n",
       "4                    0                            1                   0   \n",
       "\n",
       "   Contract_Month-to-month  Contract_One year  Contract_Two year  \\\n",
       "0                        1                  0                  0   \n",
       "1                        0                  1                  0   \n",
       "2                        1                  0                  0   \n",
       "3                        0                  1                  0   \n",
       "4                        1                  0                  0   \n",
       "\n",
       "   PaymentMethod_Bank transfer (automatic)  \\\n",
       "0                                        0   \n",
       "1                                        0   \n",
       "2                                        0   \n",
       "3                                        1   \n",
       "4                                        0   \n",
       "\n",
       "   PaymentMethod_Credit card (automatic)  PaymentMethod_Electronic check  \\\n",
       "0                                      0                               1   \n",
       "1                                      0                               0   \n",
       "2                                      0                               0   \n",
       "3                                      0                               0   \n",
       "4                                      0                               1   \n",
       "\n",
       "   PaymentMethod_Mailed check  \n",
       "0                           0  \n",
       "1                           1  \n",
       "2                           1  \n",
       "3                           0  \n",
       "4                           0  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.get_dummies(df, columns=['InternetService','Contract','PaymentMethod'])\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "1fdd6b06",
   "metadata": {},
   "outputs": [],
   "source": [
    "cols_to_scale = ['tenure','MonthlyCharges','TotalCharges']\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler = MinMaxScaler()\n",
    "\n",
    "df1[cols_to_scale] = scaler.fit_transform(df1[cols_to_scale])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "18fc01bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>gender</th>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      gender  SeniorCitizen  Partner  Dependents    tenure  PhoneService  \\\n",
       "4096       1              0        0           0  0.267606             1   \n",
       "1947       1              0        0           0  0.971831             1   \n",
       "693        1              0        0           0  0.028169             1   \n",
       "5715       0              0        0           0  0.436620             1   \n",
       "5296       1              0        0           0  0.788732             0   \n",
       "\n",
       "      MultipleLines  OnlineSecurity  OnlineBackup  DeviceProtection  ...  \\\n",
       "4096              0               1             0                 1  ...   \n",
       "1947              1               0             1                 1  ...   \n",
       "693               1               0             0                 0  ...   \n",
       "5715              1               1             1                 0  ...   \n",
       "5296              0               1             0                 1  ...   \n",
       "\n",
       "      InternetService_DSL  InternetService_Fiber optic  InternetService_No  \\\n",
       "4096                    0                            1                   0   \n",
       "1947                    0                            1                   0   \n",
       "693                     0                            1                   0   \n",
       "5715                    0                            1                   0   \n",
       "5296                    1                            0                   0   \n",
       "\n",
       "      Contract_Month-to-month  Contract_One year  Contract_Two year  \\\n",
       "4096                        1                  0                  0   \n",
       "1947                        0                  1                  0   \n",
       "693                         1                  0                  0   \n",
       "5715                        1                  0                  0   \n",
       "5296                        0                  1                  0   \n",
       "\n",
       "      PaymentMethod_Bank transfer (automatic)  \\\n",
       "4096                                        1   \n",
       "1947                                        1   \n",
       "693                                         0   \n",
       "5715                                        0   \n",
       "5296                                        0   \n",
       "\n",
       "      PaymentMethod_Credit card (automatic)  PaymentMethod_Electronic check  \\\n",
       "4096                                      0                               0   \n",
       "1947                                      0                               0   \n",
       "693                                       1                               0   \n",
       "5715                                      1                               0   \n",
       "5296                                      1                               0   \n",
       "\n",
       "      PaymentMethod_Mailed check  \n",
       "4096                           0  \n",
       "1947                           0  \n",
       "693                            0  \n",
       "5715                           0  \n",
       "5296                           0  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "c89b00fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df1.drop('Churn', axis='columns')\n",
    "y = df1.Churn"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "948aa272",
   "metadata": {},
   "source": [
    "### Find the best performing model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "54ce6a65",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_params = {\n",
    "    'svm':{\n",
    "        'model': SVC(gamma='auto'),\n",
    "        'params': {\n",
    "            'C': [1,10,20],\n",
    "            'kernel': ['rbf', 'linear']\n",
    "        }\n",
    "    },\n",
    "    'random_forest':{\n",
    "        'model': RandomForestClassifier(),\n",
    "        'params': {\n",
    "            'n_estimators': [1,5,10]\n",
    "        }\n",
    "    },\n",
    "    'log_reg':{\n",
    "        'model': LogisticRegression(),\n",
    "        'params': {\n",
    "            'C': [1,5,10]\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "ab8654d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "scores = []\n",
    "\n",
    "for model_name, mp in model_params.items():\n",
    "    clf = GridSearchCV(mp['model'], mp['params'], cv=5, return_train_score=False)\n",
    "    clf.fit(X, y)\n",
    "    scores.append({\n",
    "        'model': model_name,\n",
    "        'best_score': clf.best_score_,\n",
    "        'best_params': clf.best_params_\n",
    "    })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "3297eb44",
   "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>model</th>\n",
       "      <th>best_score</th>\n",
       "      <th>best_params</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>svm</td>\n",
       "      <td>0.800339</td>\n",
       "      <td>{'C': 10, 'kernel': 'rbf'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>random_forest</td>\n",
       "      <td>0.777160</td>\n",
       "      <td>{'n_estimators': 10}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>log_reg</td>\n",
       "      <td>0.803326</td>\n",
       "      <td>{'C': 5}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           model  best_score                 best_params\n",
       "0            svm    0.800339  {'C': 10, 'kernel': 'rbf'}\n",
       "1  random_forest    0.777160        {'n_estimators': 10}\n",
       "2        log_reg    0.803326                    {'C': 5}"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score = pd.DataFrame(scores, columns=['model','best_score','best_params'])\n",
    "df_score"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95e27424",
   "metadata": {},
   "source": [
    "### Use data to train the best performing model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "9f058c01",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "769bec20",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = LogisticRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "4ff7f1aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "6a573ce9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8083555555555556"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.score(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "0dde675a",
   "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>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>...</th>\n",
       "      <th>InternetService_DSL</th>\n",
       "      <th>InternetService_Fiber optic</th>\n",
       "      <th>InternetService_No</th>\n",
       "      <th>Contract_Month-to-month</th>\n",
       "      <th>Contract_One year</th>\n",
       "      <th>Contract_Two year</th>\n",
       "      <th>PaymentMethod_Bank transfer (automatic)</th>\n",
       "      <th>PaymentMethod_Credit card (automatic)</th>\n",
       "      <th>PaymentMethod_Electronic check</th>\n",
       "      <th>PaymentMethod_Mailed check</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.464789</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.014085</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.619718</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.014085</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender  SeniorCitizen  Partner  Dependents    tenure  PhoneService  \\\n",
       "0       1              0        1           0  0.000000             0   \n",
       "1       0              0        0           0  0.464789             1   \n",
       "2       0              0        0           0  0.014085             1   \n",
       "3       0              0        0           0  0.619718             0   \n",
       "4       1              0        0           0  0.014085             1   \n",
       "\n",
       "   MultipleLines  OnlineSecurity  OnlineBackup  DeviceProtection  ...  \\\n",
       "0              0               0             1                 0  ...   \n",
       "1              0               1             0                 1  ...   \n",
       "2              0               1             1                 0  ...   \n",
       "3              0               1             0                 1  ...   \n",
       "4              0               0             0                 0  ...   \n",
       "\n",
       "   InternetService_DSL  InternetService_Fiber optic  InternetService_No  \\\n",
       "0                    1                            0                   0   \n",
       "1                    1                            0                   0   \n",
       "2                    1                            0                   0   \n",
       "3                    1                            0                   0   \n",
       "4                    0                            1                   0   \n",
       "\n",
       "   Contract_Month-to-month  Contract_One year  Contract_Two year  \\\n",
       "0                        1                  0                  0   \n",
       "1                        0                  1                  0   \n",
       "2                        1                  0                  0   \n",
       "3                        0                  1                  0   \n",
       "4                        1                  0                  0   \n",
       "\n",
       "   PaymentMethod_Bank transfer (automatic)  \\\n",
       "0                                        0   \n",
       "1                                        0   \n",
       "2                                        0   \n",
       "3                                        1   \n",
       "4                                        0   \n",
       "\n",
       "   PaymentMethod_Credit card (automatic)  PaymentMethod_Electronic check  \\\n",
       "0                                      0                               1   \n",
       "1                                      0                               0   \n",
       "2                                      0                               0   \n",
       "3                                      0                               0   \n",
       "4                                      0                               1   \n",
       "\n",
       "   PaymentMethod_Mailed check  \n",
       "0                           0  \n",
       "1                           1  \n",
       "2                           1  \n",
       "3                           0  \n",
       "4                           0  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30d1858b",
   "metadata": {},
   "source": [
    "### Make prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "65881361",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0], dtype=int64)"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict([[0,34,56.95,1889.50,0,0,1,0,0,0,1,0,0,0,1,1,0,1,0,0,1,0,1,1,2,1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b079f7ca",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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