deploy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.feature_extraction import DictVectorizer\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import roc_auc_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>customerID</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>9237-HQITU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gender</th>\n",
       "      <td>Female</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Partner</th>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dependents</th>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tenure</th>\n",
       "      <td>1</td>\n",
       "      <td>34</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PhoneService</th>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultipleLines</th>\n",
       "      <td>No phone service</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>InternetService</th>\n",
       "      <td>DSL</td>\n",
       "      <td>DSL</td>\n",
       "      <td>DSL</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Fiber optic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OnlineBackup</th>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DeviceProtection</th>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TechSupport</th>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StreamingTV</th>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StreamingMovies</th>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Contract</th>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>One year</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>One year</td>\n",
       "      <td>Month-to-month</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PaymentMethod</th>\n",
       "      <td>Electronic check</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>Electronic check</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <td>29.85</td>\n",
       "      <td>56.95</td>\n",
       "      <td>53.85</td>\n",
       "      <td>42.3</td>\n",
       "      <td>70.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalCharges</th>\n",
       "      <td>29.85</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>108.15</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>151.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Churn</th>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 0             1               2  \\\n",
       "customerID              7590-VHVEG    5575-GNVDE      3668-QPYBK   \n",
       "gender                      Female          Male            Male   \n",
       "SeniorCitizen                    0             0               0   \n",
       "Partner                        Yes            No              No   \n",
       "Dependents                      No            No              No   \n",
       "tenure                           1            34               2   \n",
       "PhoneService                    No           Yes             Yes   \n",
       "MultipleLines     No phone service            No              No   \n",
       "InternetService                DSL           DSL             DSL   \n",
       "OnlineSecurity                  No           Yes             Yes   \n",
       "OnlineBackup                   Yes            No             Yes   \n",
       "DeviceProtection                No           Yes              No   \n",
       "TechSupport                     No            No              No   \n",
       "StreamingTV                     No            No              No   \n",
       "StreamingMovies                 No            No              No   \n",
       "Contract            Month-to-month      One year  Month-to-month   \n",
       "PaperlessBilling               Yes            No             Yes   \n",
       "PaymentMethod     Electronic check  Mailed check    Mailed check   \n",
       "MonthlyCharges               29.85         56.95           53.85   \n",
       "TotalCharges                 29.85        1889.5          108.15   \n",
       "Churn                           No            No             Yes   \n",
       "\n",
       "                                          3                 4  \n",
       "customerID                       7795-CFOCW        9237-HQITU  \n",
       "gender                                 Male            Female  \n",
       "SeniorCitizen                             0                 0  \n",
       "Partner                                  No                No  \n",
       "Dependents                               No                No  \n",
       "tenure                                   45                 2  \n",
       "PhoneService                             No               Yes  \n",
       "MultipleLines              No phone service                No  \n",
       "InternetService                         DSL       Fiber optic  \n",
       "OnlineSecurity                          Yes                No  \n",
       "OnlineBackup                             No                No  \n",
       "DeviceProtection                        Yes                No  \n",
       "TechSupport                             Yes                No  \n",
       "StreamingTV                              No                No  \n",
       "StreamingMovies                          No                No  \n",
       "Contract                           One year    Month-to-month  \n",
       "PaperlessBilling                         No               Yes  \n",
       "PaymentMethod     Bank transfer (automatic)  Electronic check  \n",
       "MonthlyCharges                         42.3              70.7  \n",
       "TotalCharges                        1840.75            151.65  \n",
       "Churn                                    No               Yes  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('WA_Fn-UseC_-Telco-Customer-Churn.csv')\n",
    "df.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   customerID        7043 non-null   object \n",
      " 1   gender            7043 non-null   object \n",
      " 2   SeniorCitizen     7043 non-null   int64  \n",
      " 3   Partner           7043 non-null   object \n",
      " 4   Dependents        7043 non-null   object \n",
      " 5   tenure            7043 non-null   int64  \n",
      " 6   PhoneService      7043 non-null   object \n",
      " 7   MultipleLines     7043 non-null   object \n",
      " 8   InternetService   7043 non-null   object \n",
      " 9   OnlineSecurity    7043 non-null   object \n",
      " 10  OnlineBackup      7043 non-null   object \n",
      " 11  DeviceProtection  7043 non-null   object \n",
      " 12  TechSupport       7043 non-null   object \n",
      " 13  StreamingTV       7043 non-null   object \n",
      " 14  StreamingMovies   7043 non-null   object \n",
      " 15  Contract          7043 non-null   object \n",
      " 16  PaperlessBilling  7043 non-null   object \n",
      " 17  PaymentMethod     7043 non-null   object \n",
      " 18  MonthlyCharges    7043 non-null   float64\n",
      " 19  TotalCharges      7043 non-null   object \n",
      " 20  Churn             7043 non-null   object \n",
      "dtypes: float64(1), int64(2), object(18)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = df.columns.str.lower().str.replace(' ','_')\n",
    "\n",
    "categorical_columns = list(df.dtypes[df.dtypes == 'object'].index)\n",
    "\n",
    "for c in categorical_columns:\n",
    "    df[c] = df[c].str.lower().str.replace(' ','_')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.totalcharges = pd.to_numeric(df.totalcharges, errors='coerce')\n",
    "df.totalcharges = df.totalcharges.fillna(0)\n",
    "\n",
    "df.churn = (df.churn == 'yes').astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>0</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>1889.50</td>\n",
       "      <td>0</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>1</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>0</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>1</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>7038</th>\n",
       "      <td>6840-resvb</td>\n",
       "      <td>male</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>24</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>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>one_year</td>\n",
       "      <td>yes</td>\n",
       "      <td>mailed_check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7039</th>\n",
       "      <td>2234-xaduh</td>\n",
       "      <td>female</td>\n",
       "      <td>0</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>no</td>\n",
       "      <td>yes</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7040</th>\n",
       "      <td>4801-jzazl</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>11</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>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>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7041</th>\n",
       "      <td>8361-ltmkd</td>\n",
       "      <td>male</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>4</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>fiber_optic</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>month-to-month</td>\n",
       "      <td>yes</td>\n",
       "      <td>mailed_check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.60</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7042</th>\n",
       "      <td>3186-ajiek</td>\n",
       "      <td>male</td>\n",
       "      <td>0</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>yes</td>\n",
       "      <td>yes</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerid  gender  seniorcitizen partner dependents  tenure  \\\n",
       "0     7590-vhveg  female              0     yes         no       1   \n",
       "1     5575-gnvde    male              0      no         no      34   \n",
       "2     3668-qpybk    male              0      no         no       2   \n",
       "3     7795-cfocw    male              0      no         no      45   \n",
       "4     9237-hqitu  female              0      no         no       2   \n",
       "...          ...     ...            ...     ...        ...     ...   \n",
       "7038  6840-resvb    male              0     yes        yes      24   \n",
       "7039  2234-xaduh  female              0     yes        yes      72   \n",
       "7040  4801-jzazl  female              0     yes        yes      11   \n",
       "7041  8361-ltmkd    male              1     yes         no       4   \n",
       "7042  3186-ajiek    male              0      no         no      66   \n",
       "\n",
       "     phoneservice     multiplelines internetservice onlinesecurity  ...  \\\n",
       "0              no  no_phone_service             dsl             no  ...   \n",
       "1             yes                no             dsl            yes  ...   \n",
       "2             yes                no             dsl            yes  ...   \n",
       "3              no  no_phone_service             dsl            yes  ...   \n",
       "4             yes                no     fiber_optic             no  ...   \n",
       "...           ...               ...             ...            ...  ...   \n",
       "7038          yes               yes             dsl            yes  ...   \n",
       "7039          yes               yes     fiber_optic             no  ...   \n",
       "7040           no  no_phone_service             dsl            yes  ...   \n",
       "7041          yes               yes     fiber_optic             no  ...   \n",
       "7042          yes                no     fiber_optic            yes  ...   \n",
       "\n",
       "     deviceprotection techsupport streamingtv streamingmovies        contract  \\\n",
       "0                  no          no          no              no  month-to-month   \n",
       "1                 yes          no          no              no        one_year   \n",
       "2                  no          no          no              no  month-to-month   \n",
       "3                 yes         yes          no              no        one_year   \n",
       "4                  no          no          no              no  month-to-month   \n",
       "...               ...         ...         ...             ...             ...   \n",
       "7038              yes         yes         yes             yes        one_year   \n",
       "7039              yes          no         yes             yes        one_year   \n",
       "7040               no          no          no              no  month-to-month   \n",
       "7041               no          no          no              no  month-to-month   \n",
       "7042              yes         yes         yes             yes        two_year   \n",
       "\n",
       "     paperlessbilling              paymentmethod monthlycharges  totalcharges  \\\n",
       "0                 yes           electronic_check          29.85         29.85   \n",
       "1                  no               mailed_check          56.95       1889.50   \n",
       "2                 yes               mailed_check          53.85        108.15   \n",
       "3                  no  bank_transfer_(automatic)          42.30       1840.75   \n",
       "4                 yes           electronic_check          70.70        151.65   \n",
       "...               ...                        ...            ...           ...   \n",
       "7038              yes               mailed_check          84.80       1990.50   \n",
       "7039              yes    credit_card_(automatic)         103.20       7362.90   \n",
       "7040              yes           electronic_check          29.60        346.45   \n",
       "7041              yes               mailed_check          74.40        306.60   \n",
       "7042              yes  bank_transfer_(automatic)         105.65       6844.50   \n",
       "\n",
       "      churn  \n",
       "0         0  \n",
       "1         0  \n",
       "2         1  \n",
       "3         0  \n",
       "4         1  \n",
       "...     ...  \n",
       "7038      0  \n",
       "7039      0  \n",
       "7040      0  \n",
       "7041      1  \n",
       "7042      0  \n",
       "\n",
       "[7043 rows x 21 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train_full, df_test = train_test_split(df, test_size=0.2, random_state=1)\n",
    "\n",
    "df_train_full = df_train_full.reset_index(drop=True)\n",
    "df_test = df_test.reset_index(drop=True)\n",
    "\n",
    "df_train, df_val = train_test_split(df_train_full, test_size=0.25, random_state=1)\n",
    "\n",
    "df_train = df_train.reset_index(drop=True)\n",
    "df_val = df_val.reset_index(drop=True)\n",
    "\n",
    "y_train = df_train.churn.values\n",
    "y_val = df_val.churn.values\n",
    "\n",
    "del df_train['churn']\n",
    "del df_val['churn']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "numerical = ['tenure', 'monthlycharges', 'totalcharges']\n",
    "\n",
    "categorical = ['gender', 'seniorcitizen', 'partner', 'dependents',\n",
    "               'phoneservice', 'multiplelines', 'internetservice',\n",
    "               'onlinesecurity', 'onlinebackup', 'deviceprotection',\n",
    "               'techsupport', 'streamingtv', 'streamingmovies',\n",
    "               'contract', 'paperlessbilling', 'paymentmethod']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "C=1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train(df, y, C=1.0):\n",
    "    cat = df[categorical + numerical].to_dict(orient='records')\n",
    "\n",
    "    dv = DictVectorizer(sparse=False)\n",
    "    dv.fit(cat)\n",
    "\n",
    "    X = dv.transform(cat)\n",
    "\n",
    "    model = LogisticRegression(solver='liblinear', C=C)\n",
    "    model.fit(X, y)\n",
    "\n",
    "    return dv, model\n",
    "\n",
    "def predict(df, dv, model):\n",
    "    cat = df[categorical + numerical].to_dict(orient='records')\n",
    "    X = dv.transform(cat)\n",
    "\n",
    "    y_pred = model.predict_proba(X)[:,1]\n",
    "\n",
    "    return y_pred\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DictVectorizer(sparse=False)\n",
      "LogisticRegression(C=0.5, solver='liblinear')\n"
     ]
    }
   ],
   "source": [
    "y_train = df_train_full.churn.values\n",
    "y_test = df_test.churn.values\n",
    "\n",
    "dv, model = train(df_train_full, y_train, C=0.5)\n",
    "print(dv)\n",
    "print(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>8879-zkjof</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>41</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>dsl</td>\n",
       "      <td>yes</td>\n",
       "      <td>...</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>one_year</td>\n",
       "      <td>yes</td>\n",
       "      <td>bank_transfer_(automatic)</td>\n",
       "      <td>79.85</td>\n",
       "      <td>3320.75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0201-mibol</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>66</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>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>two_year</td>\n",
       "      <td>yes</td>\n",
       "      <td>bank_transfer_(automatic)</td>\n",
       "      <td>102.40</td>\n",
       "      <td>6471.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1600-dilpe</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>12</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</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>bank_transfer_(automatic)</td>\n",
       "      <td>45.00</td>\n",
       "      <td>524.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8601-qacrs</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>5</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>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>mailed_check</td>\n",
       "      <td>50.60</td>\n",
       "      <td>249.95</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7919-zodzz</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>10</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>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>one_year</td>\n",
       "      <td>yes</td>\n",
       "      <td>mailed_check</td>\n",
       "      <td>65.90</td>\n",
       "      <td>660.05</td>\n",
       "      <td>0</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  8879-zkjof  female              0      no         no      41          yes   \n",
       "1  0201-mibol  female              1      no         no      66          yes   \n",
       "2  1600-dilpe  female              0      no         no      12          yes   \n",
       "3  8601-qacrs  female              0      no         no       5          yes   \n",
       "4  7919-zodzz  female              0     yes        yes      10          yes   \n",
       "\n",
       "  multiplelines internetservice onlinesecurity  ... deviceprotection  \\\n",
       "0            no             dsl            yes  ...              yes   \n",
       "1           yes     fiber_optic            yes  ...               no   \n",
       "2            no             dsl             no  ...               no   \n",
       "3           yes             dsl             no  ...               no   \n",
       "4            no             dsl             no  ...              yes   \n",
       "\n",
       "  techsupport streamingtv streamingmovies        contract paperlessbilling  \\\n",
       "0         yes         yes             yes        one_year              yes   \n",
       "1          no         yes             yes        two_year              yes   \n",
       "2          no          no              no  month-to-month              yes   \n",
       "3          no          no              no  month-to-month              yes   \n",
       "4          no          no             yes        one_year              yes   \n",
       "\n",
       "               paymentmethod monthlycharges  totalcharges  churn  \n",
       "0  bank_transfer_(automatic)          79.85       3320.75      0  \n",
       "1  bank_transfer_(automatic)         102.40       6471.85      0  \n",
       "2  bank_transfer_(automatic)          45.00        524.35      0  \n",
       "3               mailed_check          50.60        249.95      1  \n",
       "4               mailed_check          65.90        660.05      0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.05960552 0.1243028  0.32774635 ... 0.00680613 0.19979883 0.64293068]\n"
     ]
    }
   ],
   "source": [
    "y_pred = predict(df_test, dv, model)\n",
    "print(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "auc = 0.858\n"
     ]
    }
   ],
   "source": [
    "auc = roc_auc_score(y_test, y_pred)\n",
    "print('auc = %.3f' % auc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "cliente2 = {\n",
    "    'customerid': '8879-zkjor',\n",
    "    'gender': 'male',\n",
    "    'seniorcitizen': 0,\n",
    "    'partner': 'yes',\n",
    "    'dependents': 'yes',\n",
    "    'tenure': 2,\n",
    "    'phoneservice': 'yes',\n",
    "    'multiplelines': 'no',\n",
    "    'internetservice': 'dsl',\n",
    "    'onlinesecurity': 'yes',\n",
    "    'onlinebackup': 'no',\n",
    "    'deviceprotection': 'no',\n",
    "    'techsupport': 'no',\n",
    "    'streamingtv': 'no',\n",
    "    'streamingmovies': 'yes',\n",
    "    'contract': 'one_year',\n",
    "    'paperlessbilling': 'yes',\n",
    "    'paymentmethod': 'bank_transfer_(automatic)',\n",
    "    'monthlycharges': 18,\n",
    "    'totalcharges': 36\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "cliente1 = {\n",
    "    'customerid': '8879-zkjof',\n",
    "    'gender': 'female',\n",
    "    'seniorcitizen': 0,\n",
    "    'partner': 'no',\n",
    "    'dependents': 'no',\n",
    "    'tenure': 41,\n",
    "    'phoneservice': 'yes',\n",
    "    'multiplelines': 'no',\n",
    "    'internetservice': 'dsl',\n",
    "    'onlinesecurity': 'yes',\n",
    "    'onlinebackup': 'no',\n",
    "    'deviceprotection': 'yes',\n",
    "    'techsupport': 'yes',\n",
    "    'streamingtv': 'yes',\n",
    "    'streamingmovies': 'yes',\n",
    "    'contract': 'one_year',\n",
    "    'paperlessbilling': 'yes',\n",
    "    'paymentmethod': 'bank_transfer_(automatic)',\n",
    "    'monthlycharges': 79.85,\n",
    "    'totalcharges': 3320.75\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.22441983987472383"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame([cliente2])\n",
    "y_pred = predict(df, dv, model)\n",
    "y_pred[0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.05960552403272276"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame([cliente1])\n",
    "y_pred = predict(df, dv, model)\n",
    "y_pred[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Guardar el modelo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'model_C=1.0.bin'"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_file = f'model_C={C}.bin'\n",
    "output_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_out = open(output_file, 'wb')\n",
    "pickle.dump((dv, model), f_out)\n",
    "f_out.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('churn-model.bin', 'wb') as f_out:\n",
    "    pickle.dump((dv, model), f_out)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cargar el modelo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "with open('model_C=1.0.bin', 'rb') as f_in:\n",
    "    (dv, model) = pickle.load(f_in)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(DictVectorizer(sparse=False), LogisticRegression(C=0.5, solver='liblinear'))"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dv, model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "cliente3 = {\n",
    "    'customerid': '8879-zkjort',\n",
    "    'gender': 'female',\n",
    "    'seniorcitizen': 0,\n",
    "    'partner': 'no',\n",
    "    'dependents': 'yes',\n",
    "    'tenure': 10,\n",
    "    'phoneservice': 'yes',\n",
    "    'multiplelines': 'no',\n",
    "    'internetservice': 'dsl',\n",
    "    'onlinesecurity': 'yes',\n",
    "    'onlinebackup': 'yes',\n",
    "    'deviceprotection': 'no',\n",
    "    'techsupport': 'no',\n",
    "    'streamingtv': 'no',\n",
    "    'streamingmovies': 'yes',\n",
    "    'contract': 'one_year',\n",
    "    'paperlessbilling': 'yes',\n",
    "    'paymentmethod': 'bank_transfer_(automatic)',\n",
    "    'monthlycharges': 18,\n",
    "    'totalcharges': 180\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  0.,   1.,   0.,   0.,   1.,   1.,   0.,   0.,   1.,   0.,   1.,\n",
       "          0.,   0.,  18.,   1.,   0.,   0.,   0.,   0.,   1.,   0.,   0.,\n",
       "          1.,   0.,   1.,   1.,   0.,   1.,   0.,   0.,   0.,   0.,   1.,\n",
       "          0.,   0.,   0.,   1.,   1.,   0.,   0.,   1.,   0.,   0.,  10.,\n",
       "        180.]])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = dv.transform([cliente3])\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.124983101114703"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict_proba(X)[0,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}