model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>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>5926</th>\n",
       "      <td>1356-MKYSK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>6</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>78.65</td>\n",
       "      <td>483.3</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2350</th>\n",
       "      <td>8739-XNIKG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>5</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>84.00</td>\n",
       "      <td>424.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2432</th>\n",
       "      <td>0023-UYUPN</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>50</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</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>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>25.20</td>\n",
       "      <td>1306.3</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5669</th>\n",
       "      <td>1217-VASWC</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>43</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>100.55</td>\n",
       "      <td>4304</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1538</th>\n",
       "      <td>6326-MTTXK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>8</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>100.85</td>\n",
       "      <td>819.55</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  \\\n",
       "5926  1356-MKYSK    Male              0      No         No       6   \n",
       "2350  8739-XNIKG  Female              0      No         No       5   \n",
       "2432  0023-UYUPN  Female              1     Yes         No      50   \n",
       "5669  1217-VASWC    Male              1     Yes         No      43   \n",
       "1538  6326-MTTXK    Male              0      No         No       8   \n",
       "\n",
       "     PhoneService MultipleLines InternetService       OnlineSecurity  ...  \\\n",
       "5926          Yes            No             DSL                  Yes  ...   \n",
       "2350          Yes           Yes     Fiber optic                   No  ...   \n",
       "2432          Yes           Yes              No  No internet service  ...   \n",
       "5669          Yes            No     Fiber optic                   No  ...   \n",
       "1538          Yes           Yes     Fiber optic                   No  ...   \n",
       "\n",
       "         DeviceProtection          TechSupport          StreamingTV  \\\n",
       "5926                  Yes                  Yes                  Yes   \n",
       "2350                   No                   No                  Yes   \n",
       "2432  No internet service  No internet service  No internet service   \n",
       "5669                  Yes                   No                  Yes   \n",
       "1538                   No                   No                  Yes   \n",
       "\n",
       "          StreamingMovies        Contract PaperlessBilling  \\\n",
       "5926                  Yes  Month-to-month               No   \n",
       "2350                   No  Month-to-month              Yes   \n",
       "2432  No internet service        One year               No   \n",
       "5669                  Yes        One year              Yes   \n",
       "1538                  Yes  Month-to-month               No   \n",
       "\n",
       "                  PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
       "5926    Credit card (automatic)          78.65         483.3    No  \n",
       "2350           Electronic check          84.00        424.75    No  \n",
       "2432           Electronic check          25.20        1306.3    No  \n",
       "5669  Bank transfer (automatic)         100.55          4304    No  \n",
       "1538           Electronic check         100.85        819.55   Yes  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "df = pd.read_csv('customer_churn.csv')\n",
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df.drop('customerID', axis='columns', inplace=True)\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['29.85', '1889.5', '108.15', ..., '346.45', '306.6', '6844.5'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.TotalCharges.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 29.85,  56.95,  53.85, ...,  29.6 ,  74.4 , 105.65])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.MonthlyCharges.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       False\n",
       "1       False\n",
       "2       False\n",
       "3       False\n",
       "4       False\n",
       "        ...  \n",
       "7038    False\n",
       "7039    False\n",
       "7040    False\n",
       "7041    False\n",
       "7042    False\n",
       "Name: TotalCharges, Length: 7043, dtype: bool"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_numeric(df.TotalCharges, errors='coerce').isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11, 20)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[pd.to_numeric(df.TotalCharges, errors='coerce').isnull()].shape   #coerce to avoid blank spaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7043, 20)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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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>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": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[pd.to_numeric(df.TotalCharges, errors='coerce').isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' '"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[488]['TotalCharges']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7032, 20)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = df[df.TotalCharges != \" \"]\n",
    "df1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.dtypes #now we can convert TotalCharges into float without having that issue of blank spaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Acer\\AppData\\Local\\Temp\\ipykernel_18912\\3277851254.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df1.TotalCharges = pd.to_numeric(df1.TotalCharges)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.TotalCharges = pd.to_numeric(df1.TotalCharges)\n",
    "df1.TotalCharges.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x20da9256550>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tenure_churn_no = df1[df1.Churn == 'No'].tenure\n",
    "tenure_churn_yes= df1[df1.Churn == 'Yes'].tenure\n",
    "\n",
    "\n",
    "plt.xlabel(\"Tenure\")\n",
    "plt.ylabel(\"Number of Customers\")\n",
    "plt.title(\"Customer churn prediction visualization\")\n",
    "plt.hist([tenure_churn_yes, tenure_churn_no], color = ['green', 'red'], label=['Churn = Yes', 'Churn = No'])\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x20da9169750>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "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.xlabel(\"Monthly Charges\")\n",
    "plt.ylabel(\"Number of Customers\")\n",
    "plt.title(\"Customer churn prediction visualization\")\n",
    "\n",
    "plt.hist([mc_churn_yes, mc_churn_no], color=['green', 'red'], label=['Churn = Yes', 'Churn = No'])\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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 phone service' 'No' 'Yes']\n",
      "InternetService : ['DSL' 'Fiber optic' 'No']\n",
      "OnlineSecurity : ['No' 'Yes' 'No internet service']\n",
      "OnlineBackup : ['Yes' 'No' 'No internet service']\n",
      "DeviceProtection : ['No' 'Yes' 'No internet service']\n",
      "TechSupport : ['No' 'Yes' 'No internet service']\n",
      "StreamingTV : ['No' 'Yes' 'No internet service']\n",
      "StreamingMovies : ['No' 'Yes' 'No internet service']\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": [
    "def print_unique_col_values(df):\n",
    "    for column in df:\n",
    "        if( df[column].dtypes=='object'):\n",
    "            print(f\"{column} : {df[column].unique()}\")\n",
    "print_unique_col_values(df1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Acer\\AppData\\Local\\Temp\\ipykernel_18912\\755694447.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df1.replace('No internet service', 'No', inplace=True)\n",
      "C:\\Users\\Acer\\AppData\\Local\\Temp\\ipykernel_18912\\755694447.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df1.replace('No phone service', 'No', inplace=True)\n"
     ]
    }
   ],
   "source": [
    "df1.replace('No internet service', 'No', inplace=True)\n",
    "df1.replace('No phone service', 'No', inplace=True)\n",
    "print_unique_col_values(df1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gender : ['Female' 'Male']\n",
      "SeniorCitizen : [0 1]\n",
      "Partner : [1 0]\n",
      "Dependents : [0 1]\n",
      "tenure : [ 1 34  2 45  8 22 10 28 62 13 16 58 49 25 69 52 71 21 12 30 47 72 17 27\n",
      "  5 46 11 70 63 43 15 60 18 66  9  3 31 50 64 56  7 42 35 48 29 65 38 68\n",
      " 32 55 37 36 41  6  4 33 67 23 57 61 14 20 53 40 59 24 44 19 54 51 26 39]\n",
      "PhoneService : [0 1]\n",
      "MultipleLines : [0 1]\n",
      "InternetService : ['DSL' 'Fiber optic' 'Nope']\n",
      "OnlineSecurity : [0 1]\n",
      "OnlineBackup : [1 0]\n",
      "DeviceProtection : [0 1]\n",
      "TechSupport : [0 1]\n",
      "StreamingTV : [0 1]\n",
      "StreamingMovies : [0 1]\n",
      "Contract : ['Month-to-month' 'One year' 'Two year']\n",
      "PaperlessBilling : [1 0]\n",
      "PaymentMethod : ['Electronic check' 'Mailed check' 'Bank transfer (automatic)'\n",
      " 'Credit card (automatic)']\n",
      "MonthlyCharges : [29.85 56.95 53.85 ... 63.1  44.2  78.7 ]\n",
      "TotalCharges : [  29.85 1889.5   108.15 ...  346.45  306.6  6844.5 ]\n",
      "Churn : [0 1]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Acer\\AppData\\Local\\Temp\\ipykernel_18912\\2440601334.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df1['InternetService'].replace('No', 'Nope', inplace=True)\n",
      "C:\\Users\\Acer\\AppData\\Local\\Temp\\ipykernel_18912\\2440601334.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df1.replace({'Yes': 1, 'No' : 0}, inplace = True)\n"
     ]
    }
   ],
   "source": [
    "df1['InternetService'].replace('No', 'Nope', inplace=True)\n",
    "df1.replace({'Yes': 1, 'No' : 0}, inplace = True)\n",
    "for col in df1:\n",
    "    print(f\"{col} : {df1[col].unique()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
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