Untitled1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"WA_Fn-UseC_-Telco-Customer-Churn.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 21 columns):\n",
      "customerID          7043 non-null object\n",
      "gender              7043 non-null object\n",
      "SeniorCitizen       7043 non-null int64\n",
      "Partner             7043 non-null object\n",
      "Dependents          7043 non-null object\n",
      "tenure              7043 non-null int64\n",
      "PhoneService        7043 non-null object\n",
      "MultipleLines       7043 non-null object\n",
      "InternetService     7043 non-null object\n",
      "OnlineSecurity      7043 non-null object\n",
      "OnlineBackup        7043 non-null object\n",
      "DeviceProtection    7043 non-null object\n",
      "TechSupport         7043 non-null object\n",
      "StreamingTV         7043 non-null object\n",
      "StreamingMovies     7043 non-null object\n",
      "Contract            7043 non-null object\n",
      "PaperlessBilling    7043 non-null object\n",
      "PaymentMethod       7043 non-null object\n",
      "MonthlyCharges      7043 non-null float64\n",
      "TotalCharges        7043 non-null object\n",
      "Churn               7043 non-null object\n",
      "dtypes: float64(1), int64(2), object(18)\n",
      "memory usage: 660.3+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[data[\"Churn\"]=='No','Churn'] = 0 \n",
    "data.loc[data[\"Churn\"]=='Yes','Churn'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[data.SeniorCitizen==0,'SeniorCitizen'] = 'Yes' \n",
    "data.loc[data.SeniorCitizen==1,'SeniorCitizen'] = 'NO'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0\n",
       "1       0\n",
       "2       1\n",
       "3       0\n",
       "4       1\n",
       "5       1\n",
       "6       0\n",
       "7       0\n",
       "8       1\n",
       "9       0\n",
       "10      0\n",
       "11      0\n",
       "12      0\n",
       "13      1\n",
       "14      0\n",
       "15      0\n",
       "16      0\n",
       "17      0\n",
       "18      1\n",
       "19      0\n",
       "20      1\n",
       "21      0\n",
       "22      1\n",
       "23      0\n",
       "24      0\n",
       "25      0\n",
       "26      1\n",
       "27      1\n",
       "28      0\n",
       "29      1\n",
       "       ..\n",
       "7013    0\n",
       "7014    0\n",
       "7015    0\n",
       "7016    0\n",
       "7017    0\n",
       "7018    1\n",
       "7019    0\n",
       "7020    0\n",
       "7021    1\n",
       "7022    0\n",
       "7023    0\n",
       "7024    0\n",
       "7025    0\n",
       "7026    1\n",
       "7027    0\n",
       "7028    0\n",
       "7029    0\n",
       "7030    0\n",
       "7031    0\n",
       "7032    1\n",
       "7033    0\n",
       "7034    1\n",
       "7035    0\n",
       "7036    0\n",
       "7037    0\n",
       "7038    0\n",
       "7039    0\n",
       "7040    0\n",
       "7041    1\n",
       "7042    0\n",
       "Name: Churn, Length: 7043, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"Churn\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"gender\")[\"Churn\"].mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"gender\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"Contract\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"Contract\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot_1 = data.groupby(\"PhoneService\").Churn.mean().reset_index()\n",
    "df_plot_2 = data.groupby(\"MultipleLines\").Churn.mean().reset_index()\n",
    "df_plot_3 = data.groupby(\"OnlineSecurity\").Churn.mean().reset_index()\n",
    "df_plot_4 = data.groupby(\"DeviceProtection\").Churn.mean().reset_index()\n",
    "df_plot_5 = data.groupby(\"StreamingTV\").Churn.mean().reset_index()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot_1[\"PhoneService\"],df_plot_1[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAD8CAYAAACb4nSYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAEfBJREFUeJzt3X+QXWV9x/H3x6RAi1VRdjqVEBI1qFgdsWtsx4pORYzjDHHqr2DtRGubsYq2tY6NVUHjtOOP2uofOBI1HWWqAdSxa42l+JOxiuwiCCYaWSKVnXTGaBititDAt3/cE71cN+zZZLMLPO/XzJ19znOe59zvPTfzuYdz7zmkqpAkteF+S12AJGnxGPqS1BBDX5IaYuhLUkMMfUlqiKEvSQ3pFfpJ1iXZnWQ6yeZZ1r88yfVJrk3y5SSnDa17fTdvd5JnLmTxkqT5yVy/00+yDPgO8AxgBpgEzqmqXUNjHlBVP+7aZwOvqKp1Xfh/FFgLPBT4LHBqVd1xNF6MJOnu9TnSXwtMV9Weqrod2A6sHx5wMPA7xwMHP0nWA9ur6raq+i4w3W1PkrQElvcYcxJw89DyDPCk0UFJXgm8BjgG+MOhuVeOzD3p7p7sxBNPrFWrVvUoS5J00NVXX/2Dqhqba1yf0M8sfb9yTqiqLgAuSPIi4I3Axr5zk2wCNgGsXLmSqampHmVJkg5K8t99xvU5vTMDnDy0vALYezfjtwPPmc/cqtpaVeNVNT42NucHlSTpMPUJ/UlgTZLVSY4BNgATwwOSrBlafDZwQ9eeADYkOTbJamANcNWRly1JOhxznt6pqgNJzgUuA5YB26pqZ5ItwFRVTQDnJjkT+D/gFgandujGXQLsAg4Ar/SXO5K0dOb8yeZiGx8fL8/pS9L8JLm6qsbnGucVuZLUEENfkhpi6EtSQwx9SWqIoS9JDelzRa4k/cKqzZ9e6hLus25627OP+nN4pC9JDTH0Jakhhr4kNcTQl6SGGPqS1BBDX5IaYuhLUkMMfUlqiKEvSQ0x9CWpIYa+JDXE0Jekhhj6ktQQQ1+SGmLoS1JDDH1JaoihL0kNMfQlqSGGviQ1xNCXpIYY+pLUkF6hn2Rdkt1JppNsnmX9a5LsSnJdks8lOWVo3R1Jru0eEwtZvCRpfpbPNSDJMuAC4BnADDCZZKKqdg0NuwYYr6qfJfkL4B3AC7t1t1bV4xe4bknSYehzpL8WmK6qPVV1O7AdWD88oKq+UFU/6xavBFYsbJmSpIXQJ/RPAm4eWp7p+g7lZcBnhpaPSzKV5MokzzmMGiVJC2TO0ztAZumrWQcmLwbGgacOda+sqr1JHgZ8Psn1VXXjyLxNwCaAlStX9ir8UFZt/vQRzdeh3fS2Zy/4Nn2/jp6j8X7p3q/Pkf4McPLQ8gpg7+igJGcCbwDOrqrbDvZX1d7u7x7gi8Dpo3OramtVjVfV+NjY2LxegCSpvz6hPwmsSbI6yTHABuAuv8JJcjpwIYPA//5Q/wlJju3aJwJPBoa/AJYkLaI5T+9U1YEk5wKXAcuAbVW1M8kWYKqqJoB3AvcHLk0C8L2qOht4NHBhkjsZfMC8beRXP5KkRdTnnD5VtQPYMdJ33lD7zEPM+wrw2CMpUJK0cLwiV5IaYuhLUkMMfUlqiKEvSQ0x9CWpIYa+JDXE0Jekhhj6ktQQQ1+SGmLoS1JDDH1JaoihL0kNMfQlqSGGviQ1xNCXpIYY+pLUEENfkhpi6EtSQwx9SWqIoS9JDTH0Jakhhr4kNcTQl6SGGPqS1BBDX5IaYuhLUkMMfUlqiKEvSQ3pFfpJ1iXZnWQ6yeZZ1r8mya4k1yX5XJJThtZtTHJD99i4kMVLkuZnztBPsgy4AHgWcBpwTpLTRoZdA4xX1eOAjwHv6OY+GDgfeBKwFjg/yQkLV74kaT76HOmvBaarak9V3Q5sB9YPD6iqL1TVz7rFK4EVXfuZwOVVtb+qbgEuB9YtTOmSpPnqE/onATcPLc90fYfyMuAz85mbZFOSqSRT+/bt61GSJOlw9An9zNJXsw5MXgyMA++cz9yq2lpV41U1PjY21qMkSdLh6BP6M8DJQ8srgL2jg5KcCbwBOLuqbpvPXEnS4ugT+pPAmiSrkxwDbAAmhgckOR24kEHgf39o1WXAWUlO6L7APavrkyQtgeVzDaiqA0nOZRDWy4BtVbUzyRZgqqomGJzOuT9waRKA71XV2VW1P8lbGXxwAGypqv1H5ZVIkuY0Z+gDVNUOYMdI33lD7TPvZu42YNvhFihJWjhekStJDTH0Jakhhr4kNcTQl6SGGPqS1BBDX5IaYuhLUkMMfUlqiKEvSQ0x9CWpIYa+JDXE0Jekhhj6ktQQQ1+SGmLoS1JDDH1JaoihL0kNMfQlqSGGviQ1xNCXpIYY+pLUEENfkhpi6EtSQwx9SWqIoS9JDTH0Jakhhr4kNaRX6CdZl2R3kukkm2dZf0aSryc5kOR5I+vuSHJt95hYqMIlSfO3fK4BSZYBFwDPAGaAySQTVbVraNj3gJcAr51lE7dW1eMXoFZJ0hGaM/SBtcB0Ve0BSLIdWA/8IvSr6qZu3Z1HoUZJ0gLpc3rnJODmoeWZrq+v45JMJbkyyXNmG5BkUzdmat++ffPYtCRpPvqEfmbpq3k8x8qqGgdeBLw7ycN/ZWNVW6tqvKrGx8bG5rFpSdJ89An9GeDkoeUVwN6+T1BVe7u/e4AvAqfPoz5J0gLqE/qTwJokq5McA2wAev0KJ8kJSY7t2icCT2bouwBJ0uKaM/Sr6gBwLnAZ8C3gkqramWRLkrMBkjwxyQzwfODCJDu76Y8GppJ8A/gC8LaRX/1IkhZRn1/vUFU7gB0jfecNtScZnPYZnfcV4LFHWKMkaYF4Ra4kNcTQl6SGGPqS1BBDX5IaYuhLUkMMfUlqiKEvSQ0x9CWpIYa+JDXE0Jekhhj6ktQQQ1+SGmLoS1JDDH1JaoihL0kNMfQlqSGGviQ1xNCXpIYY+pLUEENfkhpi6EtSQwx9SWqIoS9JDTH0Jakhhr4kNcTQl6SGGPqS1JBeoZ9kXZLdSaaTbJ5l/RlJvp7kQJLnjazbmOSG7rFxoQqXJM3fnKGfZBlwAfAs4DTgnCSnjQz7HvAS4CMjcx8MnA88CVgLnJ/khCMvW5J0OPoc6a8FpqtqT1XdDmwH1g8PqKqbquo64M6Ruc8ELq+q/VV1C3A5sG4B6pYkHYY+oX8ScPPQ8kzX10evuUk2JZlKMrVv376em5YkzVef0M8sfdVz+73mVtXWqhqvqvGxsbGem5YkzVef0J8BTh5aXgHs7bn9I5krSVpgfUJ/EliTZHWSY4ANwETP7V8GnJXkhO4L3LO6PknSEpgz9KvqAHAug7D+FnBJVe1MsiXJ2QBJnphkBng+cGGSnd3c/cBbGXxwTAJbuj5J0hJY3mdQVe0Adoz0nTfUnmRw6ma2uduAbUdQoyRpgXhFriQ1xNCXpIYY+pLUEENfkhpi6EtSQwx9SWqIoS9JDTH0Jakhhr4kNcTQl6SGGPqS1BBDX5IaYuhLUkMMfUlqiKEvSQ0x9CWpIYa+JDXE0Jekhhj6ktQQQ1+SGmLoS1JDDH1JaoihL0kNMfQlqSGGviQ1xNCXpIYY+pLUkF6hn2Rdkt1JppNsnmX9sUku7tZ/Lcmqrn9VkluTXNs93rew5UuS5mP5XAOSLAMuAJ4BzACTSSaqatfQsJcBt1TVI5JsAN4OvLBbd2NVPX6B65YkHYY+R/prgemq2lNVtwPbgfUjY9YDH+raHwOeniQLV6YkaSH0Cf2TgJuHlme6vlnHVNUB4EfAQ7p1q5Nck+RLSZ5yhPVKko7AnKd3gNmO2KvnmP8BVlbVD5P8LvDJJI+pqh/fZXKyCdgEsHLlyh4lSZIOR58j/Rng5KHlFcDeQ41Jshx4ILC/qm6rqh8CVNXVwI3AqaNPUFVbq2q8qsbHxsbm/yokSb30Cf1JYE2S1UmOATYAEyNjJoCNXft5wOerqpKMdV8Ek+RhwBpgz8KULkmarzlP71TVgSTnApcBy4BtVbUzyRZgqqomgA8CFyWZBvYz+GAAOAPYkuQAcAfw8qrafzReiCRpbn3O6VNVO4AdI33nDbV/Djx/lnkfBz5+hDVKkhaIV+RKUkMMfUlqiKEvSQ0x9CWpIYa+JDXE0Jekhhj6ktQQQ1+SGmLoS1JDDH1JaoihL0kNMfQlqSGGviQ1xNCXpIYY+pLUEENfkhpi6EtSQwx9SWqIoS9JDTH0Jakhhr4kNcTQl6SGGPqS1BBDX5IaYuhLUkMMfUlqiKEvSQ3pFfpJ1iXZnWQ6yeZZ1h+b5OJu/deSrBpa9/quf3eSZy5c6ZKk+Zoz9JMsAy4AngWcBpyT5LSRYS8DbqmqRwD/DLy9m3sasAF4DLAOeG+3PUnSEuhzpL8WmK6qPVV1O7AdWD8yZj3woa79MeDpSdL1b6+q26rqu8B0tz1J0hLoE/onATcPLc90fbOOqaoDwI+Ah/ScK0laJMt7jMksfdVzTJ+5JNkEbOoWf5Jkd4+67gtOBH6w1EX0lbcvdQX3CPea98z36xdaec9O6TOoT+jPACcPLa8A9h5izEyS5cADgf0951JVW4GtfQq+L0kyVVXjS12H+vM9u/fxPburPqd3JoE1SVYnOYbBF7MTI2MmgI1d+3nA56uquv4N3a97VgNrgKsWpnRJ0nzNeaRfVQeSnAtcBiwDtlXVziRbgKmqmgA+CFyUZJrBEf6Gbu7OJJcAu4ADwCur6o6j9FokSXPI4IBcSyHJpu7Ulu4lfM/ufXzP7srQl6SGeBsGSWqIob8IklSSdw0tvzbJm5ewpHuUo7V/kjwtyb8f6XaWWpIPzHIVvIAMfDnJs4b6XpDkP5ayrnsyQ39x3Ab8UZITl7qQe6jm98/d3Z6kqv6sqnYtZj33Ft2vBF8O/FOS45IcD/w98Mqlreyey9BfHAcYXIfw16MrkpyS5HNJruv+rlz88pbcEe2fJG9OclGSzye5IcmfD62+f5KPJfl2kn/tbg9CkqcnuSbJ9Um2JTm2678pyVuSfL1b96iu//hu3GQ3b/RWJCT57SRXJLk2yTeTPKXrPyvJV7ttXprk/kPPdV6SLwOvS3LV0LZWJbmua38xyXjXXtdt5xtJPte3tvuyqvom8Cngb4HzgQ9X1Y1JNia5qns/3pvkfkmWd/9Wru/eo1cvbfVLoKp8HOUH8BPgAcBNDC5cey3w5m7dp4CNXftPgU8udb33tv0DvBn4BvDrDK6+vBl4KPA0BrcEWcHgAOerwB8Ax3VjTu3mfxj4q659E/Cqrv0K4ANd+x+AF3ftBwHfAY4fqeNvgDd07WXAb3b1XHFwLINgOm/ouV43NP9a4GFD497Ytb8IjANjXd2ru/4H963tvv4Ajgd2A9cDxwK/A3wSWN6t3wq8CHgS8JmheQ9a6toX++GR/iKpqh8zCJfRI4vfBz7StS9iEErNWYD9829VdWtV/QD4Ar+8sd9VVTVTVXcyCNVVwCOB71bVd7oxHwLOGNrWJ7q/V3fjAc4CNie5lkEIHweM/lfHJPDS7vuIx1bV/wK/x+DutP/Vzd3IXS+Xv3iofQnwgq79wpF1dNu6ogY3L6Sq9s+jtvu0qvopg/11UVXdBpwJPBGY6vbLU4GHM7jp4yOTvCeDW73/aKlqXip9bsOghfNu4OvAv9zNmJZ/Q3sk+2e0/+DybUN9dzD4Nz/bPaGGHZxzcDzdnOdW1SHvC1VVVyQ5A3g2g4sV3wncAlxeVeccYtpPh9oXA5cm+cRgc3XDyNgw++ufs7ZG3Nk9YLBPtlXVm0YHJXkcg1vFvxp4Lr+871cTPNJfRN2R2SUM/v8DB32F7gpm4I+BLy92XfcUR7h/1ndf5D2EwWmdybt5qm8Dq5I8olv+E+BLc5R3GfCqoe8ETh8dkOQU4PtV9X4GV6k/AbgSePLB50ryG0lOne0JqupGBh80b+JXj/JhcHrqqd0tTUjy4L61NeizwAsO/jggyUOSrEwyxuD6pEsZnP9/wlIWuRQM/cX3LgbneQ96NYNTAtcxCJ+/XJKq7jkOd/9cBXyaQci+tap+5cZ+B1XVz4GXMjiqvp7B0eH75qjrrcCvAdcl+Wa3POppwLVJrmFwBPmeqtoHvAT4aPcargQedTfPczHwYgYffqN172NwVPqJJN/glx8MfWprSlVdD7wF+Gy33/8T+C0GN4C8ojvl837g75auyqXhFbm61+vOof+kqv5xqWuR7uk80pekhnikL0kN8Uhfkhpi6EtSQwx9SWqIoS9JDTH0Jakhhr4kNeT/AagtaobptHieAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot_2[\"MultipleLines\"],df_plot_2[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"tenure\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df_plot[\"tenure\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"SeniorCitizen\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"SeniorCitizen\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"Partner\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"Partner\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"Dependents\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"Dependents\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot_3[\"OnlineSecurity\"],df_plot_3[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"OnlineBackup\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"OnlineBackup\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot_4[\"DeviceProtection\"],df_plot_4[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"TechSupport\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"TechSupport\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot_5[\"StreamingTV\"],df_plot_5[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"StreamingMovies\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"StreamingMovies\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"PaperlessBilling\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"PaperlessBilling\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"PaymentMethod\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df_plot[\"PaymentMethod\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"MonthlyCharges\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df_plot[\"MonthlyCharges\"],df_plot[\"Churn\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = data.groupby(\"TotalCharges\").Churn.mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n"
     ]
    },
    {
     "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": [
    "t = {}\n",
    "df_cluster = data[['tenure']]\n",
    "for k in range(1,10):\n",
    "    kmeans = KMeans(n_clusters = k ,max_iter = 1000).fit(df_cluster)\n",
    "    df_cluster[\"clusters\"] = kmeans.labels_\n",
    "    t[k] = kmeans.inertia_\n",
    "plt.plot(list(t.keys()),list(t.values()))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans = KMeans(n_clusters = 3)\n",
    "kmeans.fit(data[['tenure']])\n",
    "data[\"TenureCluster\"]  = kmeans.predict(data[['tenure']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1       0\n",
       "2       1\n",
       "3       0\n",
       "4       1\n",
       "5       1\n",
       "6       0\n",
       "7       1\n",
       "8       0\n",
       "9       2\n",
       "10      1\n",
       "11      1\n",
       "12      2\n",
       "13      0\n",
       "14      0\n",
       "15      2\n",
       "16      2\n",
       "17      2\n",
       "18      1\n",
       "19      1\n",
       "20      1\n",
       "21      1\n",
       "22      1\n",
       "23      2\n",
       "24      0\n",
       "25      0\n",
       "26      0\n",
       "27      1\n",
       "28      2\n",
       "29      1\n",
       "       ..\n",
       "7013    0\n",
       "7014    0\n",
       "7015    0\n",
       "7016    1\n",
       "7017    2\n",
       "7018    1\n",
       "7019    0\n",
       "7020    1\n",
       "7021    1\n",
       "7022    2\n",
       "7023    2\n",
       "7024    0\n",
       "7025    1\n",
       "7026    1\n",
       "7027    1\n",
       "7028    2\n",
       "7029    1\n",
       "7030    1\n",
       "7031    2\n",
       "7032    1\n",
       "7033    0\n",
       "7034    2\n",
       "7035    1\n",
       "7036    1\n",
       "7037    2\n",
       "7038    0\n",
       "7039    2\n",
       "7040    1\n",
       "7041    1\n",
       "7042    2\n",
       "Name: TenureCluster, Length: 7043, dtype: int32"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"TenureCluster\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "def order_cluster(cluster_name,target_name,df,ascending):\n",
    "    new_cluster_name = \"new_\"+cluster_name\n",
    "    df_new = df.groupby(cluster_name)[target_name].mean().reset_index()\n",
    "    df_new = df_new.sort_values(by=target_name,ascending=ascending).reset_index(drop= True)\n",
    "    df_new[\"index\"] = df_new.index\n",
    "    df_final = pd.merge(df,df_new[[cluster_name,'index']],on=cluster_name)\n",
    "    df_final = df_final.drop([cluster_name],axis=1)\n",
    "    df_final = df_final.rename(columns={\"index\":cluster_name})\n",
    "    return df_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = order_cluster(\"TenureCluster\",\"tenure\",data,True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TenureCluster</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2941.0</td>\n",
       "      <td>7.801428</td>\n",
       "      <td>6.227163</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1929.0</td>\n",
       "      <td>34.792120</td>\n",
       "      <td>8.297679</td>\n",
       "      <td>22.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2173.0</td>\n",
       "      <td>63.475380</td>\n",
       "      <td>7.172433</td>\n",
       "      <td>50.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count       mean       std   min   25%   50%   75%   max\n",
       "TenureCluster                                                           \n",
       "0              2941.0   7.801428  6.227163   0.0   2.0   6.0  13.0  21.0\n",
       "1              1929.0  34.792120  8.297679  22.0  27.0  35.0  42.0  49.0\n",
       "2              2173.0  63.475380  7.172433  50.0  57.0  65.0  70.0  72.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(\"TenureCluster\").tenure.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0\n",
       "1       0\n",
       "2       0\n",
       "3       0\n",
       "4       0\n",
       "5       0\n",
       "6       0\n",
       "7       0\n",
       "8       0\n",
       "9       0\n",
       "10      0\n",
       "11      0\n",
       "12      0\n",
       "13      0\n",
       "14      0\n",
       "15      0\n",
       "16      0\n",
       "17      0\n",
       "18      0\n",
       "19      0\n",
       "20      0\n",
       "21      0\n",
       "22      0\n",
       "23      0\n",
       "24      0\n",
       "25      0\n",
       "26      0\n",
       "27      0\n",
       "28      0\n",
       "29      0\n",
       "       ..\n",
       "7013    2\n",
       "7014    2\n",
       "7015    2\n",
       "7016    2\n",
       "7017    2\n",
       "7018    2\n",
       "7019    2\n",
       "7020    2\n",
       "7021    2\n",
       "7022    2\n",
       "7023    2\n",
       "7024    2\n",
       "7025    2\n",
       "7026    2\n",
       "7027    2\n",
       "7028    2\n",
       "7029    2\n",
       "7030    2\n",
       "7031    2\n",
       "7032    2\n",
       "7033    2\n",
       "7034    2\n",
       "7035    2\n",
       "7036    2\n",
       "7037    2\n",
       "7038    2\n",
       "7039    2\n",
       "7040    2\n",
       "7041    2\n",
       "7042    2\n",
       "Name: TenureCluster, Length: 7043, dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"TenureCluster\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"TenureCluster\"] = data[\"TenureCluster\"].replace({0:\"Low\",1:\"Mid\",2:\"High\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans = KMeans(n_clusters = 3)\n",
    "kmeans.fit(data[['MonthlyCharges']])\n",
    "data[\"MonthlyCluster\"]  = kmeans.predict(data[['MonthlyCharges']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = order_cluster(\"MonthlyCluster\",\"MonthlyCharges\",data,True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0\n",
       "1       0\n",
       "2       0\n",
       "3       0\n",
       "4       0\n",
       "5       0\n",
       "6       0\n",
       "7       0\n",
       "8       0\n",
       "9       0\n",
       "10      0\n",
       "11      0\n",
       "12      0\n",
       "13      0\n",
       "14      0\n",
       "15      0\n",
       "16      0\n",
       "17      0\n",
       "18      0\n",
       "19      0\n",
       "20      0\n",
       "21      0\n",
       "22      0\n",
       "23      0\n",
       "24      0\n",
       "25      0\n",
       "26      0\n",
       "27      0\n",
       "28      0\n",
       "29      0\n",
       "       ..\n",
       "7013    2\n",
       "7014    2\n",
       "7015    2\n",
       "7016    2\n",
       "7017    2\n",
       "7018    2\n",
       "7019    2\n",
       "7020    2\n",
       "7021    2\n",
       "7022    2\n",
       "7023    2\n",
       "7024    2\n",
       "7025    2\n",
       "7026    2\n",
       "7027    2\n",
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       "7029    2\n",
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       "7034    2\n",
       "7035    2\n",
       "7036    2\n",
       "7037    2\n",
       "7038    2\n",
       "7039    2\n",
       "7040    2\n",
       "7041    2\n",
       "7042    2\n",
       "Name: MonthlyCluster, Length: 7043, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"MonthlyCluster\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"MonthlyCluster\"] = data[\"MonthlyCluster\"].replace({0:\"Low\",1:\"Mid\",2:\"High\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MonthlyCluster</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>High</th>\n",
       "      <td>2912.0</td>\n",
       "      <td>94.054258</td>\n",
       "      <td>10.343944</td>\n",
       "      <td>77.85</td>\n",
       "      <td>85.05</td>\n",
       "      <td>93.90</td>\n",
       "      <td>101.9125</td>\n",
       "      <td>118.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Low</th>\n",
       "      <td>1892.0</td>\n",
       "      <td>23.384619</td>\n",
       "      <td>5.660437</td>\n",
       "      <td>18.25</td>\n",
       "      <td>19.80</td>\n",
       "      <td>20.40</td>\n",
       "      <td>25.0500</td>\n",
       "      <td>42.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mid</th>\n",
       "      <td>2239.0</td>\n",
       "      <td>61.628808</td>\n",
       "      <td>10.441432</td>\n",
       "      <td>42.60</td>\n",
       "      <td>51.80</td>\n",
       "      <td>61.55</td>\n",
       "      <td>70.7000</td>\n",
       "      <td>77.80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 count       mean        std    min    25%    50%       75%  \\\n",
       "MonthlyCluster                                                                \n",
       "High            2912.0  94.054258  10.343944  77.85  85.05  93.90  101.9125   \n",
       "Low             1892.0  23.384619   5.660437  18.25  19.80  20.40   25.0500   \n",
       "Mid             2239.0  61.628808  10.441432  42.60  51.80  61.55   70.7000   \n",
       "\n",
       "                   max  \n",
       "MonthlyCluster          \n",
       "High            118.75  \n",
       "Low              42.40  \n",
       "Mid              77.80  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(\"MonthlyCluster\").MonthlyCharges.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans = KMeans(n_clusters = 3)\n",
    "kmeans.fit(data[['TotalCharges']])\n",
    "data[\"TotalCluster\"]  = kmeans.predict(data[['TotalCharges']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = order_cluster(\"TotalCluster\",\"TotalCharges\",data,True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[pd.to_numeric(data['TotalCharges'], errors='coerce').isnull(),'TotalCharges'] = np.nan\n",
    "data = data.dropna()\n",
    "data['TotalCharges'] = pd.to_numeric(data['TotalCharges'], errors='coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"TotalCluster\"] = data[\"TotalCluster\"].replace({0:\"Low\",1:\"Mid\",2:\"High\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "lab = LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "dummy =[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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>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",
       "      <th>TenureCluster</th>\n",
       "      <th>MonthlyCluster</th>\n",
       "      <th>TotalCluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</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>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>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6713-OKOMC</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>10</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>29.75</td>\n",
       "      <td>301.90</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7469-LKBCI</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>16</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>18.95</td>\n",
       "      <td>326.80</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8779-QRDMV</td>\n",
       "      <td>Male</td>\n",
       "      <td>NO</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>39.65</td>\n",
       "      <td>39.65</td>\n",
       "      <td>1</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1680-VDCWW</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>12</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>19.80</td>\n",
       "      <td>202.25</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1066-JKSGK</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.15</td>\n",
       "      <td>20.15</td>\n",
       "      <td>1</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8665-UTDHZ</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</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>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>30.20</td>\n",
       "      <td>30.20</td>\n",
       "      <td>1</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7310-EGVHZ</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>20.20</td>\n",
       "      <td>20.20</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9867-JCZSP</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>17</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.75</td>\n",
       "      <td>418.25</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0278-YXOOG</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>5</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>21.05</td>\n",
       "      <td>113.85</td>\n",
       "      <td>1</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6380-ARCEH</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.20</td>\n",
       "      <td>20.20</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3679-XASPY</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>19.45</td>\n",
       "      <td>19.45</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>6180-YBIQI</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>5</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>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>24.30</td>\n",
       "      <td>100.20</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2928-HLDBA</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>6</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.70</td>\n",
       "      <td>112.75</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>7219-TLZHO</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.85</td>\n",
       "      <td>62.90</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3930-ZGWVE</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>19.75</td>\n",
       "      <td>19.75</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>3091-FYHKI</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>35.45</td>\n",
       "      <td>35.45</td>\n",
       "      <td>1</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>6837-BJYDQ</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>19.60</td>\n",
       "      <td>61.35</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>3077-RSNTJ</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>6</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>19.70</td>\n",
       "      <td>113.50</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>7554-NEWDD</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>10</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>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>25.70</td>\n",
       "      <td>251.60</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2907-ILJBN</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>11</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.60</td>\n",
       "      <td>233.90</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1159-WFSGR</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>20.40</td>\n",
       "      <td>321.40</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>6317-YPKDH</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</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>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>29.95</td>\n",
       "      <td>29.95</td>\n",
       "      <td>1</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1024-GUALD</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</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>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>24.80</td>\n",
       "      <td>24.80</td>\n",
       "      <td>1</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>8167-GJLRN</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3</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>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>30.40</td>\n",
       "      <td>82.15</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0956-SYCWG</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>13</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>19.65</td>\n",
       "      <td>244.80</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>3645-DEYGF</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.75</td>\n",
       "      <td>20.75</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4195-NZGTA</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</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>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>25.25</td>\n",
       "      <td>25.25</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>6469-MRVET</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>20.20</td>\n",
       "      <td>20.20</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>5961-VUSRV</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>12</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>19.35</td>\n",
       "      <td>219.35</td>\n",
       "      <td>0</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7002</th>\n",
       "      <td>5297-MDOIR</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>63</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>81.15</td>\n",
       "      <td>5224.50</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7003</th>\n",
       "      <td>6369-MCAKO</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>68</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>89.05</td>\n",
       "      <td>6185.80</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7004</th>\n",
       "      <td>6341-AEVKX</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>62</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>104.30</td>\n",
       "      <td>6613.65</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7005</th>\n",
       "      <td>8065-QBYTO</td>\n",
       "      <td>Female</td>\n",
       "      <td>NO</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>71</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>99.65</td>\n",
       "      <td>7181.25</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7006</th>\n",
       "      <td>2363-BJLSL</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>62</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>80.40</td>\n",
       "      <td>4981.15</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7007</th>\n",
       "      <td>7921-LMDFQ</td>\n",
       "      <td>Male</td>\n",
       "      <td>NO</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>51</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>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>94.00</td>\n",
       "      <td>4905.75</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7008</th>\n",
       "      <td>0530-IJVDB</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>70</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>114.60</td>\n",
       "      <td>7882.50</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7009</th>\n",
       "      <td>8213-TAZPM</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>69</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>108.75</td>\n",
       "      <td>7493.05</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7010</th>\n",
       "      <td>1304-SEGFY</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>97.85</td>\n",
       "      <td>6841.30</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7011</th>\n",
       "      <td>2904-GGUAZ</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>84.05</td>\n",
       "      <td>6052.25</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7012</th>\n",
       "      <td>5136-GFPMB</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>54</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>89.40</td>\n",
       "      <td>4869.50</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7013</th>\n",
       "      <td>2371-KFUOG</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>58</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>99.15</td>\n",
       "      <td>5720.95</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7014</th>\n",
       "      <td>6257-DTAYD</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>71</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>104.15</td>\n",
       "      <td>7365.30</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7015</th>\n",
       "      <td>4616-ULAOA</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>65</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>110.80</td>\n",
       "      <td>7245.90</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7016</th>\n",
       "      <td>6797-LNAQX</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>70</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>98.30</td>\n",
       "      <td>6859.50</td>\n",
       "      <td>1</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7017</th>\n",
       "      <td>2898-MRKPI</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>68</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>101.05</td>\n",
       "      <td>6770.50</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7018</th>\n",
       "      <td>7789-CRUVC</td>\n",
       "      <td>Female</td>\n",
       "      <td>NO</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>61</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>94.20</td>\n",
       "      <td>5895.45</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7019</th>\n",
       "      <td>6664-FPDAC</td>\n",
       "      <td>Female</td>\n",
       "      <td>NO</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>56</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>111.95</td>\n",
       "      <td>6418.90</td>\n",
       "      <td>1</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7020</th>\n",
       "      <td>9972-VAFJJ</td>\n",
       "      <td>Female</td>\n",
       "      <td>NO</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>53</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>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>94.00</td>\n",
       "      <td>4871.45</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7021</th>\n",
       "      <td>0422-UXFAP</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>51</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>98.85</td>\n",
       "      <td>4947.55</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7022</th>\n",
       "      <td>6439-PKTRR</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>70</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>80.70</td>\n",
       "      <td>5617.95</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7023</th>\n",
       "      <td>0218-QNVAS</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>71</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>100.55</td>\n",
       "      <td>7113.75</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7024</th>\n",
       "      <td>7164-BPTUT</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>57</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>89.55</td>\n",
       "      <td>5012.35</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7025</th>\n",
       "      <td>9586-JGQKH</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>64</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.40</td>\n",
       "      <td>6794.75</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7026</th>\n",
       "      <td>6691-CCIHA</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>62</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>84.95</td>\n",
       "      <td>5150.55</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7027</th>\n",
       "      <td>7203-OYKCT</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>104.95</td>\n",
       "      <td>7544.30</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7028</th>\n",
       "      <td>1035-IPQPU</td>\n",
       "      <td>Female</td>\n",
       "      <td>NO</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>63</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>103.50</td>\n",
       "      <td>6479.40</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7029</th>\n",
       "      <td>0639-TSIQW</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>67</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>102.95</td>\n",
       "      <td>6886.25</td>\n",
       "      <td>1</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7030</th>\n",
       "      <td>2234-XADUH</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.90</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7031</th>\n",
       "      <td>3186-AJIEK</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>66</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.65</td>\n",
       "      <td>6844.50</td>\n",
       "      <td>0</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7032 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerID  gender SeniorCitizen Partner Dependents  tenure  \\\n",
       "0     7590-VHVEG  Female           Yes     Yes         No       1   \n",
       "1     6713-OKOMC  Female           Yes      No         No      10   \n",
       "2     7469-LKBCI    Male           Yes      No         No      16   \n",
       "3     8779-QRDMV    Male            NO      No         No       1   \n",
       "4     1680-VDCWW    Male           Yes     Yes         No      12   \n",
       "5     1066-JKSGK    Male           Yes      No         No       1   \n",
       "6     8665-UTDHZ    Male           Yes     Yes        Yes       1   \n",
       "7     7310-EGVHZ    Male           Yes      No         No       1   \n",
       "8     9867-JCZSP  Female           Yes     Yes        Yes      17   \n",
       "9     0278-YXOOG    Male           Yes      No         No       5   \n",
       "10    6380-ARCEH    Male           Yes      No         No       1   \n",
       "11    3679-XASPY  Female           Yes     Yes        Yes       1   \n",
       "12    6180-YBIQI    Male           Yes      No         No       5   \n",
       "13    2928-HLDBA  Female           Yes      No         No       6   \n",
       "14    7219-TLZHO  Female           Yes     Yes        Yes       4   \n",
       "15    3930-ZGWVE    Male           Yes      No         No       1   \n",
       "16    3091-FYHKI    Male           Yes      No         No       1   \n",
       "17    6837-BJYDQ    Male           Yes      No         No       3   \n",
       "18    3077-RSNTJ  Female           Yes     Yes        Yes       6   \n",
       "19    7554-NEWDD    Male           Yes      No         No      10   \n",
       "20    2907-ILJBN  Female           Yes     Yes        Yes      11   \n",
       "21    1159-WFSGR  Female           Yes     Yes        Yes      16   \n",
       "22    6317-YPKDH  Female           Yes      No         No       1   \n",
       "23    1024-GUALD  Female           Yes     Yes         No       1   \n",
       "24    8167-GJLRN    Male           Yes      No         No       3   \n",
       "25    0956-SYCWG  Female           Yes      No         No      13   \n",
       "26    3645-DEYGF    Male           Yes      No        Yes       1   \n",
       "27    4195-NZGTA  Female           Yes      No         No       1   \n",
       "28    6469-MRVET    Male           Yes     Yes        Yes       1   \n",
       "29    5961-VUSRV  Female           Yes      No         No      12   \n",
       "...          ...     ...           ...     ...        ...     ...   \n",
       "7002  5297-MDOIR  Female           Yes     Yes         No      63   \n",
       "7003  6369-MCAKO  Female           Yes     Yes        Yes      68   \n",
       "7004  6341-AEVKX  Female           Yes     Yes         No      62   \n",
       "7005  8065-QBYTO  Female            NO      No         No      71   \n",
       "7006  2363-BJLSL    Male           Yes      No         No      62   \n",
       "7007  7921-LMDFQ    Male            NO      No         No      51   \n",
       "7008  0530-IJVDB    Male           Yes      No        Yes      70   \n",
       "7009  8213-TAZPM  Female           Yes     Yes        Yes      69   \n",
       "7010  1304-SEGFY  Female           Yes     Yes         No      72   \n",
       "7011  2904-GGUAZ  Female           Yes     Yes         No      72   \n",
       "7012  5136-GFPMB    Male           Yes      No         No      54   \n",
       "7013  2371-KFUOG    Male           Yes      No         No      58   \n",
       "7014  6257-DTAYD    Male           Yes     Yes         No      71   \n",
       "7015  4616-ULAOA  Female           Yes     Yes        Yes      65   \n",
       "7016  6797-LNAQX    Male           Yes     Yes        Yes      70   \n",
       "7017  2898-MRKPI    Male           Yes     Yes        Yes      68   \n",
       "7018  7789-CRUVC  Female            NO     Yes         No      61   \n",
       "7019  6664-FPDAC  Female            NO      No         No      56   \n",
       "7020  9972-VAFJJ  Female            NO     Yes         No      53   \n",
       "7021  0422-UXFAP  Female           Yes     Yes         No      51   \n",
       "7022  6439-PKTRR  Female           Yes     Yes        Yes      70   \n",
       "7023  0218-QNVAS    Male           Yes     Yes        Yes      71   \n",
       "7024  7164-BPTUT    Male           Yes      No        Yes      57   \n",
       "7025  9586-JGQKH  Female           Yes     Yes         No      64   \n",
       "7026  6691-CCIHA  Female           Yes     Yes         No      62   \n",
       "7027  7203-OYKCT    Male           Yes      No         No      72   \n",
       "7028  1035-IPQPU  Female            NO     Yes         No      63   \n",
       "7029  0639-TSIQW  Female           Yes      No         No      67   \n",
       "7030  2234-XADUH  Female           Yes     Yes        Yes      72   \n",
       "7031  3186-AJIEK    Male           Yes      No         No      66   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService       OnlineSecurity  ...  \\\n",
       "0              No  No phone service             DSL                   No  ...   \n",
       "1              No  No phone service             DSL                  Yes  ...   \n",
       "2             Yes                No              No  No internet service  ...   \n",
       "3              No  No phone service             DSL                   No  ...   \n",
       "4             Yes                No              No  No internet service  ...   \n",
       "5             Yes                No              No  No internet service  ...   \n",
       "6              No  No phone service             DSL                   No  ...   \n",
       "7             Yes                No              No  No internet service  ...   \n",
       "8             Yes                No              No  No internet service  ...   \n",
       "9             Yes                No              No  No internet service  ...   \n",
       "10            Yes                No              No  No internet service  ...   \n",
       "11            Yes                No              No  No internet service  ...   \n",
       "12             No  No phone service             DSL                   No  ...   \n",
       "13            Yes                No              No  No internet service  ...   \n",
       "14            Yes                No              No  No internet service  ...   \n",
       "15            Yes                No              No  No internet service  ...   \n",
       "16             No  No phone service             DSL                   No  ...   \n",
       "17            Yes                No              No  No internet service  ...   \n",
       "18            Yes                No              No  No internet service  ...   \n",
       "19            Yes               Yes              No  No internet service  ...   \n",
       "20            Yes                No              No  No internet service  ...   \n",
       "21            Yes                No              No  No internet service  ...   \n",
       "22             No  No phone service             DSL                   No  ...   \n",
       "23             No  No phone service             DSL                   No  ...   \n",
       "24             No  No phone service             DSL                   No  ...   \n",
       "25            Yes                No              No  No internet service  ...   \n",
       "26            Yes                No              No  No internet service  ...   \n",
       "27             No  No phone service             DSL                   No  ...   \n",
       "28            Yes                No              No  No internet service  ...   \n",
       "29            Yes                No              No  No internet service  ...   \n",
       "...           ...               ...             ...                  ...  ...   \n",
       "7002          Yes                No     Fiber optic                  Yes  ...   \n",
       "7003          Yes               Yes             DSL                  Yes  ...   \n",
       "7004          Yes                No     Fiber optic                  Yes  ...   \n",
       "7005          Yes               Yes     Fiber optic                  Yes  ...   \n",
       "7006          Yes                No             DSL                   No  ...   \n",
       "7007          Yes                No     Fiber optic                   No  ...   \n",
       "7008          Yes               Yes     Fiber optic                  Yes  ...   \n",
       "7009          Yes               Yes     Fiber optic                   No  ...   \n",
       "7010          Yes               Yes     Fiber optic                   No  ...   \n",
       "7011          Yes               Yes     Fiber optic                  Yes  ...   \n",
       "7012          Yes               Yes     Fiber optic                   No  ...   \n",
       "7013          Yes                No     Fiber optic                  Yes  ...   \n",
       "7014          Yes               Yes     Fiber optic                   No  ...   \n",
       "7015          Yes               Yes     Fiber optic                   No  ...   \n",
       "7016          Yes               Yes     Fiber optic                   No  ...   \n",
       "7017          Yes               Yes     Fiber optic                   No  ...   \n",
       "7018          Yes               Yes     Fiber optic                  Yes  ...   \n",
       "7019          Yes               Yes     Fiber optic                   No  ...   \n",
       "7020          Yes                No     Fiber optic                   No  ...   \n",
       "7021          Yes               Yes     Fiber optic                   No  ...   \n",
       "7022          Yes               Yes             DSL                  Yes  ...   \n",
       "7023          Yes               Yes     Fiber optic                   No  ...   \n",
       "7024          Yes               Yes             DSL                  Yes  ...   \n",
       "7025          Yes               Yes     Fiber optic                   No  ...   \n",
       "7026          Yes               Yes             DSL                  Yes  ...   \n",
       "7027          Yes               Yes     Fiber optic                   No  ...   \n",
       "7028          Yes               Yes     Fiber optic                   No  ...   \n",
       "7029          Yes               Yes     Fiber optic                  Yes  ...   \n",
       "7030          Yes               Yes     Fiber optic                   No  ...   \n",
       "7031          Yes                No     Fiber optic                  Yes  ...   \n",
       "\n",
       "          StreamingMovies        Contract PaperlessBilling  \\\n",
       "0                      No  Month-to-month              Yes   \n",
       "1                      No  Month-to-month               No   \n",
       "2     No internet service        Two year               No   \n",
       "3                     Yes  Month-to-month              Yes   \n",
       "4     No internet service        One year               No   \n",
       "5     No internet service  Month-to-month               No   \n",
       "6                      No  Month-to-month               No   \n",
       "7     No internet service  Month-to-month               No   \n",
       "8     No internet service        One year               No   \n",
       "9     No internet service  Month-to-month               No   \n",
       "10    No internet service  Month-to-month               No   \n",
       "11    No internet service  Month-to-month               No   \n",
       "12                     No  Month-to-month               No   \n",
       "13    No internet service  Month-to-month               No   \n",
       "14    No internet service  Month-to-month               No   \n",
       "15    No internet service  Month-to-month               No   \n",
       "16                    Yes  Month-to-month              Yes   \n",
       "17    No internet service        One year               No   \n",
       "18    No internet service  Month-to-month               No   \n",
       "19    No internet service        Two year               No   \n",
       "20    No internet service        One year               No   \n",
       "21    No internet service  Month-to-month               No   \n",
       "22                     No  Month-to-month               No   \n",
       "23                     No  Month-to-month              Yes   \n",
       "24                     No  Month-to-month               No   \n",
       "25    No internet service        One year               No   \n",
       "26    No internet service  Month-to-month               No   \n",
       "27                     No  Month-to-month               No   \n",
       "28    No internet service        One year              Yes   \n",
       "29    No internet service        One year              Yes   \n",
       "...                   ...             ...              ...   \n",
       "7002                   No        One year              Yes   \n",
       "7003                  Yes        Two year              Yes   \n",
       "7004                  Yes        One year              Yes   \n",
       "7005                   No        One year              Yes   \n",
       "7006                  Yes  Month-to-month              Yes   \n",
       "7007                  Yes        One year              Yes   \n",
       "7008                  Yes        Two year              Yes   \n",
       "7009                  Yes        One year              Yes   \n",
       "7010                  Yes        Two year              Yes   \n",
       "7011                   No        Two year              Yes   \n",
       "7012                  Yes  Month-to-month               No   \n",
       "7013                  Yes        One year               No   \n",
       "7014                  Yes        Two year              Yes   \n",
       "7015                  Yes        Two year              Yes   \n",
       "7016                  Yes        Two year               No   \n",
       "7017                  Yes        One year              Yes   \n",
       "7018                   No  Month-to-month              Yes   \n",
       "7019                  Yes        One year              Yes   \n",
       "7020                   No        One year              Yes   \n",
       "7021                  Yes        One year              Yes   \n",
       "7022                   No        Two year               No   \n",
       "7023                  Yes        One year               No   \n",
       "7024                  Yes        Two year               No   \n",
       "7025                  Yes        Two year              Yes   \n",
       "7026                  Yes        Two year              Yes   \n",
       "7027                  Yes        One year              Yes   \n",
       "7028                  Yes  Month-to-month              Yes   \n",
       "7029                   No  Month-to-month              Yes   \n",
       "7030                  Yes        One year              Yes   \n",
       "7031                  Yes        Two year              Yes   \n",
       "\n",
       "                  PaymentMethod MonthlyCharges TotalCharges Churn  \\\n",
       "0              Electronic check          29.85        29.85     0   \n",
       "1                  Mailed check          29.75       301.90     0   \n",
       "2       Credit card (automatic)          18.95       326.80     0   \n",
       "3              Electronic check          39.65        39.65     1   \n",
       "4     Bank transfer (automatic)          19.80       202.25     0   \n",
       "5                  Mailed check          20.15        20.15     1   \n",
       "6              Electronic check          30.20        30.20     1   \n",
       "7     Bank transfer (automatic)          20.20        20.20     0   \n",
       "8                  Mailed check          20.75       418.25     0   \n",
       "9                  Mailed check          21.05       113.85     1   \n",
       "10                 Mailed check          20.20        20.20     0   \n",
       "11             Electronic check          19.45        19.45     0   \n",
       "12                 Mailed check          24.30       100.20     0   \n",
       "13                 Mailed check          20.70       112.75     0   \n",
       "14                 Mailed check          20.85        62.90     0   \n",
       "15                 Mailed check          19.75        19.75     0   \n",
       "16             Electronic check          35.45        35.45     1   \n",
       "17                 Mailed check          19.60        61.35     0   \n",
       "18                 Mailed check          19.70       113.50     0   \n",
       "19    Bank transfer (automatic)          25.70       251.60     0   \n",
       "20                 Mailed check          20.60       233.90     0   \n",
       "21             Electronic check          20.40       321.40     0   \n",
       "22    Bank transfer (automatic)          29.95        29.95     1   \n",
       "23             Electronic check          24.80        24.80     1   \n",
       "24             Electronic check          30.40        82.15     0   \n",
       "25             Electronic check          19.65       244.80     0   \n",
       "26                 Mailed check          20.75        20.75     0   \n",
       "27             Electronic check          25.25        25.25     0   \n",
       "28             Electronic check          20.20        20.20     0   \n",
       "29    Bank transfer (automatic)          19.35       219.35     0   \n",
       "...                         ...            ...          ...   ...   \n",
       "7002    Credit card (automatic)          81.15      5224.50     0   \n",
       "7003  Bank transfer (automatic)          89.05      6185.80     0   \n",
       "7004           Electronic check         104.30      6613.65     0   \n",
       "7005    Credit card (automatic)          99.65      7181.25     0   \n",
       "7006  Bank transfer (automatic)          80.40      4981.15     0   \n",
       "7007  Bank transfer (automatic)          94.00      4905.75     0   \n",
       "7008           Electronic check         114.60      7882.50     0   \n",
       "7009  Bank transfer (automatic)         108.75      7493.05     0   \n",
       "7010           Electronic check          97.85      6841.30     0   \n",
       "7011  Bank transfer (automatic)          84.05      6052.25     0   \n",
       "7012    Credit card (automatic)          89.40      4869.50     0   \n",
       "7013  Bank transfer (automatic)          99.15      5720.95     0   \n",
       "7014    Credit card (automatic)         104.15      7365.30     0   \n",
       "7015    Credit card (automatic)         110.80      7245.90     0   \n",
       "7016  Bank transfer (automatic)          98.30      6859.50     1   \n",
       "7017    Credit card (automatic)         101.05      6770.50     0   \n",
       "7018    Credit card (automatic)          94.20      5895.45     0   \n",
       "7019           Electronic check         111.95      6418.90     1   \n",
       "7020           Electronic check          94.00      4871.45     0   \n",
       "7021           Electronic check          98.85      4947.55     0   \n",
       "7022           Electronic check          80.70      5617.95     0   \n",
       "7023  Bank transfer (automatic)         100.55      7113.75     0   \n",
       "7024               Mailed check          89.55      5012.35     0   \n",
       "7025  Bank transfer (automatic)         105.40      6794.75     0   \n",
       "7026           Electronic check          84.95      5150.55     0   \n",
       "7027           Electronic check         104.95      7544.30     0   \n",
       "7028           Electronic check         103.50      6479.40     0   \n",
       "7029    Credit card (automatic)         102.95      6886.25     1   \n",
       "7030    Credit card (automatic)         103.20      7362.90     0   \n",
       "7031  Bank transfer (automatic)         105.65      6844.50     0   \n",
       "\n",
       "     TenureCluster  MonthlyCluster  TotalCluster  \n",
       "0              Low             Low           Low  \n",
       "1              Low             Low           Low  \n",
       "2              Low             Low           Low  \n",
       "3              Low             Low           Low  \n",
       "4              Low             Low           Low  \n",
       "5              Low             Low           Low  \n",
       "6              Low             Low           Low  \n",
       "7              Low             Low           Low  \n",
       "8              Low             Low           Low  \n",
       "9              Low             Low           Low  \n",
       "10             Low             Low           Low  \n",
       "11             Low             Low           Low  \n",
       "12             Low             Low           Low  \n",
       "13             Low             Low           Low  \n",
       "14             Low             Low           Low  \n",
       "15             Low             Low           Low  \n",
       "16             Low             Low           Low  \n",
       "17             Low             Low           Low  \n",
       "18             Low             Low           Low  \n",
       "19             Low             Low           Low  \n",
       "20             Low             Low           Low  \n",
       "21             Low             Low           Low  \n",
       "22             Low             Low           Low  \n",
       "23             Low             Low           Low  \n",
       "24             Low             Low           Low  \n",
       "25             Low             Low           Low  \n",
       "26             Low             Low           Low  \n",
       "27             Low             Low           Low  \n",
       "28             Low             Low           Low  \n",
       "29             Low             Low           Low  \n",
       "...            ...             ...           ...  \n",
       "7002          High            High          High  \n",
       "7003          High            High          High  \n",
       "7004          High            High          High  \n",
       "7005          High            High          High  \n",
       "7006          High            High          High  \n",
       "7007          High            High          High  \n",
       "7008          High            High          High  \n",
       "7009          High            High          High  \n",
       "7010          High            High          High  \n",
       "7011          High            High          High  \n",
       "7012          High            High          High  \n",
       "7013          High            High          High  \n",
       "7014          High            High          High  \n",
       "7015          High            High          High  \n",
       "7016          High            High          High  \n",
       "7017          High            High          High  \n",
       "7018          High            High          High  \n",
       "7019          High            High          High  \n",
       "7020          High            High          High  \n",
       "7021          High            High          High  \n",
       "7022          High            High          High  \n",
       "7023          High            High          High  \n",
       "7024          High            High          High  \n",
       "7025          High            High          High  \n",
       "7026          High            High          High  \n",
       "7027          High            High          High  \n",
       "7028          High            High          High  \n",
       "7029          High            High          High  \n",
       "7030          High            High          High  \n",
       "7031          High            High          High  \n",
       "\n",
       "[7032 rows x 24 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "for column in data.columns:\n",
    "    if data[column].dtype == object and column!= 'customerID':\n",
    "        if data[column].nunique == 2:\n",
    "            data[column] = lab.fit_transform(data[column])\n",
    "        else:\n",
    "            dummy.append(column)\n",
    "data = pd.get_dummies(data=data,columns = dummy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TenureCluster_High</th>\n",
       "      <th>TenureCluster_Low</th>\n",
       "      <th>TenureCluster_Mid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   TenureCluster_High  TenureCluster_Low  TenureCluster_Mid\n",
       "0                   0                  1                  0\n",
       "1                   0                  1                  0\n",
       "2                   0                  1                  0\n",
       "3                   0                  1                  0\n",
       "4                   0                  1                  0"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['TenureCluster_High','TenureCluster_Low','TenureCluster_Mid']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "import statsmodels.api as sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "import statsmodels.formula.api as smf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>tenure</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "      <th>gender_Female</th>\n",
       "      <th>gender_Male</th>\n",
       "      <th>SeniorCitizen_NO</th>\n",
       "      <th>SeniorCitizen_Yes</th>\n",
       "      <th>Partner_No</th>\n",
       "      <th>...</th>\n",
       "      <th>PaymentMethod_Mailed check</th>\n",
       "      <th>TenureCluster_High</th>\n",
       "      <th>TenureCluster_Low</th>\n",
       "      <th>TenureCluster_Mid</th>\n",
       "      <th>MonthlyCluster_High</th>\n",
       "      <th>MonthlyCluster_Low</th>\n",
       "      <th>MonthlyCluster_Mid</th>\n",
       "      <th>TotalCluster_High</th>\n",
       "      <th>TotalCluster_Low</th>\n",
       "      <th>TotalCluster_Mid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>1</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6713-OKOMC</td>\n",
       "      <td>10</td>\n",
       "      <td>29.75</td>\n",
       "      <td>301.90</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7469-LKBCI</td>\n",
       "      <td>16</td>\n",
       "      <td>18.95</td>\n",
       "      <td>326.80</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <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",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8779-QRDMV</td>\n",
       "      <td>1</td>\n",
       "      <td>39.65</td>\n",
       "      <td>39.65</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1680-VDCWW</td>\n",
       "      <td>12</td>\n",
       "      <td>19.80</td>\n",
       "      <td>202.25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <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 × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  tenure  MonthlyCharges  TotalCharges  Churn  gender_Female  \\\n",
       "0  7590-VHVEG       1           29.85         29.85      0              1   \n",
       "1  6713-OKOMC      10           29.75        301.90      0              1   \n",
       "2  7469-LKBCI      16           18.95        326.80      0              0   \n",
       "3  8779-QRDMV       1           39.65         39.65      1              0   \n",
       "4  1680-VDCWW      12           19.80        202.25      0              0   \n",
       "\n",
       "   gender_Male  SeniorCitizen_NO  SeniorCitizen_Yes  Partner_No  ...  \\\n",
       "0            0                 0                  1           0  ...   \n",
       "1            0                 0                  1           1  ...   \n",
       "2            1                 0                  1           1  ...   \n",
       "3            1                 1                  0           1  ...   \n",
       "4            1                 0                  1           0  ...   \n",
       "\n",
       "   PaymentMethod_Mailed check  TenureCluster_High  TenureCluster_Low  \\\n",
       "0                           0                   0                  1   \n",
       "1                           1                   0                  1   \n",
       "2                           0                   0                  1   \n",
       "3                           0                   0                  1   \n",
       "4                           0                   0                  1   \n",
       "\n",
       "   TenureCluster_Mid  MonthlyCluster_High  MonthlyCluster_Low  \\\n",
       "0                  0                    0                   1   \n",
       "1                  0                    0                   1   \n",
       "2                  0                    0                   1   \n",
       "3                  0                    0                   1   \n",
       "4                  0                    0                   1   \n",
       "\n",
       "   MonthlyCluster_Mid  TotalCluster_High  TotalCluster_Low  TotalCluster_Mid  \n",
       "0                   0                  0                 1                 0  \n",
       "1                   0                  0                 1                 0  \n",
       "2                   0                  0                 1                 0  \n",
       "3                   0                  0                 1                 0  \n",
       "4                   0                  0                 1                 0  \n",
       "\n",
       "[5 rows x 57 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "gm_columns = 'gender_Female'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "for column in data.columns:\n",
    "    if column not in ['Churn','customerID','gender_Female']:\n",
    "        gm_columns = gm_columns+ ' + ' + column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "all_columns = []\n",
    "for column in data.columns:\n",
    "    column = column.replace(\" \", \"_\").replace(\"(\", \"_\").replace(\")\", \"_\").replace(\"-\", \"_\")\n",
    "    all_columns.append(column)\n",
    "\n",
    "data.columns = all_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0\n",
       "1       0\n",
       "2       0\n",
       "3       0\n",
       "4       1\n",
       "5       0\n",
       "6       0\n",
       "7       0\n",
       "8       1\n",
       "9       0\n",
       "10      0\n",
       "11      0\n",
       "12      0\n",
       "13      0\n",
       "14      0\n",
       "15      0\n",
       "16      0\n",
       "17      1\n",
       "18      0\n",
       "19      0\n",
       "20      1\n",
       "21      0\n",
       "22      0\n",
       "23      0\n",
       "24      0\n",
       "25      1\n",
       "26      0\n",
       "27      0\n",
       "28      1\n",
       "29      1\n",
       "       ..\n",
       "7002    1\n",
       "7003    0\n",
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       "7005    1\n",
       "7006    0\n",
       "7007    1\n",
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       "7010    0\n",
       "7011    0\n",
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       "7017    1\n",
       "7018    0\n",
       "7019    1\n",
       "7020    1\n",
       "7021    1\n",
       "7022    0\n",
       "7023    1\n",
       "7024    0\n",
       "7025    0\n",
       "7026    0\n",
       "7027    1\n",
       "7028    0\n",
       "7029    0\n",
       "7030    1\n",
       "7031    0\n",
       "Name: Contract_One year, Length: 7032, dtype: uint8"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"Contract_One year\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'gender_Female + tenure + MonthlyCharges + TotalCharges + gender_Male + SeniorCitizen_NO + SeniorCitizen_Yes + Partner_No + Partner_Yes + Dependents_No + Dependents_Yes + PhoneService_No + PhoneService_Yes + MultipleLines_No + MultipleLines_No_phone_service + MultipleLines_Yes + InternetService_DSL + InternetService_Fiber_optic + InternetService_No + OnlineSecurity_No + OnlineSecurity_No_internet_service + OnlineSecurity_Yes + OnlineBackup_No + OnlineBackup_No_internet_service + OnlineBackup_Yes + DeviceProtection_No + DeviceProtection_No_internet_service + DeviceProtection_Yes + TechSupport_No + TechSupport_No_internet_service + TechSupport_Yes + StreamingTV_No + StreamingTV_No_internet_service + StreamingTV_Yes + StreamingMovies_No + StreamingMovies_No_internet_service + StreamingMovies_Yes + Contract_Month_to_month + Contract_One_year + Contract_Two_year + PaperlessBilling_No + PaperlessBilling_Yes + PaymentMethod_Bank_transfer__automatic_ + PaymentMethod_Credit_card__automatic_ + PaymentMethod_Electronic_check + PaymentMethod_Mailed_check + TenureCluster_High + TenureCluster_Low + TenureCluster_Mid + MonthlyCluster_High + MonthlyCluster_Low + MonthlyCluster_Mid + TotalCluster_High + TotalCluster_Low + TotalCluster_Mid'"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gm_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = smf.glm(formula='Churn ~ {}'.format(gm_columns),data=data, family=sm.families.Binomial())\n",
    "res = model.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 Generalized Linear Model Regression Results                  \n",
      "==============================================================================\n",
      "Dep. Variable:                  Churn   No. Observations:                 7032\n",
      "Model:                            GLM   Df Residuals:                     7002\n",
      "Model Family:                Binomial   Df Model:                           29\n",
      "Link Function:                  logit   Scale:                          1.0000\n",
      "Method:                          IRLS   Log-Likelihood:                -2902.6\n",
      "Date:                Tue, 25 Feb 2020   Deviance:                       5805.1\n",
      "Time:                        20:33:25   Pearson chi2:                 7.60e+03\n",
      "No. Iterations:                   100   Covariance Type:             nonrobust\n",
      "===========================================================================================================\n",
      "                                              coef    std err          z      P>|z|      [0.025      0.975]\n",
      "-----------------------------------------------------------------------------------------------------------\n",
      "Intercept                                   0.2026      0.199      1.020      0.308      -0.187       0.592\n",
      "gender_Female                               0.1130      0.104      1.088      0.276      -0.091       0.317\n",
      "tenure                                     -0.0623      0.008     -7.479      0.000      -0.079      -0.046\n",
      "MonthlyCharges                             -0.0349      0.032     -1.095      0.274      -0.097       0.028\n",
      "TotalCharges                                0.0001   9.96e-05      1.226      0.220   -7.31e-05       0.000\n",
      "gender_Male                                 0.0895      0.105      0.853      0.394      -0.116       0.295\n",
      "SeniorCitizen_NO                            0.2117      0.109      1.934      0.053      -0.003       0.426\n",
      "SeniorCitizen_Yes                          -0.0091      0.106     -0.085      0.932      -0.218       0.199\n",
      "Partner_No                                  0.1009      0.107      0.942      0.346      -0.109       0.311\n",
      "Partner_Yes                                 0.1016      0.106      0.958      0.338      -0.106       0.310\n",
      "Dependents_No                               0.1669      0.108      1.541      0.123      -0.045       0.379\n",
      "Dependents_Yes                              0.0357      0.110      0.325      0.745      -0.179       0.251\n",
      "PhoneService_No                            -0.0082      0.138     -0.060      0.952      -0.278       0.262\n",
      "PhoneService_Yes                            0.2108      0.322      0.655      0.512      -0.420       0.841\n",
      "MultipleLines_No                           -0.1252      0.092     -1.361      0.173      -0.305       0.055\n",
      "MultipleLines_No_phone_service             -0.0082      0.138     -0.060      0.952      -0.278       0.262\n",
      "MultipleLines_Yes                           0.3360      0.243      1.381      0.167      -0.141       0.813\n",
      "InternetService_DSL                        -0.6244      0.250     -2.493      0.013      -1.115      -0.134\n",
      "InternetService_Fiber_optic                 1.0429      0.552      1.889      0.059      -0.039       2.125\n",
      "InternetService_No                         -0.2158      0.113     -1.904      0.057      -0.438       0.006\n",
      "OnlineSecurity_No                           0.3113      0.085      3.660      0.000       0.145       0.478\n",
      "OnlineSecurity_No_internet_service         -0.2158      0.113     -1.904      0.057      -0.438       0.006\n",
      "OnlineSecurity_Yes                          0.1071      0.236      0.454      0.650      -0.355       0.570\n",
      "OnlineBackup_No                             0.2047      0.083      2.454      0.014       0.041       0.368\n",
      "OnlineBackup_No_internet_service           -0.2158      0.113     -1.904      0.057      -0.438       0.006\n",
      "OnlineBackup_Yes                            0.2137      0.235      0.908      0.364      -0.248       0.675\n",
      "DeviceProtection_No                         0.1334      0.084      1.589      0.112      -0.031       0.298\n",
      "DeviceProtection_No_internet_service       -0.2158      0.113     -1.904      0.057      -0.438       0.006\n",
      "DeviceProtection_Yes                        0.2850      0.236      1.210      0.226      -0.177       0.747\n",
      "TechSupport_No                              0.2988      0.085      3.516      0.000       0.132       0.465\n",
      "TechSupport_No_internet_service            -0.2158      0.113     -1.904      0.057      -0.438       0.006\n",
      "TechSupport_Yes                             0.1196      0.237      0.505      0.613      -0.344       0.584\n",
      "StreamingTV_No                             -0.0768      0.043     -1.796      0.072      -0.161       0.007\n",
      "StreamingTV_No_internet_service            -0.2158      0.113     -1.904      0.057      -0.438       0.006\n",
      "StreamingTV_Yes                             0.4952      0.314      1.575      0.115      -0.121       1.111\n",
      "StreamingMovies_No                         -0.0764      0.043     -1.776      0.076      -0.161       0.008\n",
      "StreamingMovies_No_internet_service        -0.2158      0.113     -1.904      0.057      -0.438       0.006\n",
      "StreamingMovies_Yes                         0.4948      0.314      1.573      0.116      -0.122       1.111\n",
      "Contract_Month_to_month                     0.7531      0.100      7.517      0.000       0.557       0.950\n",
      "Contract_One_year                           0.0738      0.102      0.721      0.471      -0.127       0.275\n",
      "Contract_Two_year                          -0.6244      0.133     -4.692      0.000      -0.885      -0.364\n",
      "PaperlessBilling_No                        -0.0714      0.107     -0.669      0.503      -0.281       0.138\n",
      "PaperlessBilling_Yes                        0.2740      0.105      2.599      0.009       0.067       0.481\n",
      "PaymentMethod_Bank_transfer__automatic_     0.0201      0.084      0.238      0.812      -0.145       0.185\n",
      "PaymentMethod_Credit_card__automatic_      -0.0671      0.086     -0.782      0.434      -0.235       0.101\n",
      "PaymentMethod_Electronic_check              0.3081      0.072      4.283      0.000       0.167       0.449\n",
      "PaymentMethod_Mailed_check                 -0.0586      0.085     -0.691      0.489      -0.225       0.108\n",
      "TenureCluster_High                          0.4566      0.176      2.602      0.009       0.113       0.801\n",
      "TenureCluster_Low                          -0.1298      0.160     -0.810      0.418      -0.444       0.184\n",
      "TenureCluster_Mid                          -0.1242      0.100     -1.244      0.213      -0.320       0.071\n",
      "MonthlyCluster_High                         0.0495      0.153      0.322      0.747      -0.251       0.350\n",
      "MonthlyCluster_Low                          0.0873      0.188      0.465      0.642      -0.281       0.455\n",
      "MonthlyCluster_Mid                          0.0658      0.108      0.610      0.542      -0.145       0.277\n",
      "TotalCluster_High                           0.3937      0.194      2.026      0.043       0.013       0.774\n",
      "TotalCluster_Low                           -0.3140      0.165     -1.898      0.058      -0.638       0.010\n",
      "TotalCluster_Mid                            0.1229      0.104      1.177      0.239      -0.082       0.328\n",
      "===========================================================================================================\n"
     ]
    }
   ],
   "source": [
    "print(res.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Intercept                                  1.224552\n",
       "gender_Female                              1.119670\n",
       "tenure                                     0.939613\n",
       "MonthlyCharges                             0.965739\n",
       "TotalCharges                               1.000122\n",
       "gender_Male                                1.093672\n",
       "SeniorCitizen_NO                           1.235738\n",
       "SeniorCitizen_Yes                          0.990948\n",
       "Partner_No                                 1.106210\n",
       "Partner_Yes                                1.106980\n",
       "Dependents_No                              1.181601\n",
       "Dependents_Yes                             1.036350\n",
       "PhoneService_No                            0.991825\n",
       "PhoneService_Yes                           1.234646\n",
       "MultipleLines_No                           0.882343\n",
       "MultipleLines_No_phone_service             0.991825\n",
       "MultipleLines_Yes                          1.399281\n",
       "InternetService_DSL                        0.535557\n",
       "InternetService_Fiber_optic                2.837318\n",
       "InternetService_No                         0.805868\n",
       "OnlineSecurity_No                          1.365185\n",
       "OnlineSecurity_No_internet_service         0.805868\n",
       "OnlineSecurity_Yes                         1.113069\n",
       "OnlineBackup_No                            1.227211\n",
       "OnlineBackup_No_internet_service           0.805868\n",
       "OnlineBackup_Yes                           1.238210\n",
       "DeviceProtection_No                        1.142701\n",
       "DeviceProtection_No_internet_service       0.805868\n",
       "DeviceProtection_Yes                       1.329784\n",
       "TechSupport_No                             1.348281\n",
       "TechSupport_No_internet_service            0.805868\n",
       "TechSupport_Yes                            1.127023\n",
       "StreamingTV_No                             0.926069\n",
       "StreamingTV_No_internet_service            0.805868\n",
       "StreamingTV_Yes                            1.640854\n",
       "StreamingMovies_No                         0.926423\n",
       "StreamingMovies_No_internet_service        0.805868\n",
       "StreamingMovies_Yes                        1.640227\n",
       "Contract_Month_to_month                    2.123677\n",
       "Contract_One_year                          1.076641\n",
       "Contract_Two_year                          0.535572\n",
       "PaperlessBilling_No                        0.931084\n",
       "PaperlessBilling_Yes                       1.315189\n",
       "PaymentMethod_Bank_transfer__automatic_    1.020322\n",
       "PaymentMethod_Credit_card__automatic_      0.935139\n",
       "PaymentMethod_Electronic_check             1.360872\n",
       "PaymentMethod_Mailed_check                 0.943076\n",
       "TenureCluster_High                         1.578758\n",
       "TenureCluster_Low                          0.878232\n",
       "TenureCluster_Mid                          0.883187\n",
       "MonthlyCluster_High                        1.050697\n",
       "MonthlyCluster_Low                         1.091263\n",
       "MonthlyCluster_Mid                         1.067998\n",
       "TotalCluster_High                          1.482407\n",
       "TotalCluster_Low                           0.730501\n",
       "TotalCluster_Mid                           1.130809\n",
       "dtype: float64"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.exp(res.params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[243  23]\n",
      " [ 46  40]]\n",
      "45750\n",
      "158400\n",
      "112650\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import KFold, cross_val_score, train_test_split\n",
    "\n",
    "X = data.drop(['Churn','customerID'],axis=1)\n",
    "y = data[\"Churn\"]\n",
    "\n",
    "X_train, X_test, y_train, y_test =train_test_split(X, y, test_size=0.05, random_state=56)\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "best_lr1 = LogisticRegression(C=0.8)\n",
    "\n",
    "\n",
    "best_lr1.fit(X_train,y_train)\n",
    "\n",
    "best_lr1.score(X_test,y_test)\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "y_pred_log = best_lr1.predict(X_test)\n",
    "confusion_matrix_log = confusion_matrix(y_test, y_pred_log)\n",
    "print(confusion_matrix_log)\n",
    "\n",
    "ourmodel = (45*450) + (236+19)*100\n",
    "\n",
    "print(ourmodel)\n",
    "\n",
    "nomodel = (236+19+45+52)*450\n",
    "\n",
    "print(nomodel)\n",
    "\n",
    "saved = nomodel - ourmodel\n",
    "\n",
    "print(saved)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.7698863636363636"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "data_1 = pd.read_csv(\"Churn_1.csv\")\n",
    "\n",
    "data_1[\"Churn Reason\"].fillna(\"No Reason\",inplace=True)\n",
    "\n",
    "data_1[\"Churn Reason\"].shape\n",
    "\n",
    "best_lr2 = LogisticRegression(C=0.8)\n",
    "\n",
    "data_1.shape\n",
    "\n",
    "data_1.loc[pd.to_numeric(data_1['Total Charges'], errors='coerce').isnull(),'Total Charges'] = np.nan\n",
    "data_1 = data_1.dropna()\n",
    "data_1['Total Charges'] = pd.to_numeric(data_1['Total Charges'], errors='coerce')\n",
    "\n",
    "data_1\n",
    "\n",
    "from sklearn.model_selection import KFold, cross_val_score, train_test_split\n",
    "\n",
    "X_train_1, X_test_1,y_train_1, y_test_1 =train_test_split(X, data_1[\"Churn Reason\"], test_size=0.05, random_state=56)\n",
    "\n",
    "best_lr2.fit(X,data_1[\"Churn Reason\"])\n",
    "\n",
    "best_lr2.score(X_test_1,y_test_1)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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