pratica_churn.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Criar DataFrame com Base nos Datasets\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Carregar Dataframe de Clientes (Customer)\n",
    "\n",
    "df_customers = pd.read_csv('/home/rafnaves/estudos/rocketseat/IA/eda/datasets/churn_customers.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</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",
       "    </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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  gender  SeniorCitizen Partner Dependents\n",
       "0  7590-VHVEG  Female              0     Yes         No\n",
       "1  5575-GNVDE    Male              0      No         No\n",
       "2  3668-QPYBK    Male              0      No         No\n",
       "3  7795-CFOCW    Male              0      No         No\n",
       "4  9237-HQITU  Female              0      No         No"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Mostrar 5 primeiros registros\n",
    "df_customers.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "  <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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\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",
       "    </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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "      customerID  gender  SeniorCitizen Partner Dependents\n",
       "7038  6840-RESVB    Male              0     Yes        Yes\n",
       "7039  2234-XADUH  Female              0     Yes        Yes\n",
       "7040  4801-JZAZL  Female              0     Yes        Yes\n",
       "7041  8361-LTMKD    Male              1     Yes         No\n",
       "7042  3186-AJIEK    Male              0      No         No"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Mostrar 5 ultimos registros\n",
    "df_customers.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 5 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",
      "dtypes: int64(1), object(4)\n",
      "memory usage: 275.2+ KB\n"
     ]
    }
   ],
   "source": [
    "# Mostrar Estrutura / Schema do DataFrame\n",
    "df_customers.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 10 columns):\n",
      " #   Column            Non-Null Count  Dtype \n",
      "---  ------            --------------  ----- \n",
      " 0   customerID        7043 non-null   object\n",
      " 1   PhoneService      7043 non-null   object\n",
      " 2   MultipleLines     7043 non-null   object\n",
      " 3   InternetService   7043 non-null   object\n",
      " 4   OnlineSecurity    7043 non-null   object\n",
      " 5   OnlineBackup      7043 non-null   object\n",
      " 6   DeviceProtection  7043 non-null   object\n",
      " 7   TechSupport       7043 non-null   object\n",
      " 8   StreamingTV       7043 non-null   object\n",
      " 9   StreamingMovies   7043 non-null   object\n",
      "dtypes: object(10)\n",
      "memory usage: 550.4+ KB\n"
     ]
    }
   ],
   "source": [
    "# Dataframe de serviços (services)\n",
    "# Carregar Dataframe de Clientes (Customer)\n",
    "\n",
    "df_services = pd.read_csv('/home/rafnaves/estudos/rocketseat/IA/eda/datasets/churn_services.csv')\n",
    "df_services.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
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       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID PhoneService     MultipleLines InternetService OnlineSecurity  \\\n",
       "0  7590-VHVEG           No  No phone service             DSL             No   \n",
       "1  5575-GNVDE          Yes                No             DSL            Yes   \n",
       "2  3668-QPYBK          Yes                No             DSL            Yes   \n",
       "3  7795-CFOCW           No  No phone service             DSL            Yes   \n",
       "4  9237-HQITU          Yes                No     Fiber optic             No   \n",
       "\n",
       "  OnlineBackup DeviceProtection TechSupport StreamingTV StreamingMovies  \n",
       "0          Yes               No          No          No              No  \n",
       "1           No              Yes          No          No              No  \n",
       "2          Yes               No          No          No              No  \n",
       "3           No              Yes         Yes          No              No  \n",
       "4           No               No          No          No              No  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_services.head(5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
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       "      <td>6840-RESVB</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
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       "      <td>Yes</td>\n",
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       "      <th>7039</th>\n",
       "      <td>2234-XADUH</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
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       "      <th>7040</th>\n",
       "      <td>4801-JZAZL</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
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       "      <td>8361-LTMKD</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7042</th>\n",
       "      <td>3186-AJIEK</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerID PhoneService     MultipleLines InternetService  \\\n",
       "7038  6840-RESVB          Yes               Yes             DSL   \n",
       "7039  2234-XADUH          Yes               Yes     Fiber optic   \n",
       "7040  4801-JZAZL           No  No phone service             DSL   \n",
       "7041  8361-LTMKD          Yes               Yes     Fiber optic   \n",
       "7042  3186-AJIEK          Yes                No     Fiber optic   \n",
       "\n",
       "     OnlineSecurity OnlineBackup DeviceProtection TechSupport StreamingTV  \\\n",
       "7038            Yes           No              Yes         Yes         Yes   \n",
       "7039             No          Yes              Yes          No         Yes   \n",
       "7040            Yes           No               No          No          No   \n",
       "7041             No           No               No          No          No   \n",
       "7042            Yes           No              Yes         Yes         Yes   \n",
       "\n",
       "     StreamingMovies  \n",
       "7038             Yes  \n",
       "7039             Yes  \n",
       "7040              No  \n",
       "7041              No  \n",
       "7042             Yes  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_services.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>tenure</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>1</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>34</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>2</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>45</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>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  tenure        Contract PaperlessBilling  \\\n",
       "0  7590-VHVEG       1  Month-to-month              Yes   \n",
       "1  5575-GNVDE      34        One year               No   \n",
       "2  3668-QPYBK       2  Month-to-month              Yes   \n",
       "3  7795-CFOCW      45        One year               No   \n",
       "4  9237-HQITU       2  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  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Carregar DataFrame de Contratos (contracts)\n",
    "df_contracts = pd.read_csv('/home/rafnaves/estudos/rocketseat/IA/eda/datasets/churn_contracts.csv')\n",
    "df_contracts.head(5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 8 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   customerID        7043 non-null   object \n",
      " 1   tenure            7043 non-null   int64  \n",
      " 2   Contract          7043 non-null   object \n",
      " 3   PaperlessBilling  7043 non-null   object \n",
      " 4   PaymentMethod     7043 non-null   object \n",
      " 5   MonthlyCharges    7043 non-null   float64\n",
      " 6   TotalCharges      7043 non-null   object \n",
      " 7   Churn             7043 non-null   object \n",
      "dtypes: float64(1), int64(1), object(6)\n",
      "memory usage: 440.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df_contracts.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>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>7038</th>\n",
       "      <td>6840-RESVB</td>\n",
       "      <td>24</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7039</th>\n",
       "      <td>2234-XADUH</td>\n",
       "      <td>72</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.9</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7040</th>\n",
       "      <td>4801-JZAZL</td>\n",
       "      <td>11</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>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7041</th>\n",
       "      <td>8361-LTMKD</td>\n",
       "      <td>4</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.6</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7042</th>\n",
       "      <td>3186-AJIEK</td>\n",
       "      <td>66</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.65</td>\n",
       "      <td>6844.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerID  tenure        Contract PaperlessBilling  \\\n",
       "7038  6840-RESVB      24        One year              Yes   \n",
       "7039  2234-XADUH      72        One year              Yes   \n",
       "7040  4801-JZAZL      11  Month-to-month              Yes   \n",
       "7041  8361-LTMKD       4  Month-to-month              Yes   \n",
       "7042  3186-AJIEK      66        Two year              Yes   \n",
       "\n",
       "                  PaymentMethod  MonthlyCharges TotalCharges Churn  \n",
       "7038               Mailed check           84.80       1990.5    No  \n",
       "7039    Credit card (automatic)          103.20       7362.9    No  \n",
       "7040           Electronic check           29.60       346.45    No  \n",
       "7041               Mailed check           74.40        306.6   Yes  \n",
       "7042  Bank transfer (automatic)          105.65       6844.5    No  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_contracts.tail(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transformação de Dados\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "could not convert string to float: ' '",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[13], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Transformar coluna TotalCharges de String para Float - Abordagem 1 com astype\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m df_contracts\u001b[38;5;241m.\u001b[39mTotalCharges \u001b[38;5;241m=\u001b[39m \u001b[43mdf_contracts\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTotalCharges\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mastype\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.pyenv/versions/IA/lib/python3.11/site-packages/pandas/core/generic.py:6643\u001b[0m, in \u001b[0;36mNDFrame.astype\u001b[0;34m(self, dtype, copy, errors)\u001b[0m\n\u001b[1;32m   6637\u001b[0m     results \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m   6638\u001b[0m         ser\u001b[38;5;241m.\u001b[39mastype(dtype, copy\u001b[38;5;241m=\u001b[39mcopy, errors\u001b[38;5;241m=\u001b[39merrors) \u001b[38;5;28;01mfor\u001b[39;00m _, ser \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mitems()\n\u001b[1;32m   6639\u001b[0m     ]\n\u001b[1;32m   6641\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   6642\u001b[0m     \u001b[38;5;66;03m# else, only a single dtype is given\u001b[39;00m\n\u001b[0;32m-> 6643\u001b[0m     new_data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_mgr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mastype\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   6644\u001b[0m     res \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_constructor_from_mgr(new_data, axes\u001b[38;5;241m=\u001b[39mnew_data\u001b[38;5;241m.\u001b[39maxes)\n\u001b[1;32m   6645\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m res\u001b[38;5;241m.\u001b[39m__finalize__(\u001b[38;5;28mself\u001b[39m, method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mastype\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "File \u001b[0;32m~/.pyenv/versions/IA/lib/python3.11/site-packages/pandas/core/internals/managers.py:430\u001b[0m, in \u001b[0;36mBaseBlockManager.astype\u001b[0;34m(self, dtype, copy, errors)\u001b[0m\n\u001b[1;32m    427\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m using_copy_on_write():\n\u001b[1;32m    428\u001b[0m     copy \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m--> 430\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    431\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mastype\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    432\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    433\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    434\u001b[0m \u001b[43m    \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    435\u001b[0m \u001b[43m    \u001b[49m\u001b[43musing_cow\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43musing_copy_on_write\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    436\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.pyenv/versions/IA/lib/python3.11/site-packages/pandas/core/internals/managers.py:363\u001b[0m, in \u001b[0;36mBaseBlockManager.apply\u001b[0;34m(self, f, align_keys, **kwargs)\u001b[0m\n\u001b[1;32m    361\u001b[0m         applied \u001b[38;5;241m=\u001b[39m b\u001b[38;5;241m.\u001b[39mapply(f, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    362\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 363\u001b[0m         applied \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    364\u001b[0m     result_blocks \u001b[38;5;241m=\u001b[39m extend_blocks(applied, result_blocks)\n\u001b[1;32m    366\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtype\u001b[39m(\u001b[38;5;28mself\u001b[39m)\u001b[38;5;241m.\u001b[39mfrom_blocks(result_blocks, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxes)\n",
      "File \u001b[0;32m~/.pyenv/versions/IA/lib/python3.11/site-packages/pandas/core/internals/blocks.py:758\u001b[0m, in \u001b[0;36mBlock.astype\u001b[0;34m(self, dtype, copy, errors, using_cow, squeeze)\u001b[0m\n\u001b[1;32m    755\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCan not squeeze with more than one column.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    756\u001b[0m     values \u001b[38;5;241m=\u001b[39m values[\u001b[38;5;241m0\u001b[39m, :]  \u001b[38;5;66;03m# type: ignore[call-overload]\u001b[39;00m\n\u001b[0;32m--> 758\u001b[0m new_values \u001b[38;5;241m=\u001b[39m \u001b[43mastype_array_safe\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    760\u001b[0m new_values \u001b[38;5;241m=\u001b[39m maybe_coerce_values(new_values)\n\u001b[1;32m    762\u001b[0m refs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/.pyenv/versions/IA/lib/python3.11/site-packages/pandas/core/dtypes/astype.py:237\u001b[0m, in \u001b[0;36mastype_array_safe\u001b[0;34m(values, dtype, copy, errors)\u001b[0m\n\u001b[1;32m    234\u001b[0m     dtype \u001b[38;5;241m=\u001b[39m dtype\u001b[38;5;241m.\u001b[39mnumpy_dtype\n\u001b[1;32m    236\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 237\u001b[0m     new_values \u001b[38;5;241m=\u001b[39m \u001b[43mastype_array\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    238\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mValueError\u001b[39;00m, \u001b[38;5;167;01mTypeError\u001b[39;00m):\n\u001b[1;32m    239\u001b[0m     \u001b[38;5;66;03m# e.g. _astype_nansafe can fail on object-dtype of strings\u001b[39;00m\n\u001b[1;32m    240\u001b[0m     \u001b[38;5;66;03m#  trying to convert to float\u001b[39;00m\n\u001b[1;32m    241\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m errors \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n",
      "File \u001b[0;32m~/.pyenv/versions/IA/lib/python3.11/site-packages/pandas/core/dtypes/astype.py:182\u001b[0m, in \u001b[0;36mastype_array\u001b[0;34m(values, dtype, copy)\u001b[0m\n\u001b[1;32m    179\u001b[0m     values \u001b[38;5;241m=\u001b[39m values\u001b[38;5;241m.\u001b[39mastype(dtype, copy\u001b[38;5;241m=\u001b[39mcopy)\n\u001b[1;32m    181\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 182\u001b[0m     values \u001b[38;5;241m=\u001b[39m \u001b[43m_astype_nansafe\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    184\u001b[0m \u001b[38;5;66;03m# in pandas we don't store numpy str dtypes, so convert to object\u001b[39;00m\n\u001b[1;32m    185\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(dtype, np\u001b[38;5;241m.\u001b[39mdtype) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28missubclass\u001b[39m(values\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mtype, \u001b[38;5;28mstr\u001b[39m):\n",
      "File \u001b[0;32m~/.pyenv/versions/IA/lib/python3.11/site-packages/pandas/core/dtypes/astype.py:133\u001b[0m, in \u001b[0;36m_astype_nansafe\u001b[0;34m(arr, dtype, copy, skipna)\u001b[0m\n\u001b[1;32m    129\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(msg)\n\u001b[1;32m    131\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m copy \u001b[38;5;129;01mor\u001b[39;00m arr\u001b[38;5;241m.\u001b[39mdtype \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mobject\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m dtype \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mobject\u001b[39m:\n\u001b[1;32m    132\u001b[0m     \u001b[38;5;66;03m# Explicit copy, or required since NumPy can't view from / to object.\u001b[39;00m\n\u001b[0;32m--> 133\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43marr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mastype\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m    135\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m arr\u001b[38;5;241m.\u001b[39mastype(dtype, copy\u001b[38;5;241m=\u001b[39mcopy)\n",
      "\u001b[0;31mValueError\u001b[0m: could not convert string to float: ' '"
     ]
    }
   ],
   "source": [
    "# Transformar coluna TotalCharges de String para Float - Abordagem 1 com astype\n",
    "df_contracts.TotalCharges = df_contracts.TotalCharges.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Unable to parse string \" \" at position 488",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "File \u001b[0;32mlib.pyx:2391\u001b[0m, in \u001b[0;36mpandas._libs.lib.maybe_convert_numeric\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Unable to parse string \" \"",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[14], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Transformar coluna TotalCharges de String para Float - abordagem 2 (to_numeric)\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m df_contracts\u001b[38;5;241m.\u001b[39mTotalCharges \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_numeric\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdf_contracts\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTotalCharges\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.pyenv/versions/IA/lib/python3.11/site-packages/pandas/core/tools/numeric.py:232\u001b[0m, in \u001b[0;36mto_numeric\u001b[0;34m(arg, errors, downcast, dtype_backend)\u001b[0m\n\u001b[1;32m    230\u001b[0m coerce_numeric \u001b[38;5;241m=\u001b[39m errors \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mraise\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    231\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 232\u001b[0m     values, new_mask \u001b[38;5;241m=\u001b[39m \u001b[43mlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmaybe_convert_numeric\u001b[49m\u001b[43m(\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# type: ignore[call-overload]\u001b[39;49;00m\n\u001b[1;32m    233\u001b[0m \u001b[43m        \u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    234\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mset\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    235\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcoerce_numeric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcoerce_numeric\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    236\u001b[0m \u001b[43m        \u001b[49m\u001b[43mconvert_to_masked_nullable\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype_backend\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mis\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mno_default\u001b[49m\n\u001b[1;32m    237\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43misinstance\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mvalues_dtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mStringDtype\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    238\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;129;43;01mand\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mvalues_dtype\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstorage\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m==\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpyarrow_numpy\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    239\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    240\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mValueError\u001b[39;00m, \u001b[38;5;167;01mTypeError\u001b[39;00m):\n\u001b[1;32m    241\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m errors \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mraise\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n",
      "File \u001b[0;32mlib.pyx:2433\u001b[0m, in \u001b[0;36mpandas._libs.lib.maybe_convert_numeric\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Unable to parse string \" \" at position 488"
     ]
    }
   ],
   "source": [
    "# Transformar coluna TotalCharges de String para Float - abordagem 2 (to_numeric)\n",
    "df_contracts.TotalCharges = pd.to_numeric(df_contracts.TotalCharges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transformar coluna TotalCharges de String para Float - abordagem 3 (to_numeric com coerce)\n",
    "\n",
    "df_contracts.TotalCharges = pd.to_numeric(df_contracts.TotalCharges, errors='coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 8 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   customerID        7043 non-null   object \n",
      " 1   tenure            7043 non-null   int64  \n",
      " 2   Contract          7043 non-null   object \n",
      " 3   PaperlessBilling  7043 non-null   object \n",
      " 4   PaymentMethod     7043 non-null   object \n",
      " 5   MonthlyCharges    7043 non-null   float64\n",
      " 6   TotalCharges      7032 non-null   float64\n",
      " 7   Churn             7043 non-null   object \n",
      "dtypes: float64(2), int64(1), object(5)\n",
      "memory usage: 440.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df_contracts.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Após a transfomarção de TotalCharges para numerics, a coluna passou a ter 11 valores ausentes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Renomear Colunas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Above65yo</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</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",
       "    </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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\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",
       "    </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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerID  gender  Above65yo Partner Dependents\n",
       "0     7590-VHVEG  Female          0     Yes         No\n",
       "1     5575-GNVDE    Male          0      No         No\n",
       "2     3668-QPYBK    Male          0      No         No\n",
       "3     7795-CFOCW    Male          0      No         No\n",
       "4     9237-HQITU  Female          0      No         No\n",
       "...          ...     ...        ...     ...        ...\n",
       "7038  6840-RESVB    Male          0     Yes        Yes\n",
       "7039  2234-XADUH  Female          0     Yes        Yes\n",
       "7040  4801-JZAZL  Female          0     Yes        Yes\n",
       "7041  8361-LTMKD    Male          1     Yes         No\n",
       "7042  3186-AJIEK    Male          0      No         No\n",
       "\n",
       "[7043 rows x 5 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Renomear coluna no DataFrame, usando rename e dicionario\n",
    "df_customers.rename(columns={'SeniorCitizen':'Above65yo'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 5 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",
      "dtypes: int64(1), object(4)\n",
      "memory usage: 275.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df_customers.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 5 columns):\n",
      " #   Column      Non-Null Count  Dtype \n",
      "---  ------      --------------  ----- \n",
      " 0   customerID  7043 non-null   object\n",
      " 1   gender      7043 non-null   object\n",
      " 2   Above65yo   7043 non-null   int64 \n",
      " 3   Partner     7043 non-null   object\n",
      " 4   Dependents  7043 non-null   object\n",
      "dtypes: int64(1), object(4)\n",
      "memory usage: 275.2+ KB\n"
     ]
    }
   ],
   "source": [
    "# Criar um DataFrame com Base nas colunas renomeadas\n",
    "df_customers_renamed = df_customers.rename(columns={'SeniorCitizen':'Above65yo'})\n",
    "df_customers_renamed.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 5 columns):\n",
      " #   Column      Non-Null Count  Dtype \n",
      "---  ------      --------------  ----- \n",
      " 0   customerID  7043 non-null   object\n",
      " 1   gender      7043 non-null   object\n",
      " 2   Above65yo   7043 non-null   int64 \n",
      " 3   Partner     7043 non-null   object\n",
      " 4   Dependents  7043 non-null   object\n",
      "dtypes: int64(1), object(4)\n",
      "memory usage: 275.2+ KB\n"
     ]
    }
   ],
   "source": [
    "# Aplicar o resultado do rename no proprio DataFrame\n",
    "df_customers.rename(columns={'SeniorCitizen':'Above65yo'}, inplace=True)\n",
    "df_customers.info()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 5 columns):\n",
      " #   Column          Non-Null Count  Dtype \n",
      "---  ------          --------------  ----- \n",
      " 0   IDCliente       7043 non-null   object\n",
      " 1   Genero          7043 non-null   object\n",
      " 2   Mais65anos      7043 non-null   int64 \n",
      " 3   TemParceiro     7043 non-null   object\n",
      " 4   TemDependentes  7043 non-null   object\n",
      "dtypes: int64(1), object(4)\n",
      "memory usage: 275.2+ KB\n"
     ]
    }
   ],
   "source": [
    "# Rename usando Lista - Modificar todos os nomes de colunas\n",
    "df_customers.columns = ['IDCliente', 'Genero','Mais65anos','TemParceiro','TemDependentes']\n",
    "df_customers.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unificar DataFrames de Costumes, Services e Contracts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7043"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Contar quantidade de registros por DataFrame\n",
    "len(df_customers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7043"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_services)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7043"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_contracts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 10 columns):\n",
      " #   Column            Non-Null Count  Dtype \n",
      "---  ------            --------------  ----- \n",
      " 0   IDCliente         7043 non-null   object\n",
      " 1   PhoneService      7043 non-null   object\n",
      " 2   MultipleLines     7043 non-null   object\n",
      " 3   InternetService   7043 non-null   object\n",
      " 4   OnlineSecurity    7043 non-null   object\n",
      " 5   OnlineBackup      7043 non-null   object\n",
      " 6   DeviceProtection  7043 non-null   object\n",
      " 7   TechSupport       7043 non-null   object\n",
      " 8   StreamingTV       7043 non-null   object\n",
      " 9   StreamingMovies   7043 non-null   object\n",
      "dtypes: object(10)\n",
      "memory usage: 550.4+ KB\n"
     ]
    }
   ],
   "source": [
    "# Renomear Colunas\n",
    "df_services.rename(columns={'customerID': 'IDCliente'},inplace=True)\n",
    "df_services.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Unificando DataFrame de customer com services, criando um terceiro DataFrame\n",
    "df_temp = df_customers.merge(df_services, on=['IDCliente'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 14 columns):\n",
      " #   Column            Non-Null Count  Dtype \n",
      "---  ------            --------------  ----- \n",
      " 0   IDCliente         7043 non-null   object\n",
      " 1   Genero            7043 non-null   object\n",
      " 2   Mais65anos        7043 non-null   int64 \n",
      " 3   TemParceiro       7043 non-null   object\n",
      " 4   TemDependentes    7043 non-null   object\n",
      " 5   PhoneService      7043 non-null   object\n",
      " 6   MultipleLines     7043 non-null   object\n",
      " 7   InternetService   7043 non-null   object\n",
      " 8   OnlineSecurity    7043 non-null   object\n",
      " 9   OnlineBackup      7043 non-null   object\n",
      " 10  DeviceProtection  7043 non-null   object\n",
      " 11  TechSupport       7043 non-null   object\n",
      " 12  StreamingTV       7043 non-null   object\n",
      " 13  StreamingMovies   7043 non-null   object\n",
      "dtypes: int64(1), object(13)\n",
      "memory usage: 770.5+ KB\n"
     ]
    }
   ],
   "source": [
    "# Mostrar dataframe temp\n",
    "df_temp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "    </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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0  7590-VHVEG  Female           0         Yes             No           No   \n",
       "1  5575-GNVDE    Male           0          No             No          Yes   \n",
       "2  3668-QPYBK    Male           0          No             No          Yes   \n",
       "3  7795-CFOCW    Male           0          No             No           No   \n",
       "4  9237-HQITU  Female           0          No             No          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
       "0  No phone service             DSL             No          Yes   \n",
       "1                No             DSL            Yes           No   \n",
       "2                No             DSL            Yes          Yes   \n",
       "3  No phone service             DSL            Yes           No   \n",
       "4                No     Fiber optic             No           No   \n",
       "\n",
       "  DeviceProtection TechSupport StreamingTV StreamingMovies  \n",
       "0               No          No          No              No  \n",
       "1              Yes          No          No              No  \n",
       "2               No          No          No              No  \n",
       "3              Yes         Yes          No              No  \n",
       "4               No          No          No              No  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_temp.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merge com nomes de coluna diferentes porem conteudo iguals\n",
    "df_churn_temp = df_temp.merge(df_contracts, left_on=['IDCliente'], right_on=['customerID'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 22 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   IDCliente         7043 non-null   object \n",
      " 1   Genero            7043 non-null   object \n",
      " 2   Mais65anos        7043 non-null   int64  \n",
      " 3   TemParceiro       7043 non-null   object \n",
      " 4   TemDependentes    7043 non-null   object \n",
      " 5   PhoneService      7043 non-null   object \n",
      " 6   MultipleLines     7043 non-null   object \n",
      " 7   InternetService   7043 non-null   object \n",
      " 8   OnlineSecurity    7043 non-null   object \n",
      " 9   OnlineBackup      7043 non-null   object \n",
      " 10  DeviceProtection  7043 non-null   object \n",
      " 11  TechSupport       7043 non-null   object \n",
      " 12  StreamingTV       7043 non-null   object \n",
      " 13  StreamingMovies   7043 non-null   object \n",
      " 14  customerID        7043 non-null   object \n",
      " 15  tenure            7043 non-null   int64  \n",
      " 16  Contract          7043 non-null   object \n",
      " 17  PaperlessBilling  7043 non-null   object \n",
      " 18  PaymentMethod     7043 non-null   object \n",
      " 19  MonthlyCharges    7043 non-null   float64\n",
      " 20  TotalCharges      7032 non-null   float64\n",
      " 21  Churn             7043 non-null   object \n",
      "dtypes: float64(2), int64(2), object(18)\n",
      "memory usage: 1.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df_churn_temp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 22 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   IDCliente         7043 non-null   object \n",
      " 1   Genero            7043 non-null   object \n",
      " 2   Mais65anos        7043 non-null   int64  \n",
      " 3   TemParceiro       7043 non-null   object \n",
      " 4   TemDependentes    7043 non-null   object \n",
      " 5   PhoneService      7043 non-null   object \n",
      " 6   MultipleLines     7043 non-null   object \n",
      " 7   InternetService   7043 non-null   object \n",
      " 8   OnlineSecurity    7043 non-null   object \n",
      " 9   OnlineBackup      7043 non-null   object \n",
      " 10  DeviceProtection  7043 non-null   object \n",
      " 11  TechSupport       7043 non-null   object \n",
      " 12  StreamingTV       7043 non-null   object \n",
      " 13  StreamingMovies   7043 non-null   object \n",
      " 14  customerID        7043 non-null   object \n",
      " 15  tenure            7043 non-null   int64  \n",
      " 16  Contract          7043 non-null   object \n",
      " 17  PaperlessBilling  7043 non-null   object \n",
      " 18  PaymentMethod     7043 non-null   object \n",
      " 19  MonthlyCharges    7043 non-null   float64\n",
      " 20  TotalCharges      7032 non-null   float64\n",
      " 21  Churn             7043 non-null   object \n",
      "dtypes: float64(2), int64(2), object(18)\n",
      "memory usage: 1.2+ MB\n"
     ]
    }
   ],
   "source": [
    "# Unificar os tres dataframes de uma vez, com colunas de nomes diferentes\n",
    "df_churn = df_customers.merge(df_services, on=['IDCliente']).merge(df_contracts, left_on=['IDCliente'], right_on=['customerID'])\n",
    "df_churn.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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   IDCliente         7043 non-null   object \n",
      " 1   Genero            7043 non-null   object \n",
      " 2   Mais65anos        7043 non-null   int64  \n",
      " 3   TemParceiro       7043 non-null   object \n",
      " 4   TemDependentes    7043 non-null   object \n",
      " 5   PhoneService      7043 non-null   object \n",
      " 6   MultipleLines     7043 non-null   object \n",
      " 7   InternetService   7043 non-null   object \n",
      " 8   OnlineSecurity    7043 non-null   object \n",
      " 9   OnlineBackup      7043 non-null   object \n",
      " 10  DeviceProtection  7043 non-null   object \n",
      " 11  TechSupport       7043 non-null   object \n",
      " 12  StreamingTV       7043 non-null   object \n",
      " 13  StreamingMovies   7043 non-null   object \n",
      " 14  tenure            7043 non-null   int64  \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      7032 non-null   float64\n",
      " 20  Churn             7043 non-null   object \n",
      "dtypes: float64(2), int64(2), object(17)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "# Removendo coluna duplicada\n",
    "df_churn.drop(['customerID'], axis=1, inplace=True)\n",
    "df_churn.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Detecção de Valores ausentes \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IDCliente            0\n",
       "Genero               0\n",
       "Mais65anos           0\n",
       "TemParceiro          0\n",
       "TemDependentes       0\n",
       "PhoneService         0\n",
       "MultipleLines        0\n",
       "InternetService      0\n",
       "OnlineSecurity       0\n",
       "OnlineBackup         0\n",
       "DeviceProtection     0\n",
       "TechSupport          0\n",
       "StreamingTV          0\n",
       "StreamingMovies      0\n",
       "tenure               0\n",
       "Contract             0\n",
       "PaperlessBilling     0\n",
       "PaymentMethod        0\n",
       "MonthlyCharges       0\n",
       "TotalCharges        11\n",
       "Churn                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Detecção de Valores ausentes em todas colunas de um DataFrame\n",
    "\n",
    "df_churn.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(11)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Detectar valores ausentes em uma coluna\n",
    "df_churn.TotalCharges.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>4472-LVYGI</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>52.55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>3115-CZMZD</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>936</th>\n",
       "      <td>5709-LVOEQ</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>80.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1082</th>\n",
       "      <td>4367-NUYAO</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>25.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1340</th>\n",
       "      <td>1371-DWPAZ</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>56.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3331</th>\n",
       "      <td>7644-OMVMY</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>19.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3826</th>\n",
       "      <td>3213-VVOLG</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>25.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4380</th>\n",
       "      <td>2520-SGTTA</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5218</th>\n",
       "      <td>2923-ARZLG</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>0</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>19.70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6670</th>\n",
       "      <td>4075-WKNIU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>73.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6754</th>\n",
       "      <td>2775-SEFEE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>61.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "488   4472-LVYGI  Female           0         Yes            Yes           No   \n",
       "753   3115-CZMZD    Male           0          No            Yes          Yes   \n",
       "936   5709-LVOEQ  Female           0         Yes            Yes          Yes   \n",
       "1082  4367-NUYAO    Male           0         Yes            Yes          Yes   \n",
       "1340  1371-DWPAZ  Female           0         Yes            Yes           No   \n",
       "3331  7644-OMVMY    Male           0         Yes            Yes          Yes   \n",
       "3826  3213-VVOLG    Male           0         Yes            Yes          Yes   \n",
       "4380  2520-SGTTA  Female           0         Yes            Yes          Yes   \n",
       "5218  2923-ARZLG    Male           0         Yes            Yes          Yes   \n",
       "6670  4075-WKNIU  Female           0         Yes            Yes          Yes   \n",
       "6754  2775-SEFEE    Male           0          No            Yes          Yes   \n",
       "\n",
       "         MultipleLines InternetService       OnlineSecurity  \\\n",
       "488   No phone service             DSL                  Yes   \n",
       "753                 No              No  No internet service   \n",
       "936                 No             DSL                  Yes   \n",
       "1082               Yes              No  No internet service   \n",
       "1340  No phone service             DSL                  Yes   \n",
       "3331                No              No  No internet service   \n",
       "3826               Yes              No  No internet service   \n",
       "4380                No              No  No internet service   \n",
       "5218                No              No  No internet service   \n",
       "6670               Yes             DSL                   No   \n",
       "6754               Yes             DSL                  Yes   \n",
       "\n",
       "             OnlineBackup  ...          TechSupport          StreamingTV  \\\n",
       "488                    No  ...                  Yes                  Yes   \n",
       "753   No internet service  ...  No internet service  No internet service   \n",
       "936                   Yes  ...                   No                  Yes   \n",
       "1082  No internet service  ...  No internet service  No internet service   \n",
       "1340                  Yes  ...                  Yes                  Yes   \n",
       "3331  No internet service  ...  No internet service  No internet service   \n",
       "3826  No internet service  ...  No internet service  No internet service   \n",
       "4380  No internet service  ...  No internet service  No internet service   \n",
       "5218  No internet service  ...  No internet service  No internet service   \n",
       "6670                  Yes  ...                  Yes                  Yes   \n",
       "6754                  Yes  ...                  Yes                   No   \n",
       "\n",
       "          StreamingMovies tenure  Contract PaperlessBilling  \\\n",
       "488                    No      0  Two year              Yes   \n",
       "753   No internet service      0  Two year               No   \n",
       "936                   Yes      0  Two year               No   \n",
       "1082  No internet service      0  Two year               No   \n",
       "1340                   No      0  Two year               No   \n",
       "3331  No internet service      0  Two year               No   \n",
       "3826  No internet service      0  Two year               No   \n",
       "4380  No internet service      0  Two year               No   \n",
       "5218  No internet service      0  One year              Yes   \n",
       "6670                   No      0  Two year               No   \n",
       "6754                   No      0  Two year              Yes   \n",
       "\n",
       "                  PaymentMethod MonthlyCharges  TotalCharges  Churn  \n",
       "488   Bank transfer (automatic)          52.55           NaN     No  \n",
       "753                Mailed check          20.25           NaN     No  \n",
       "936                Mailed check          80.85           NaN     No  \n",
       "1082               Mailed check          25.75           NaN     No  \n",
       "1340    Credit card (automatic)          56.05           NaN     No  \n",
       "3331               Mailed check          19.85           NaN     No  \n",
       "3826               Mailed check          25.35           NaN     No  \n",
       "4380               Mailed check          20.00           NaN     No  \n",
       "5218               Mailed check          19.70           NaN     No  \n",
       "6670               Mailed check          73.35           NaN     No  \n",
       "6754  Bank transfer (automatic)          61.90           NaN     No  \n",
       "\n",
       "[11 rows x 21 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quantas linhas tem pelo menos 1 coluna com valor ausente\n",
    "df_churn[df_churn.isna().any(axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(1)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quantas colunas tem pelo menos 1 valor ausente\n",
    "df_churn.isna().any(axis=0).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Remover valores ausentes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>Yes</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",
       "    </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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>No</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>11</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.60</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>66</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.65</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "1     5575-GNVDE    Male           0          No             No          Yes   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "3     7795-CFOCW    Male           0          No             No           No   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7038  6840-RESVB    Male           0         Yes            Yes          Yes   \n",
       "7039  2234-XADUH  Female           0         Yes            Yes          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "7042  3186-AJIEK    Male           0          No             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
       "0     No phone service             DSL             No          Yes   \n",
       "1                   No             DSL            Yes           No   \n",
       "2                   No             DSL            Yes          Yes   \n",
       "3     No phone service             DSL            Yes           No   \n",
       "4                   No     Fiber optic             No           No   \n",
       "...                ...             ...            ...          ...   \n",
       "7038               Yes             DSL            Yes           No   \n",
       "7039               Yes     Fiber optic             No          Yes   \n",
       "7040  No phone service             DSL            Yes           No   \n",
       "7041               Yes     Fiber optic             No           No   \n",
       "7042                No     Fiber optic            Yes           No   \n",
       "\n",
       "     DeviceProtection TechSupport StreamingTV StreamingMovies  tenure  \\\n",
       "0                  No          No          No              No       1   \n",
       "1                 Yes          No          No              No      34   \n",
       "2                  No          No          No              No       2   \n",
       "3                 Yes         Yes          No              No      45   \n",
       "4                  No          No          No              No       2   \n",
       "...               ...         ...         ...             ...     ...   \n",
       "7038              Yes         Yes         Yes             Yes      24   \n",
       "7039              Yes          No         Yes             Yes      72   \n",
       "7040               No          No          No              No      11   \n",
       "7041               No          No          No              No       4   \n",
       "7042              Yes         Yes         Yes             Yes      66   \n",
       "\n",
       "            Contract PaperlessBilling              PaymentMethod  \\\n",
       "0     Month-to-month              Yes           Electronic check   \n",
       "1           One year               No               Mailed check   \n",
       "2     Month-to-month              Yes               Mailed check   \n",
       "3           One year               No  Bank transfer (automatic)   \n",
       "4     Month-to-month              Yes           Electronic check   \n",
       "...              ...              ...                        ...   \n",
       "7038        One year              Yes               Mailed check   \n",
       "7039        One year              Yes    Credit card (automatic)   \n",
       "7040  Month-to-month              Yes           Electronic check   \n",
       "7041  Month-to-month              Yes               Mailed check   \n",
       "7042        Two year              Yes  Bank transfer (automatic)   \n",
       "\n",
       "      MonthlyCharges Churn  \n",
       "0              29.85    No  \n",
       "1              56.95    No  \n",
       "2              53.85   Yes  \n",
       "3              42.30    No  \n",
       "4              70.70   Yes  \n",
       "...              ...   ...  \n",
       "7038           84.80    No  \n",
       "7039          103.20    No  \n",
       "7040           29.60    No  \n",
       "7041           74.40   Yes  \n",
       "7042          105.65    No  \n",
       "\n",
       "[7043 rows x 20 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remover de forma direta a coluna\n",
    "df_churn.drop(columns=['TotalCharges'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>Yes</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",
       "    </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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>No</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>11</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.60</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>66</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.65</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "1     5575-GNVDE    Male           0          No             No          Yes   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "3     7795-CFOCW    Male           0          No             No           No   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7038  6840-RESVB    Male           0         Yes            Yes          Yes   \n",
       "7039  2234-XADUH  Female           0         Yes            Yes          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "7042  3186-AJIEK    Male           0          No             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
       "0     No phone service             DSL             No          Yes   \n",
       "1                   No             DSL            Yes           No   \n",
       "2                   No             DSL            Yes          Yes   \n",
       "3     No phone service             DSL            Yes           No   \n",
       "4                   No     Fiber optic             No           No   \n",
       "...                ...             ...            ...          ...   \n",
       "7038               Yes             DSL            Yes           No   \n",
       "7039               Yes     Fiber optic             No          Yes   \n",
       "7040  No phone service             DSL            Yes           No   \n",
       "7041               Yes     Fiber optic             No           No   \n",
       "7042                No     Fiber optic            Yes           No   \n",
       "\n",
       "     DeviceProtection TechSupport StreamingTV StreamingMovies  tenure  \\\n",
       "0                  No          No          No              No       1   \n",
       "1                 Yes          No          No              No      34   \n",
       "2                  No          No          No              No       2   \n",
       "3                 Yes         Yes          No              No      45   \n",
       "4                  No          No          No              No       2   \n",
       "...               ...         ...         ...             ...     ...   \n",
       "7038              Yes         Yes         Yes             Yes      24   \n",
       "7039              Yes          No         Yes             Yes      72   \n",
       "7040               No          No          No              No      11   \n",
       "7041               No          No          No              No       4   \n",
       "7042              Yes         Yes         Yes             Yes      66   \n",
       "\n",
       "            Contract PaperlessBilling              PaymentMethod  \\\n",
       "0     Month-to-month              Yes           Electronic check   \n",
       "1           One year               No               Mailed check   \n",
       "2     Month-to-month              Yes               Mailed check   \n",
       "3           One year               No  Bank transfer (automatic)   \n",
       "4     Month-to-month              Yes           Electronic check   \n",
       "...              ...              ...                        ...   \n",
       "7038        One year              Yes               Mailed check   \n",
       "7039        One year              Yes    Credit card (automatic)   \n",
       "7040  Month-to-month              Yes           Electronic check   \n",
       "7041  Month-to-month              Yes               Mailed check   \n",
       "7042        Two year              Yes  Bank transfer (automatic)   \n",
       "\n",
       "      MonthlyCharges Churn  \n",
       "0              29.85    No  \n",
       "1              56.95    No  \n",
       "2              53.85   Yes  \n",
       "3              42.30    No  \n",
       "4              70.70   Yes  \n",
       "...              ...   ...  \n",
       "7038           84.80    No  \n",
       "7039          103.20    No  \n",
       "7040           29.60    No  \n",
       "7041           74.40   Yes  \n",
       "7042          105.65    No  \n",
       "\n",
       "[7043 rows x 20 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remover colunas com valores ausentes\n",
    "df_churn.dropna(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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",
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       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</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>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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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",
       "    <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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</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>No</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>11</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</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>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>66</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>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "1     5575-GNVDE    Male           0          No             No          Yes   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "3     7795-CFOCW    Male           0          No             No           No   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7038  6840-RESVB    Male           0         Yes            Yes          Yes   \n",
       "7039  2234-XADUH  Female           0         Yes            Yes          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "7042  3186-AJIEK    Male           0          No             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0     No phone service             DSL             No          Yes  ...   \n",
       "1                   No             DSL            Yes           No  ...   \n",
       "2                   No             DSL            Yes          Yes  ...   \n",
       "3     No phone service             DSL            Yes           No  ...   \n",
       "4                   No     Fiber optic             No           No  ...   \n",
       "...                ...             ...            ...          ...  ...   \n",
       "7038               Yes             DSL            Yes           No  ...   \n",
       "7039               Yes     Fiber optic             No          Yes  ...   \n",
       "7040  No phone service             DSL            Yes           No  ...   \n",
       "7041               Yes     Fiber optic             No           No  ...   \n",
       "7042                No     Fiber optic            Yes           No  ...   \n",
       "\n",
       "     TechSupport StreamingTV StreamingMovies tenure        Contract  \\\n",
       "0             No          No              No      1  Month-to-month   \n",
       "1             No          No              No     34        One year   \n",
       "2             No          No              No      2  Month-to-month   \n",
       "3            Yes          No              No     45        One year   \n",
       "4             No          No              No      2  Month-to-month   \n",
       "...          ...         ...             ...    ...             ...   \n",
       "7038         Yes         Yes             Yes     24        One year   \n",
       "7039          No         Yes             Yes     72        One year   \n",
       "7040          No          No              No     11  Month-to-month   \n",
       "7041          No          No              No      4  Month-to-month   \n",
       "7042         Yes         Yes             Yes     66        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        No  \n",
       "1        No  \n",
       "2       Yes  \n",
       "3        No  \n",
       "4       Yes  \n",
       "...     ...  \n",
       "7038     No  \n",
       "7039     No  \n",
       "7040     No  \n",
       "7041    Yes  \n",
       "7042     No  \n",
       "\n",
       "[7043 rows x 21 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remover colunas com todos os valores ausentes\n",
    "df_churn.dropna(axis=1, how='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
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       "    </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",
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       "      <td>No</td>\n",
       "      <td>No</td>\n",
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       "      <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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
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       "      <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",
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       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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",
       "    <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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</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>No</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>11</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</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>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>66</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>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7032 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "1     5575-GNVDE    Male           0          No             No          Yes   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "3     7795-CFOCW    Male           0          No             No           No   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7038  6840-RESVB    Male           0         Yes            Yes          Yes   \n",
       "7039  2234-XADUH  Female           0         Yes            Yes          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "7042  3186-AJIEK    Male           0          No             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0     No phone service             DSL             No          Yes  ...   \n",
       "1                   No             DSL            Yes           No  ...   \n",
       "2                   No             DSL            Yes          Yes  ...   \n",
       "3     No phone service             DSL            Yes           No  ...   \n",
       "4                   No     Fiber optic             No           No  ...   \n",
       "...                ...             ...            ...          ...  ...   \n",
       "7038               Yes             DSL            Yes           No  ...   \n",
       "7039               Yes     Fiber optic             No          Yes  ...   \n",
       "7040  No phone service             DSL            Yes           No  ...   \n",
       "7041               Yes     Fiber optic             No           No  ...   \n",
       "7042                No     Fiber optic            Yes           No  ...   \n",
       "\n",
       "     TechSupport StreamingTV StreamingMovies tenure        Contract  \\\n",
       "0             No          No              No      1  Month-to-month   \n",
       "1             No          No              No     34        One year   \n",
       "2             No          No              No      2  Month-to-month   \n",
       "3            Yes          No              No     45        One year   \n",
       "4             No          No              No      2  Month-to-month   \n",
       "...          ...         ...             ...    ...             ...   \n",
       "7038         Yes         Yes             Yes     24        One year   \n",
       "7039          No         Yes             Yes     72        One year   \n",
       "7040          No          No              No     11  Month-to-month   \n",
       "7041          No          No              No      4  Month-to-month   \n",
       "7042         Yes         Yes             Yes     66        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        No  \n",
       "1        No  \n",
       "2       Yes  \n",
       "3        No  \n",
       "4       Yes  \n",
       "...     ...  \n",
       "7038     No  \n",
       "7039     No  \n",
       "7040     No  \n",
       "7041    Yes  \n",
       "7042     No  \n",
       "\n",
       "[7032 rows x 21 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remover linhas com valores ausentes\n",
    "df_churn.dropna(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</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>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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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",
       "    <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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</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>No</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>11</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</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>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>66</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>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "1     5575-GNVDE    Male           0          No             No          Yes   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "3     7795-CFOCW    Male           0          No             No           No   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7038  6840-RESVB    Male           0         Yes            Yes          Yes   \n",
       "7039  2234-XADUH  Female           0         Yes            Yes          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "7042  3186-AJIEK    Male           0          No             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0     No phone service             DSL             No          Yes  ...   \n",
       "1                   No             DSL            Yes           No  ...   \n",
       "2                   No             DSL            Yes          Yes  ...   \n",
       "3     No phone service             DSL            Yes           No  ...   \n",
       "4                   No     Fiber optic             No           No  ...   \n",
       "...                ...             ...            ...          ...  ...   \n",
       "7038               Yes             DSL            Yes           No  ...   \n",
       "7039               Yes     Fiber optic             No          Yes  ...   \n",
       "7040  No phone service             DSL            Yes           No  ...   \n",
       "7041               Yes     Fiber optic             No           No  ...   \n",
       "7042                No     Fiber optic            Yes           No  ...   \n",
       "\n",
       "     TechSupport StreamingTV StreamingMovies tenure        Contract  \\\n",
       "0             No          No              No      1  Month-to-month   \n",
       "1             No          No              No     34        One year   \n",
       "2             No          No              No      2  Month-to-month   \n",
       "3            Yes          No              No     45        One year   \n",
       "4             No          No              No      2  Month-to-month   \n",
       "...          ...         ...             ...    ...             ...   \n",
       "7038         Yes         Yes             Yes     24        One year   \n",
       "7039          No         Yes             Yes     72        One year   \n",
       "7040          No          No              No     11  Month-to-month   \n",
       "7041          No          No              No      4  Month-to-month   \n",
       "7042         Yes         Yes             Yes     66        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        No  \n",
       "1        No  \n",
       "2       Yes  \n",
       "3        No  \n",
       "4       Yes  \n",
       "...     ...  \n",
       "7038     No  \n",
       "7039     No  \n",
       "7040     No  \n",
       "7041    Yes  \n",
       "7042     No  \n",
       "\n",
       "[7043 rows x 21 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remover linhas com todos os valores ausentes\n",
    "df_churn.dropna(axis=0, how='all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inputação de Valores Ausentes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</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>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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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",
       "    <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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</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>No</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>11</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</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>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>66</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>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "1     5575-GNVDE    Male           0          No             No          Yes   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "3     7795-CFOCW    Male           0          No             No           No   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7038  6840-RESVB    Male           0         Yes            Yes          Yes   \n",
       "7039  2234-XADUH  Female           0         Yes            Yes          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "7042  3186-AJIEK    Male           0          No             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0     No phone service             DSL             No          Yes  ...   \n",
       "1                   No             DSL            Yes           No  ...   \n",
       "2                   No             DSL            Yes          Yes  ...   \n",
       "3     No phone service             DSL            Yes           No  ...   \n",
       "4                   No     Fiber optic             No           No  ...   \n",
       "...                ...             ...            ...          ...  ...   \n",
       "7038               Yes             DSL            Yes           No  ...   \n",
       "7039               Yes     Fiber optic             No          Yes  ...   \n",
       "7040  No phone service             DSL            Yes           No  ...   \n",
       "7041               Yes     Fiber optic             No           No  ...   \n",
       "7042                No     Fiber optic            Yes           No  ...   \n",
       "\n",
       "     TechSupport StreamingTV StreamingMovies tenure        Contract  \\\n",
       "0             No          No              No      1  Month-to-month   \n",
       "1             No          No              No     34        One year   \n",
       "2             No          No              No      2  Month-to-month   \n",
       "3            Yes          No              No     45        One year   \n",
       "4             No          No              No      2  Month-to-month   \n",
       "...          ...         ...             ...    ...             ...   \n",
       "7038         Yes         Yes             Yes     24        One year   \n",
       "7039          No         Yes             Yes     72        One year   \n",
       "7040          No          No              No     11  Month-to-month   \n",
       "7041          No          No              No      4  Month-to-month   \n",
       "7042         Yes         Yes             Yes     66        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        No  \n",
       "1        No  \n",
       "2       Yes  \n",
       "3        No  \n",
       "4       Yes  \n",
       "...     ...  \n",
       "7038     No  \n",
       "7039     No  \n",
       "7040     No  \n",
       "7041    Yes  \n",
       "7042     No  \n",
       "\n",
       "[7043 rows x 21 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Preencher todos os valores ausentes por 0\n",
    "df_churn.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
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       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
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       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</th>\n",
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       "      <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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</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>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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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",
       "    <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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</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>No</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>11</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</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>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>66</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>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "1     5575-GNVDE    Male           0          No             No          Yes   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "3     7795-CFOCW    Male           0          No             No           No   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7038  6840-RESVB    Male           0         Yes            Yes          Yes   \n",
       "7039  2234-XADUH  Female           0         Yes            Yes          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "7042  3186-AJIEK    Male           0          No             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0     No phone service             DSL             No          Yes  ...   \n",
       "1                   No             DSL            Yes           No  ...   \n",
       "2                   No             DSL            Yes          Yes  ...   \n",
       "3     No phone service             DSL            Yes           No  ...   \n",
       "4                   No     Fiber optic             No           No  ...   \n",
       "...                ...             ...            ...          ...  ...   \n",
       "7038               Yes             DSL            Yes           No  ...   \n",
       "7039               Yes     Fiber optic             No          Yes  ...   \n",
       "7040  No phone service             DSL            Yes           No  ...   \n",
       "7041               Yes     Fiber optic             No           No  ...   \n",
       "7042                No     Fiber optic            Yes           No  ...   \n",
       "\n",
       "     TechSupport StreamingTV StreamingMovies tenure        Contract  \\\n",
       "0             No          No              No      1  Month-to-month   \n",
       "1             No          No              No     34        One year   \n",
       "2             No          No              No      2  Month-to-month   \n",
       "3            Yes          No              No     45        One year   \n",
       "4             No          No              No      2  Month-to-month   \n",
       "...          ...         ...             ...    ...             ...   \n",
       "7038         Yes         Yes             Yes     24        One year   \n",
       "7039          No         Yes             Yes     72        One year   \n",
       "7040          No          No              No     11  Month-to-month   \n",
       "7041          No          No              No      4  Month-to-month   \n",
       "7042         Yes         Yes             Yes     66        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        No  \n",
       "1        No  \n",
       "2       Yes  \n",
       "3        No  \n",
       "4       Yes  \n",
       "...     ...  \n",
       "7038     No  \n",
       "7039     No  \n",
       "7040     No  \n",
       "7041    Yes  \n",
       "7042     No  \n",
       "\n",
       "[7043 rows x 21 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Preencher valores padrão conforme a coluna\n",
    "df_churn.fillna(value={'TotalCharges':0, 'Genero': 'Não Declarado'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</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>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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</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",
       "    <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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</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>No</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>11</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>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</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>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>66</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>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "1     5575-GNVDE    Male           0          No             No          Yes   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "3     7795-CFOCW    Male           0          No             No           No   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7038  6840-RESVB    Male           0         Yes            Yes          Yes   \n",
       "7039  2234-XADUH  Female           0         Yes            Yes          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "7042  3186-AJIEK    Male           0          No             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0     No phone service             DSL             No          Yes  ...   \n",
       "1                   No             DSL            Yes           No  ...   \n",
       "2                   No             DSL            Yes          Yes  ...   \n",
       "3     No phone service             DSL            Yes           No  ...   \n",
       "4                   No     Fiber optic             No           No  ...   \n",
       "...                ...             ...            ...          ...  ...   \n",
       "7038               Yes             DSL            Yes           No  ...   \n",
       "7039               Yes     Fiber optic             No          Yes  ...   \n",
       "7040  No phone service             DSL            Yes           No  ...   \n",
       "7041               Yes     Fiber optic             No           No  ...   \n",
       "7042                No     Fiber optic            Yes           No  ...   \n",
       "\n",
       "     TechSupport StreamingTV StreamingMovies tenure        Contract  \\\n",
       "0             No          No              No      1  Month-to-month   \n",
       "1             No          No              No     34        One year   \n",
       "2             No          No              No      2  Month-to-month   \n",
       "3            Yes          No              No     45        One year   \n",
       "4             No          No              No      2  Month-to-month   \n",
       "...          ...         ...             ...    ...             ...   \n",
       "7038         Yes         Yes             Yes     24        One year   \n",
       "7039          No         Yes             Yes     72        One year   \n",
       "7040          No          No              No     11  Month-to-month   \n",
       "7041          No          No              No      4  Month-to-month   \n",
       "7042         Yes         Yes             Yes     66        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        No  \n",
       "1        No  \n",
       "2       Yes  \n",
       "3        No  \n",
       "4       Yes  \n",
       "...     ...  \n",
       "7038     No  \n",
       "7039     No  \n",
       "7040     No  \n",
       "7041    Yes  \n",
       "7042     No  \n",
       "\n",
       "[7043 rows x 21 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Prencher todos os valores ausentes de uma coluna com a media\n",
    "media_TotalCharges = df_churn.TotalCharges.mean()\n",
    "df_churn.fillna(value={'TotalCharges':media_TotalCharges})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analise Univariada"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- a faixa etaria do cliente tem uma forte associação associada com o churn\n",
    "\n",
    "- Um cliente com menos de 6 meses de contrato é mais propenso ao churn\n",
    "\n",
    "- cliente com contrato mensal é mais pronpenso ao churn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Churn\n",
       "No     5174\n",
       "Yes    1869\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Contar clientes usando a variaval Churn como referencia\n",
    "df_churn.Churn.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Churn\n",
       "No     0.73463\n",
       "Yes    0.26537\n",
       "Name: proportion, dtype: float64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Identificar distribuição usando porcentagem\n",
    "df_churn.Churn.value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['No', 'Yes'], dtype=object)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Como identificar valores possiveis (unicos) numa variavel do dataframe\n",
    "df_churn.Churn.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0, 0, '5174'), Text(0, 0, '1869')]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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l2rVrp+nTp+vSpUtuY7Zv366ePXvK19dXkZGRSk9Pv/EzBAAATU6dAiYsLEwLFixQfn6+vvjiCw0aNEgjRozQoUOHJEnJycnavHmzNmzYoB07dqi4uFgjR4507V9TU6O4uDhVVVVp165dWrt2rdLT0zVnzhzXmMLCQsXFxWngwIEqKCjQtGnTNHHiRGVnZ9fTKQMAANNZnE6n82YOEBQUpNdee02PPfaY2rZtq/Xr1+uxxx6TJB05ckSdO3dWXl6e+vTpo08++US/+c1vVFxcrODgYEnSqlWrNHPmTJ0+fVo+Pj6aOXOmMjMzdfDgQdfPePzxx1VWVqasrKzrnpfD4VBAQIDKy8tltVpv5hSNc/fzmZ6eAhrQtwviPD0FAKg31/v3+4bvgampqdH777+v8+fPy2azKT8/X9XV1YqJiXGN6dSpk9q3b6+8vDxJUl5enrp16+aKF0mKjY2Vw+FwXcXJy8tzO0btmNpj/JjKyko5HA63BQAANE11DpgDBw6odevW8vX11eTJk/XRRx8pKipKdrtdPj4+CgwMdBsfHBwsu90uSbLb7W7xUru9dttPjXE4HLpw4cKPzmv+/PkKCAhwLeHh4XU9NQAAYIg6B8x9992ngoIC7dmzR1OmTNH48eN1+PDhWzG3Opk1a5bKy8tdy8mTJz09JQAAcIt413UHHx8fRUZGSpJ69eqlffv2aenSpRo1apSqqqpUVlbmdhWmpKREISEhkqSQkBDt3bvX7Xi1TyldOeafn1wqKSmR1WqVn5/fj87L19dXvr6+dT0dAABgoJv+HJjLly+rsrJSvXr1UvPmzZWbm+vadvToURUVFclms0mSbDabDhw4oNLSUteYnJwcWa1WRUVFucZceYzaMbXHAAAAqNMVmFmzZmnYsGFq3769zp07p/Xr12v79u3Kzs5WQECAEhISlJKSoqCgIFmtVk2dOlU2m019+vSRJA0ZMkRRUVEaO3asFi5cKLvdrtmzZysxMdF19WTy5Mlavny5ZsyYoaeeekrbtm1TRkaGMjN5sgYAAPygTgFTWlqqcePG6dSpUwoICFB0dLSys7M1ePBgSdKSJUvk5eWl+Ph4VVZWKjY2VitWrHDt36xZM23ZskVTpkyRzWZTq1atNH78eL300kuuMREREcrMzFRycrKWLl2qsLAwrV69WrGxsfV0ygAAwHQ3/TkwjRWfA4PbBZ8DA6ApueWfAwMAAOApBAwAADAOAQMAAIxDwAAAAOMQMAAAwDgEDAAAMA4BAwAAjEPAAAAA4xAwAADAOAQMAAAwDgEDAACMQ8AAAADjEDAAAMA4BAwAADAOAQMAAIxDwAAAAOMQMAAAwDgEDAAAMA4BAwAAjEPAAAAA4xAwAADAOAQMAAAwDgEDAACMQ8AAAADjEDAAAMA4BAwAADAOAQMAAIxDwAAAAOMQMAAAwDgEDAAAMA4BAwAAjEPAAAAA4xAwAADAOAQMAAAwDgEDAACMQ8AAAADjEDAAAMA4BAwAADAOAQMAAIxDwAAAAOMQMAAAwDgEDAAAMA4BAwAAjEPAAAAA4xAwAADAOAQMAAAwDgEDAACMQ8AAAADjEDAAAMA4BAwAADAOAQMAAIxDwAAAAOMQMAAAwDgEDAAAMA4BAwAAjEPAAAAA4xAwAADAOHUKmPnz5+uXv/yl/P391a5dOz3yyCM6evSo25iLFy8qMTFRbdq0UevWrRUfH6+SkhK3MUVFRYqLi1PLli3Vrl07TZ8+XZcuXXIbs337dvXs2VO+vr6KjIxUenr6jZ0hAMDjdu7cqeHDhys0NFQWi0UbN250215RUaGkpCSFhYXJz89PUVFRWrVq1VXHycvL06BBg9SqVStZrVYNGDBAFy5ccG3fv3+/Bg8erMDAQLVp00ZPP/20KioqbvXpwQPqFDA7duxQYmKidu/erZycHFVXV2vIkCE6f/68a0xycrI2b96sDRs2aMeOHSouLtbIkSNd22tqahQXF6eqqirt2rVLa9euVXp6uubMmeMaU1hYqLi4OA0cOFAFBQWaNm2aJk6cqOzs7Ho4ZQBAQzt//ry6d++utLS0a25PSUlRVlaW3n33XX311VeaNm2akpKStGnTJteYvLw8DR06VEOGDNHevXu1b98+JSUlycvrhz9lxcXFiomJUWRkpPbs2aOsrCwdOnRITz75ZEOcIhqYxel0Om9059OnT6tdu3basWOHBgwYoPLycrVt21br16/XY489Jkk6cuSIOnfurLy8PPXp00effPKJfvOb36i4uFjBwcGSpFWrVmnmzJk6ffq0fHx8NHPmTGVmZurgwYOun/X444+rrKxMWVlZ1zU3h8OhgIAAlZeXy2q13ugpGunu5zM9PQU0oG8XxHl6CkCdWCwWffTRR3rkkUdc67p27apRo0bpxRdfdK3r1auXhg0bpt/97neSpD59+mjw4MF6+eWXr3nct956Sy+++KJOnTrlipoDBw4oOjpax44dU2Rk5K07KdSb6/37fVP3wJSXl0uSgoKCJEn5+fmqrq5WTEyMa0ynTp3Uvn175eXlSfqhoLt16+aKF0mKjY2Vw+HQoUOHXGOuPEbtmNpjAACalr59+2rTpk3629/+JqfTqU8//VR//etfNWTIEElSaWmp9uzZo3bt2qlv374KDg7Wr3/9a3322WeuY1RWVsrHx8cVL5Lk5+cnSW7j0DTccMBcvnxZ06ZN0wMPPKCuXbtKkux2u3x8fBQYGOg2Njg4WHa73TXmynip3V677afGOBwOt/c6r1RZWSmHw+G2AADM8OabbyoqKkphYWHy8fHR0KFDlZaWpgEDBkiSvvnmG0lSamqqJk2apKysLPXs2VMPPvigjh07JkkaNGiQ7Ha7XnvtNVVVVekf//iHnn/+eUnSqVOnPHNiuGVuOGASExN18OBBvf/++/U5nxs2f/58BQQEuJbw8HBPTwkAcJ3efPNN7d69W5s2bVJ+fr4WLVqkxMRE/fnPf5b0w780S9IzzzyjCRMm6Be/+IWWLFmi++67T++8844kqUuXLlq7dq0WLVqkli1bKiQkRBEREQoODna7KoOm4Yb+G01KStKWLVv06aefKiwszLU+JCREVVVVKisrcxtfUlKikJAQ15h/fiqp9vXPjbFara7Lgf9s1qxZKi8vdy0nT568kVMDADSwCxcu6IUXXtDixYs1fPhwRUdHKykpSaNGjdLrr78uSbrrrrskSVFRUW77du7cWUVFRa7XTzzxhOx2u/72t7/pzJkzSk1N1enTp9WxY8eGOyE0iDoFjNPpVFJSkj766CNt27ZNERERbtt79eql5s2bKzc317Xu6NGjKioqks1mkyTZbDYdOHBApaWlrjE5OTmyWq2u/2HabDa3Y9SOqT3Gtfj6+spqtbotAIDGr7q6WtXV1VddJWnWrJnrysvdd9+t0NDQqz66469//as6dOhw1TGDg4PVunVrffDBB2rRooUGDx58604AHuFdl8GJiYlav369Pv74Y/n7+7vuWQkICJCfn58CAgKUkJCglJQUBQUFyWq1aurUqbLZbOrTp48kaciQIYqKitLYsWO1cOFC2e12zZ49W4mJifL19ZUkTZ48WcuXL9eMGTP01FNPadu2bcrIyFBmJk/XAICJKioqdPz4cdfrwsJCFRQUKCgoSO3bt9evf/1rTZ8+XX5+furQoYN27NihdevWafHixZJ+eHJp+vTpmjt3rrp3764ePXpo7dq1OnLkiD788EPXcZcvX66+ffuqdevWysnJ0fTp07VgwYKr7s2E+er0GLXFYrnm+jVr1ries7948aKeffZZ/eEPf1BlZaViY2O1YsUK19tDknTixAlNmTJF27dvV6tWrTR+/HgtWLBA3t7/31Pbt29XcnKyDh8+rLCwML344ot1epafx6hxu+Axaphg+/btGjhw4FXrx48fr/T0dNntds2aNUtbt27V2bNn1aFDBz399NNKTk52+9uzYMECpaWl6ezZs+revbsWLlyofv36ubaPGzdOmZmZqqioUKdOnfTcc89p7NixDXKOqB/X+/f7pj4HpjEjYHC7IGAANCUN8jkwAAAAnkDAAAAA49TpJl4AgGfxFvHthbeIfxxXYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgHAIGAAAYh4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgHAIGAAAYh4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgHAIGAAAYh4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgHAIGAAAYh4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgnDoHzM6dOzV8+HCFhobKYrFo48aNbtudTqfmzJmju+66S35+foqJidGxY8fcxpw9e1ZjxoyR1WpVYGCgEhISVFFR4Tbmyy+/VP/+/dWiRQuFh4dr4cKFdT87AADQJNU5YM6fP6/u3bsrLS3tmtsXLlyoZcuWadWqVdqzZ49atWql2NhYXbx40TVmzJgxOnTokHJycrRlyxbt3LlTTz/9tGu7w+HQkCFD1KFDB+Xn5+u1115Tamqq3nrrrRs4RQAA0NR413WHYcOGadiwYdfc5nQ69cYbb2j27NkaMWKEJGndunUKDg7Wxo0b9fjjj+urr75SVlaW9u3bp/vvv1+S9Oabb+qhhx7S66+/rtDQUL333nuqqqrSO++8Ix8fH3Xp0kUFBQVavHixW+gAAIDbU73eA1NYWCi73a6YmBjXuoCAAPXu3Vt5eXmSpLy8PAUGBrriRZJiYmLk5eWlPXv2uMYMGDBAPj4+rjGxsbE6evSo/vGPf9TnlAEAgIHqfAXmp9jtdklScHCw2/rg4GDXNrvdrnbt2rlPwttbQUFBbmMiIiKuOkbttjvuuOOqn11ZWanKykrXa4fDcZNnAwAAGqsm8xTS/PnzFRAQ4FrCw8M9PSUAAHCL1GvAhISESJJKSkrc1peUlLi2hYSEqLS01G37pUuXdPbsWbcx1zrGlT/jn82aNUvl5eWu5eTJkzd/QgAAoFGq14CJiIhQSEiIcnNzXescDof27Nkjm80mSbLZbCorK1N+fr5rzLZt23T58mX17t3bNWbnzp2qrq52jcnJydF99913zbePJMnX11dWq9VtAQAATVOdA6aiokIFBQUqKCiQ9MONuwUFBSoqKpLFYtG0adP0u9/9Tps2bdKBAwc0btw4hYaG6pFHHpEkde7cWUOHDtWkSZO0d+9eff7550pKStLjjz+u0NBQSdITTzwhHx8fJSQk6NChQ/rggw+0dOlSpaSk1NuJAwAAc9X5Jt4vvvhCAwcOdL2ujYrx48crPT1dM2bM0Pnz5/X000+rrKxM/fr1U1ZWllq0aOHa57333lNSUpIefPBBeXl5KT4+XsuWLXNtDwgI0NatW5WYmKhevXrpzjvv1Jw5c3iEGgAASJIsTqfT6elJ3AoOh0MBAQEqLy+/7d5Ouvv5TE9PAQ3o2wVxnp4CGhC/37eX2/H3+3r/fjeZp5AAAMDtg4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgHAIGAAAYh4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgHAIGAAAYh4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgHAIGAAAYh4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgHAIGAAAYh4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGKdRB0xaWpruvvtutWjRQr1799bevXs9PSUAANAINNqA+eCDD5SSkqK5c+dq//796t69u2JjY1VaWurpqQEAAA9rtAGzePFiTZo0SRMmTFBUVJRWrVqlli1b6p133vH01AAAgIc1yoCpqqpSfn6+YmJiXOu8vLwUExOjvLw8D84MAAA0Bt6ensC1/P3vf1dNTY2Cg4Pd1gcHB+vIkSPX3KeyslKVlZWu1+Xl5ZIkh8Nx6ybaSF2u/N7TU0ADuh3/N3474/f79nI7/n7XnrPT6fzJcY0yYG7E/PnzNW/evKvWh4eHe2A2QMMJeMPTMwBwq9zOv9/nzp1TQEDAj25vlAFz5513qlmzZiopKXFbX1JSopCQkGvuM2vWLKWkpLheX758WWfPnlWbNm1ksVhu6XzheQ6HQ+Hh4Tp58qSsVqunpwOgHvH7fXtxOp06d+6cQkNDf3JcowwYHx8f9erVS7m5uXrkkUck/RAkubm5SkpKuuY+vr6+8vX1dVsXGBh4i2eKxsZqtfJ/cEATxe/37eOnrrzUapQBI0kpKSkaP3687r//fv3qV7/SG2+8ofPnz2vChAmenhoAAPCwRhswo0aN0unTpzVnzhzZ7Xb16NFDWVlZV93YCwAAbj+NNmAkKSkp6UffMgKu5Ovrq7lz5171NiIA8/H7jWuxOH/uOSUAAIBGplF+kB0AAMBPIWAAAIBxCBgAAGAcAgYA0KhcuHBB33///1+ZcOLECb3xxhvaunWrB2eFxoaAAQA0KiNGjNC6deskSWVlZerdu7cWLVqkESNGaOXKlR6eHRoLAgZNgtPp/Nkv/gJghv3796t///6SpA8//FDBwcE6ceKE1q1bp2XLlnl4dmgsCBgYbd26derWrZv8/Pzk5+en6Oho/fd//7enpwXgJnz//ffy9/eXJG3dulUjR46Ul5eX+vTpoxMnTnh4dmgsCBgYa/HixZoyZYoeeughZWRkKCMjQ0OHDtXkyZO1ZMkST08PwA2KjIzUxo0bdfLkSWVnZ2vIkCGSpNLSUr4LCS58kB2MFRERoXnz5mncuHFu69euXavU1FQVFhZ6aGYAbsaHH36oJ554QjU1NRo0aJBycnIkSfPnz9fOnTv1ySefeHiGaAwIGBirRYsWOnjwoCIjI93WHzt2TN26ddPFixc9NDMAN8tut+vUqVPq3r27vLx+eLNg7969slqt6tSpk4dnh8aAt5BgrMjISGVkZFy1/oMPPtA999zjgRkBqC8hISHy9/dXTk6OLly4IEn65S9/SbzApVF/mSPwU+bNm6dRo0Zp586deuCBByRJn3/+uXJzc68ZNgDMcObMGf32t7/Vp59+KovFomPHjqljx45KSEjQHXfcoUWLFnl6imgEuAIDY8XHx2vPnj1q06aNNm7cqI0bN+rOO+/U3r179eijj3p6egBuUHJyspo3b66ioiK1bNnStX7UqFHKysry4MzQmHAPDACgUQkJCVF2dra6d+8uf39//eUvf1HHjh31zTffKDo6WhUVFZ6eIhoB3kKCcby8vGSxWH5yjMVi0aVLlxpoRgDq0/nz592uvNQ6e/asfH19PTAjNEYEDIzz0Ucf/ei2vLw8LVu2TJcvX27AGQGoD8XFxQoNDVX//v21bt06vfzyy5J++BeSy5cva+HChRo4cKCHZ4nGgreQ0CQcPXpUzz//vDZv3qwxY8bopZdeUocOHTw9LQB1cMcddygtLU3du3fXoEGD1LNnT23btk0PP/ywDh06pLNnz+rzzz/Xv/7rv3p6qmgEuIkXRisuLtakSZPUrVs3Xbp0SQUFBVq7di3xAhjoP//zP/XMM88oNTVVhw8fVr9+/TRixAidP39eI0eO1P/+7/8SL3DhCgyMVF5erldeeUVvvvmmevTooVdffdX15W8AzFVYWKiEhAQdPnxYb731lh5++GFPTwmNFAED4yxcuFCvvvqqQkJC9Morr2jEiBGenhKAerZ8+XIlJyerc+fO8vZ2v11z//79HpoVGhMCBsbx8vKSn5+fYmJi1KxZsx8d96c//akBZwWgvpw4cUITJkzQwYMH9cwzz1wVMHPnzvXQzNCY8BQSjDNu3LiffYwagJl+//vf69lnn1VMTIwOHTqktm3benpKaKS4AgMAaBSGDh2qvXv36o033rjqW+aBf8YVGABAo1BTU6Mvv/xSYWFhnp4KDMAVGAAAYBw+BwYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAdCoWCwWbdy40dPTANDIETAAGpTdbtfUqVPVsWNH+fr6Kjw8XMOHD1dubq6npwbAIHyQHYAG8+233+qBBx5QYGCgXnvtNXXr1k3V1dXKzs5WYmKijhw5ckt+blVVlXx8fG7JsQF4BldgADSYf//3f5fFYtHevXsVHx+ve++9V126dFFKSop2797tGvf3v/9djz76qFq2bKl77rlHmzZtcm1LT09XYGCg23E3btzo9v1Yqamp6tGjh1avXq2IiAi1aNFC0g9vT61evfpHjw3AHAQMgAZx9uxZZWVlKTExUa1atbpq+5VRMm/ePP32t7/Vl19+qYceekhjxozR2bNn6/Tzjh8/rj/+8Y/605/+pIKCgno9NgDPI2AANIjjx4/L6XSqU6dOPzv2ySef1OjRoxUZGalXXnlFFRUV2rt3b51+XlVVldatW6df/OIXio6OrtdjA/A8AgZAg6jL165dGRytWrWS1WpVaWlpnX5ehw4d1LZt21tybACeR8AAaBD33HOPLBbLdd2o27x5c7fXFotFly9fliR5eXldFUPV1dVXHeNab1P93LEBmIOAAdAggoKCFBsbq7S0NJ0/f/6q7WVlZdd1nLZt2+rcuXNux7jyHhcAtwcCBkCDSUtLU01NjX71q1/pj3/8o44dO6avvvpKy5Ytk81mu65j9O7dWy1bttQLL7ygr7/+WuvXr1d6evqtnTiARoeAAdBgOnbsqP3792vgwIF69tln1bVrVw0ePFi5ublauXLldR0jKChI7777rv7nf/5H3bp10x/+8Aelpqbe2okDaHQszrrcWQcAANAIcAUGAAAYh4ABAADGIWAAAIBxCBgAAGAcAgYAABiHgAEAAMYhYAAAgHEIGAAAYBwCBgAAGIeAAQAAxiFgAACAcQgYAABgnP8DMVgJ5SxVc6wAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot distribuição Churn (quantidade)\n",
    "ax = df_churn.Churn.value_counts().plot.bar()\n",
    "\n",
    "ax.bar_label(ax.containers[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Month-to-month', 'One year', 'Two year'], dtype=object)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quais são os tipos de contrato\n",
    "df_churn.Contract.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0, 0, '3875'), Text(0, 0, '1695'), Text(0, 0, '1473')]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot distribuição Contrato (quantidade)\n",
    "ax = df_churn.Contract.value_counts().plot.bar()\n",
    "\n",
    "ax.bar_label(ax.containers[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Frequency'>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histograma do tempo de contrato\n",
    "df_churn.tenure.plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A variavel tempo de contrato (ternure) não apresenta uma distribuição normal\n",
    "a maioria dos valores se concetram nos extremos, ou seja contratos com poucos meses de ativação e contratos longos, acima dos 65 meses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Frequency'>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histograma do Monthly Charges\n",
    "df_churn.MonthlyCharges.plot.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(32.37114865824223)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Medidas de Posição - Media tempo de contrato\n",
    "df_churn.tenure.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(29.0)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Medidas de Posição - Mediana\n",
    "df_churn.tenure.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "Name: tenure, dtype: int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Medidas de Posição - Moda\n",
    "df_churn.tenure.mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(24.55948102309446)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Medidas de dipersão - desvio Padrão tempo de contrato\n",
    "df_churn.tenure.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(75.86842617906674)"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Medidas de dipersão - Coeficiente de variação\n",
    "df_churn.tenure.std() / df_churn.tenure.mean() * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "613"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quantos Clientes possuem 1 mes de contrato - Filtro\n",
    "len(df_churn[(df_churn.tenure==1)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.70367741019452"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quantos clientes de 1 mes de contrato representam percentualmente\n",
    "len(df_churn[(df_churn.tenure==1)]) / len(df_churn) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1470"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quantos clientes possuem entre 1 e 6 meses de contrato\n",
    "len (df_churn[(df_churn.tenure>=1) & (df_churn.tenure<=6)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tenure\n",
       "1     613\n",
       "72    362\n",
       "2     238\n",
       "3     200\n",
       "4     176\n",
       "     ... \n",
       "28     57\n",
       "39     56\n",
       "44     51\n",
       "36     50\n",
       "0      11\n",
       "Name: tenure, Length: 73, dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_churn.groupby(['tenure'])['tenure'].count().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='tenure'>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_churn.groupby(['tenure'])['tenure'].count().sort_values().plot.barh(figsize = (20, 20))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analise Bivariada"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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>Contract</th>\n",
       "      <th>Month-to-month</th>\n",
       "      <th>One year</th>\n",
       "      <th>Two year</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Churn</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>2220</td>\n",
       "      <td>1307</td>\n",
       "      <td>1647</td>\n",
       "      <td>5174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>1655</td>\n",
       "      <td>166</td>\n",
       "      <td>48</td>\n",
       "      <td>1869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>3875</td>\n",
       "      <td>1473</td>\n",
       "      <td>1695</td>\n",
       "      <td>7043</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Contract  Month-to-month  One year  Two year   All\n",
       "Churn                                             \n",
       "No                  2220      1307      1647  5174\n",
       "Yes                 1655       166        48  1869\n",
       "All                 3875      1473      1695  7043"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Hipotese: Clientes com contrato do tipo mensal são mais propensos ao churn\n",
    "# Construir tabela de contigencia entre tipo de contrato e churn\n",
    "\n",
    "pd.crosstab(df_churn.Churn, df_churn.Contract, margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "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>Contract</th>\n",
       "      <th>Month-to-month</th>\n",
       "      <th>One year</th>\n",
       "      <th>Two year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Churn</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>0.429068</td>\n",
       "      <td>0.252609</td>\n",
       "      <td>0.318322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>0.885500</td>\n",
       "      <td>0.088818</td>\n",
       "      <td>0.025682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>0.550192</td>\n",
       "      <td>0.209144</td>\n",
       "      <td>0.240664</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Contract  Month-to-month  One year  Two year\n",
       "Churn                                       \n",
       "No              0.429068  0.252609  0.318322\n",
       "Yes             0.885500  0.088818  0.025682\n",
       "All             0.550192  0.209144  0.240664"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Contruir Tabela de Contigencia entre Tipo de Contrato e Churn - proporção\n",
    "pd.crosstab(df_churn.Churn, df_churn.Contract, margins=True, normalize='index')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Considerando o publico total, os clientes de contrato mensal representam 55%. porem se consideramos apenas os clientes que abandonaram o serviço, 88% tinham contrato mensal mes.\n",
    "Desta forma, podemos afirmar que há uma correlação entre i tipo de contrato mensal e de abandono"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "# avaliar correlação entre duas variaveis categoricas\n",
    "\n",
    "# Teste de hipotese chamado chi-square ou qui-quadrado de pearson\n",
    "# num teste de hipotese, duas hipoteses são formuladas:\n",
    "# H0 (hipotese nula): as duas variaveis são idependentes\n",
    "# h1 (hipotese complementar): as duas não são idependentes\n",
    "\n",
    "# o teste confirma ou recusa a hipotese nula\n",
    "#  quando a probabilidade de observarmos h0 é inferior a 0.05 (p-value) recusamos a hipotese nula\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df da crosstab (sem totais)\n",
    "df_crosstab_churn_contract = pd.crosstab(df_churn.Churn, df_churn.Contract)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calcular os scores e p-values\n",
    "from scipy.stats import chi2\n",
    "from scipy.stats import chi2_contingency\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tupla = Lista imutavel\n",
    "chi_scores_churn_contract = chi2_contingency(df_crosstab_churn_contract)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Chi2ContingencyResult(statistic=np.float64(1184.5965720837926), pvalue=np.float64(5.863038300673391e-258), dof=2, expected_freq=array([[2846.69175067, 1082.11018032, 1245.198069  ],\n",
       "       [1028.30824933,  390.88981968,  449.801931  ]]))"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chi_scores_churn_contract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores_churn_contract = pd.Series(chi_scores_churn_contract[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "pvalues_churn_contract = pd.Series(chi_scores_churn_contract[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "# apresentar numeros com decimais sem a notação cientifica\n",
    "pd.set_option('display.float_format', lambda x: '%.15f' %x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Criar dataframe com os resultados\n",
    "df_chi_scores_churn_contract = pd.DataFrame({'qui2': scores_churn_contract, 'p_value': pvalues_churn_contract})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "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>qui2</th>\n",
       "      <th>p_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1184.596572083792580</td>\n",
       "      <td>0.000000000000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  qui2           p_value\n",
       "0 1184.596572083792580 0.000000000000000"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_chi_scores_churn_contract"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conforme Teste estatistico (chi square), o pvalue <= 0.05, desta forma rejeitamos a hipotese nula, ou seja as variaveis não são idependentes. pelo qui2 alto, podemos afirmar que há uma forte correlação"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Avaliar a correlação entre uma variaval qualitativa q quantitativa\n",
    "# Usar o mesmo teste de chi-square, mas transformar a variavel quantitativa em qualitativa\n",
    "# hipotese cliente com menos de 6 meses de contrato é mais propenso ao churn\n",
    "\n",
    "# criar uma coluna nova no DataFrame com base numa condição de outra coluna\n",
    "# coluna = 'TempoMenor6Meses'\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "# criar coluna nova\n",
    "df_churn['TempoMenor6Meses'] = np.where(df_churn.tenure<6, 'Yes', 'no')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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>TempoMenor6Meses</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.950000000000003</td>\n",
       "      <td>1889.500000000000000</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.850000000000001</td>\n",
       "      <td>108.150000000000006</td>\n",
       "      <td>Yes</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.299999999999997</td>\n",
       "      <td>1840.750000000000000</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.700000000000003</td>\n",
       "      <td>151.650000000000006</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0  7590-VHVEG  Female           0         Yes             No           No   \n",
       "1  5575-GNVDE    Male           0          No             No          Yes   \n",
       "2  3668-QPYBK    Male           0          No             No          Yes   \n",
       "3  7795-CFOCW    Male           0          No             No           No   \n",
       "4  9237-HQITU  Female           0          No             No          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0  No phone service             DSL             No          Yes  ...   \n",
       "1                No             DSL            Yes           No  ...   \n",
       "2                No             DSL            Yes          Yes  ...   \n",
       "3  No phone service             DSL            Yes           No  ...   \n",
       "4                No     Fiber optic             No           No  ...   \n",
       "\n",
       "  StreamingTV StreamingMovies tenure        Contract  PaperlessBilling  \\\n",
       "0          No              No      1  Month-to-month               Yes   \n",
       "1          No              No     34        One year                No   \n",
       "2          No              No      2  Month-to-month               Yes   \n",
       "3          No              No     45        One year                No   \n",
       "4          No              No      2  Month-to-month               Yes   \n",
       "\n",
       "               PaymentMethod     MonthlyCharges         TotalCharges  Churn  \\\n",
       "0           Electronic check 29.850000000000001   29.850000000000001     No   \n",
       "1               Mailed check 56.950000000000003 1889.500000000000000     No   \n",
       "2               Mailed check 53.850000000000001  108.150000000000006    Yes   \n",
       "3  Bank transfer (automatic) 42.299999999999997 1840.750000000000000     No   \n",
       "4           Electronic check 70.700000000000003  151.650000000000006    Yes   \n",
       "\n",
       "   TempoMenor6Meses  \n",
       "0               Yes  \n",
       "1                no  \n",
       "2               Yes  \n",
       "3                no  \n",
       "4               Yes  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_churn.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "df_crosstab_churn_tenure = pd.crosstab(df_churn.Churn, df_churn.TempoMenor6Meses)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "#calcular os scores\n",
    "chi_scores_churn_tenure = chi2_contingency(df_crosstab_churn_tenure)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores_churn_tenure = pd.Series(chi_scores_churn_tenure[0])\n",
    "pvalues_churn_tenure = pd.Series(chi_scores_churn_tenure[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>Qui2</th>\n",
       "      <th>p-value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>669.721615828710355</td>\n",
       "      <td>0.000000000000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Qui2           p-value\n",
       "0 669.721615828710355 0.000000000000000"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_chi_scores_churn_tenure = pd.DataFrame({'Qui2': scores_churn_tenure, 'p-value':pvalues_churn_tenure})\n",
    "df_chi_scores_churn_tenure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Como o p-value <= 0.5, rejeitamos a h0, ou seja as variaveis não são idependentes\n",
    "- a correlação entre churn e tempo de contrato <6 meses é menor que a correlação entre churn e tipo de contrato."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.825880460933202)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Correlação de duas variaveis numericas\n",
    "# quanto mais tempo de contrato, maior o valor pago\n",
    "\n",
    "# Correlação entre duas varveis numerias - pearson\n",
    "df_churn.tenure.corr(df_churn.TotalCharges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.8891770805365491)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Correlação de duas variaveis numericas\n",
    "# quanto mais tempo de contrato, maior o valor pago\n",
    "\n",
    "# Correlação entre duas varveis numerias - sparmen\n",
    "df_churn.tenure.corr(df_churn.TotalCharges, method='spearman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='tenure', ylabel='TotalCharges'>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot scatter entre tenure e total charges\n",
    "# grafico de dispersão\n",
    "df_churn.plot.scatter(x='tenure', y='TotalCharges')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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>TempoMenor6Meses</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.950000000000003</td>\n",
       "      <td>1889.500000000000000</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.850000000000001</td>\n",
       "      <td>108.150000000000006</td>\n",
       "      <td>Yes</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.299999999999997</td>\n",
       "      <td>1840.750000000000000</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.700000000000003</td>\n",
       "      <td>151.650000000000006</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0  7590-VHVEG  Female           0         Yes             No           No   \n",
       "1  5575-GNVDE    Male           0          No             No          Yes   \n",
       "2  3668-QPYBK    Male           0          No             No          Yes   \n",
       "3  7795-CFOCW    Male           0          No             No           No   \n",
       "4  9237-HQITU  Female           0          No             No          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0  No phone service             DSL             No          Yes  ...   \n",
       "1                No             DSL            Yes           No  ...   \n",
       "2                No             DSL            Yes          Yes  ...   \n",
       "3  No phone service             DSL            Yes           No  ...   \n",
       "4                No     Fiber optic             No           No  ...   \n",
       "\n",
       "  StreamingTV StreamingMovies tenure        Contract  PaperlessBilling  \\\n",
       "0          No              No      1  Month-to-month               Yes   \n",
       "1          No              No     34        One year                No   \n",
       "2          No              No      2  Month-to-month               Yes   \n",
       "3          No              No     45        One year                No   \n",
       "4          No              No      2  Month-to-month               Yes   \n",
       "\n",
       "               PaymentMethod     MonthlyCharges         TotalCharges  Churn  \\\n",
       "0           Electronic check 29.850000000000001   29.850000000000001     No   \n",
       "1               Mailed check 56.950000000000003 1889.500000000000000     No   \n",
       "2               Mailed check 53.850000000000001  108.150000000000006    Yes   \n",
       "3  Bank transfer (automatic) 42.299999999999997 1840.750000000000000     No   \n",
       "4           Electronic check 70.700000000000003  151.650000000000006    Yes   \n",
       "\n",
       "   TempoMenor6Meses  \n",
       "0               Yes  \n",
       "1                no  \n",
       "2               Yes  \n",
       "3                no  \n",
       "4               Yes  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Validar se a faixa etaria do cliente tem uma forte associação com churn\n",
    "df_churn.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Churn         No   Yes\n",
      "Mais65anos            \n",
      "0           4508  1393\n",
      "1            666   476\n"
     ]
    }
   ],
   "source": [
    "# avaliar correlação entre duas variaveis categoricas\n",
    "\n",
    "# Teste de hipotese chamado chi-square ou qui-quadrado de pearson\n",
    "# num teste de hipotese, duas hipoteses são formuladas:\n",
    "# H0 (hipotese nula): as duas variaveis são idependentes\n",
    "# h1 (hipotese complementar): as duas não são idependentes\n",
    "\n",
    "# o teste confirma ou recusa a hipotese nula\n",
    "#  quando a probabilidade de observarmos h0 é inferior a 0.05 (p-value) recusamos a hipotese nula\n",
    "# a faixa etaria do cliente tem associação com churn?\n",
    "\n",
    "# Criando a tabela de contingência \n",
    "tabela_contingencia = pd.crosstab(df_churn['Mais65anos'], df_churn['Churn'])\n",
    "\n",
    "print(tabela_contingencia)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Qui-quadrado: 159.42630036838742\n",
      "Valor-p: 1.510066805092378e-36\n"
     ]
    }
   ],
   "source": [
    "chi2, p, dof, expected = chi2_contingency(tabela_contingencia)\n",
    "\n",
    "print(f\"Qui-quadrado: {chi2}\")\n",
    "print(f\"Valor-p: {p}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O valor-p (p-value) é 1.51e-36, ou seja, quase zero, muito menor que 0.05.\n",
    "\n",
    "Isso significa que há uma associação estatisticamente significativa entre idade acima de 65 anos e churn. Em outras palavras, a idade do cliente influencia o churn de forma relevante."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Churn             No   Yes\n",
      "Contract                  \n",
      "Month-to-month  2220  1655\n",
      "One year        1307   166\n",
      "Two year        1647    48\n"
     ]
    }
   ],
   "source": [
    "# o tipo de contrato influencia?\n",
    "# Criando a tabela de contingência \n",
    "tabela_contingencia = pd.crosstab(df_churn['Contract'], df_churn['Churn'])\n",
    "\n",
    "print(tabela_contingencia)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Qui-quadrado: 1184.5965720837926\n",
      "Valor-p: 5.863038300673391e-258\n"
     ]
    }
   ],
   "source": [
    "chi2, p, dof, expected = chi2_contingency(tabela_contingencia)\n",
    "\n",
    "print(f\"Qui-quadrado: {chi2}\")\n",
    "print(f\"Valor-p: {p}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Re-Teste "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "# avaliar correlação entre duas variaveis categoricas\n",
    "# a idade influencia no churn?\n",
    "# df da crosstab (sem totais)\n",
    "df_crosstab_churn_Mais65anos = pd.crosstab(df_churn.Churn, df_churn.Mais65anos)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Chi2ContingencyResult(statistic=np.float64(1184.5965720837926), pvalue=np.float64(5.863038300673391e-258), dof=2, expected_freq=array([[2846.69175067, 1082.11018032, 1245.198069  ],\n",
       "       [1028.30824933,  390.88981968,  449.801931  ]]))"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Tupla = Lista imutavel\n",
    "chi_scores_churn_Mais65anos = chi2_contingency(df_crosstab_churn_Mais65anos)\n",
    "chi_scores_churn_contract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores_churn_Mais65anos= pd.Series(chi_scores_churn_Mais65anos[0])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "pvalues_churn_Mais65anos = pd.Series(chi_scores_churn_Mais65anos[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Criar dataframe com os resultados\n",
    "df_chi_scores_churn_Mais65anos = pd.DataFrame({'qui2': scores_churn_Mais65anos, 'p_value': pvalues_churn_Mais65anos})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "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>qui2</th>\n",
       "      <th>p_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>159.426300368387416</td>\n",
       "      <td>0.000000000000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 qui2           p_value\n",
       "0 159.426300368387416 0.000000000000000"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_chi_scores_churn_Mais65anos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conforme Teste estatistico (chi square), o pvalue <= 0.05, desta forma rejeitamos a hipotese nula, ou seja as variaveis não são idependentes. pelo qui2 alto, podemos afirmar que há uma forte correlação"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Month-to-month influencia no cancelamento do contrato?\n",
    "# Contract -> qualitativa\n",
    "# tenure -> qualitativa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "# criar coluna nova\n",
    "df_churn['MesAmes'] = np.where(df_churn.Contract=='Month-to-month', 'Yes', 'no')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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>TempoMenor6Meses</th>\n",
       "      <th>MesAmes</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.950000000000003</td>\n",
       "      <td>1889.500000000000000</td>\n",
       "      <td>No</td>\n",
       "      <td>no</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.850000000000001</td>\n",
       "      <td>108.150000000000006</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.299999999999997</td>\n",
       "      <td>1840.750000000000000</td>\n",
       "      <td>No</td>\n",
       "      <td>no</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.700000000000003</td>\n",
       "      <td>151.650000000000006</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0  7590-VHVEG  Female           0         Yes             No           No   \n",
       "1  5575-GNVDE    Male           0          No             No          Yes   \n",
       "2  3668-QPYBK    Male           0          No             No          Yes   \n",
       "3  7795-CFOCW    Male           0          No             No           No   \n",
       "4  9237-HQITU  Female           0          No             No          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0  No phone service             DSL             No          Yes  ...   \n",
       "1                No             DSL            Yes           No  ...   \n",
       "2                No             DSL            Yes          Yes  ...   \n",
       "3  No phone service             DSL            Yes           No  ...   \n",
       "4                No     Fiber optic             No           No  ...   \n",
       "\n",
       "  StreamingMovies tenure        Contract PaperlessBilling  \\\n",
       "0              No      1  Month-to-month              Yes   \n",
       "1              No     34        One year               No   \n",
       "2              No      2  Month-to-month              Yes   \n",
       "3              No     45        One year               No   \n",
       "4              No      2  Month-to-month              Yes   \n",
       "\n",
       "               PaymentMethod     MonthlyCharges         TotalCharges Churn  \\\n",
       "0           Electronic check 29.850000000000001   29.850000000000001    No   \n",
       "1               Mailed check 56.950000000000003 1889.500000000000000    No   \n",
       "2               Mailed check 53.850000000000001  108.150000000000006   Yes   \n",
       "3  Bank transfer (automatic) 42.299999999999997 1840.750000000000000    No   \n",
       "4           Electronic check 70.700000000000003  151.650000000000006   Yes   \n",
       "\n",
       "   TempoMenor6Meses  MesAmes  \n",
       "0               Yes      Yes  \n",
       "1                no       no  \n",
       "2               Yes      Yes  \n",
       "3                no       no  \n",
       "4               Yes      Yes  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_churn.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_crosstab_churn_MesAmes = pd.crosstab(df_churn.Churn, df_churn.MesAmes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "#calcular os scores\n",
    "chi_scores_churn_MesAmes = chi2_contingency(df_crosstab_churn_MesAmes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores_churn_MesAmes = pd.Series(chi_scores_churn_MesAmes[0])\n",
    "pvalues_churn_MesAmes = pd.Series(chi_scores_churn_MesAmes[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "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>Qui2</th>\n",
       "      <th>p-value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1153.971661109347679</td>\n",
       "      <td>0.000000000000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Qui2           p-value\n",
       "0 1153.971661109347679 0.000000000000000"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_chi_scores_churn_MesAmes = pd.DataFrame({'Qui2': scores_churn_MesAmes, 'p-value':pvalues_churn_MesAmes})\n",
    "df_chi_scores_churn_MesAmes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Como o p-value <= 0.5, rejeitamos a h0, ou seja as variaveis não são idependentes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Detecção de Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 23 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   IDCliente         7043 non-null   object \n",
      " 1   Genero            7043 non-null   object \n",
      " 2   Mais65anos        7043 non-null   int64  \n",
      " 3   TemParceiro       7043 non-null   object \n",
      " 4   TemDependentes    7043 non-null   object \n",
      " 5   PhoneService      7043 non-null   object \n",
      " 6   MultipleLines     7043 non-null   object \n",
      " 7   InternetService   7043 non-null   object \n",
      " 8   OnlineSecurity    7043 non-null   object \n",
      " 9   OnlineBackup      7043 non-null   object \n",
      " 10  DeviceProtection  7043 non-null   object \n",
      " 11  TechSupport       7043 non-null   object \n",
      " 12  StreamingTV       7043 non-null   object \n",
      " 13  StreamingMovies   7043 non-null   object \n",
      " 14  tenure            7043 non-null   int64  \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      7032 non-null   float64\n",
      " 20  Churn             7043 non-null   object \n",
      " 21  TempoMenor6Meses  7043 non-null   object \n",
      " 22  MesAmes           7043 non-null   object \n",
      "dtypes: float64(2), int64(2), object(19)\n",
      "memory usage: 1.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df_churn.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 7032 entries, 0 to 7042\n",
      "Data columns (total 23 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   IDCliente         7032 non-null   object \n",
      " 1   Genero            7032 non-null   object \n",
      " 2   Mais65anos        7032 non-null   int64  \n",
      " 3   TemParceiro       7032 non-null   object \n",
      " 4   TemDependentes    7032 non-null   object \n",
      " 5   PhoneService      7032 non-null   object \n",
      " 6   MultipleLines     7032 non-null   object \n",
      " 7   InternetService   7032 non-null   object \n",
      " 8   OnlineSecurity    7032 non-null   object \n",
      " 9   OnlineBackup      7032 non-null   object \n",
      " 10  DeviceProtection  7032 non-null   object \n",
      " 11  TechSupport       7032 non-null   object \n",
      " 12  StreamingTV       7032 non-null   object \n",
      " 13  StreamingMovies   7032 non-null   object \n",
      " 14  tenure            7032 non-null   int64  \n",
      " 15  Contract          7032 non-null   object \n",
      " 16  PaperlessBilling  7032 non-null   object \n",
      " 17  PaymentMethod     7032 non-null   object \n",
      " 18  MonthlyCharges    7032 non-null   float64\n",
      " 19  TotalCharges      7032 non-null   float64\n",
      " 20  Churn             7032 non-null   object \n",
      " 21  TempoMenor6Meses  7032 non-null   object \n",
      " 22  MesAmes           7032 non-null   object \n",
      "dtypes: float64(2), int64(2), object(19)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "# Remover Linhas com valores nulos\n",
    "\n",
    "df_churn.dropna(axis=0, inplace=True)\n",
    "df_churn.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Box Plot geral\n",
    "df_churn['TotalCharges'].plot.box()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TotalCharges    Axes(0.125,0.11;0.775x0.77)\n",
       "dtype: object"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Box plot agrupado por contract\n",
    "df_churn.plot.box(column='TotalCharges', by='Contract')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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>TempoMenor6Meses</th>\n",
       "      <th>MesAmes</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.850000000000001</td>\n",
       "      <td>108.150000000000006</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.700000000000003</td>\n",
       "      <td>151.650000000000006</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9305-CDSKC</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>8</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>99.650000000000006</td>\n",
       "      <td>820.500000000000000</td>\n",
       "      <td>Yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1452-KIOVK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>22</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>89.099999999999994</td>\n",
       "      <td>1949.400000000000091</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</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>7033</th>\n",
       "      <td>9767-FFLEM</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>38</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>69.500000000000000</td>\n",
       "      <td>2625.250000000000000</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7034</th>\n",
       "      <td>0639-TSIQW</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>67</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>102.950000000000003</td>\n",
       "      <td>6886.250000000000000</td>\n",
       "      <td>Yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7035</th>\n",
       "      <td>8456-QDAVC</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>19</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>78.700000000000003</td>\n",
       "      <td>1495.099999999999909</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>11</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.600000000000001</td>\n",
       "      <td>346.449999999999989</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.400000000000006</td>\n",
       "      <td>306.600000000000023</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3875 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "5     9305-CDSKC  Female           0          No             No          Yes   \n",
       "6     1452-KIOVK    Male           0          No            Yes          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7033  9767-FFLEM    Male           0          No             No          Yes   \n",
       "7034  0639-TSIQW  Female           0          No             No          Yes   \n",
       "7035  8456-QDAVC    Male           0          No             No          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0     No phone service             DSL             No          Yes  ...   \n",
       "2                   No             DSL            Yes          Yes  ...   \n",
       "4                   No     Fiber optic             No           No  ...   \n",
       "5                  Yes     Fiber optic             No           No  ...   \n",
       "6                  Yes     Fiber optic             No          Yes  ...   \n",
       "...                ...             ...            ...          ...  ...   \n",
       "7033                No     Fiber optic             No           No  ...   \n",
       "7034               Yes     Fiber optic            Yes          Yes  ...   \n",
       "7035                No     Fiber optic             No           No  ...   \n",
       "7040  No phone service             DSL            Yes           No  ...   \n",
       "7041               Yes     Fiber optic             No           No  ...   \n",
       "\n",
       "     StreamingMovies tenure        Contract PaperlessBilling  \\\n",
       "0                 No      1  Month-to-month              Yes   \n",
       "2                 No      2  Month-to-month              Yes   \n",
       "4                 No      2  Month-to-month              Yes   \n",
       "5                Yes      8  Month-to-month              Yes   \n",
       "6                 No     22  Month-to-month              Yes   \n",
       "...              ...    ...             ...              ...   \n",
       "7033              No     38  Month-to-month              Yes   \n",
       "7034              No     67  Month-to-month              Yes   \n",
       "7035              No     19  Month-to-month              Yes   \n",
       "7040              No     11  Month-to-month              Yes   \n",
       "7041              No      4  Month-to-month              Yes   \n",
       "\n",
       "                  PaymentMethod      MonthlyCharges         TotalCharges  \\\n",
       "0              Electronic check  29.850000000000001   29.850000000000001   \n",
       "2                  Mailed check  53.850000000000001  108.150000000000006   \n",
       "4              Electronic check  70.700000000000003  151.650000000000006   \n",
       "5              Electronic check  99.650000000000006  820.500000000000000   \n",
       "6       Credit card (automatic)  89.099999999999994 1949.400000000000091   \n",
       "...                         ...                 ...                  ...   \n",
       "7033    Credit card (automatic)  69.500000000000000 2625.250000000000000   \n",
       "7034    Credit card (automatic) 102.950000000000003 6886.250000000000000   \n",
       "7035  Bank transfer (automatic)  78.700000000000003 1495.099999999999909   \n",
       "7040           Electronic check  29.600000000000001  346.449999999999989   \n",
       "7041               Mailed check  74.400000000000006  306.600000000000023   \n",
       "\n",
       "     Churn  TempoMenor6Meses  MesAmes  \n",
       "0       No               Yes      Yes  \n",
       "2      Yes               Yes      Yes  \n",
       "4      Yes               Yes      Yes  \n",
       "5      Yes                no      Yes  \n",
       "6       No                no      Yes  \n",
       "...    ...               ...      ...  \n",
       "7033    No                no      Yes  \n",
       "7034   Yes                no      Yes  \n",
       "7035    No                no      Yes  \n",
       "7040    No                no      Yes  \n",
       "7041   Yes               Yes      Yes  \n",
       "\n",
       "[3875 rows x 23 columns]"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_churn_month = df_churn[df_churn.Contract =='Month-to-month']\n",
    "df_churn_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Frequency'>"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_churn_month.TotalCharges.plot.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(1906.4)"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Metodo de Tukey - IQR (DISTRIBUIÇÃO NÃO NORMMAL)]\n",
    "# IQR - Range Interquartil\n",
    "# IQR = 3o quartil - 1o Quartil\n",
    "q1_TotalCharges_month = df_churn_month.TotalCharges.quantile(0.25)\n",
    "q3_TotalCharges_month = df_churn_month.TotalCharges.quantile(0.75)\n",
    "iqr_TotalCharges_month = q3_TotalCharges_month - q1_TotalCharges_month\n",
    "iqr_TotalCharges_month\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(np.float64(-2699.5000000000005), np.float64(4926.1))"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "limInf_TotalCharges_month = q1_TotalCharges_month - (iqr_TotalCharges_month * 1.5)\n",
    "limSup_TotalCharges_month = q3_TotalCharges_month + (iqr_TotalCharges_month * 1.5)\n",
    "limInf_TotalCharges_month, limSup_TotalCharges_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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>TempoMenor6Meses</th>\n",
       "      <th>MesAmes</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>29.850000000000001</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.850000000000001</td>\n",
       "      <td>108.150000000000006</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.700000000000003</td>\n",
       "      <td>151.650000000000006</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9305-CDSKC</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>8</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>99.650000000000006</td>\n",
       "      <td>820.500000000000000</td>\n",
       "      <td>Yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1452-KIOVK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>22</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>89.099999999999994</td>\n",
       "      <td>1949.400000000000091</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</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>7033</th>\n",
       "      <td>9767-FFLEM</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>38</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>69.500000000000000</td>\n",
       "      <td>2625.250000000000000</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7034</th>\n",
       "      <td>0639-TSIQW</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>67</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>102.950000000000003</td>\n",
       "      <td>6886.250000000000000</td>\n",
       "      <td>Yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7035</th>\n",
       "      <td>8456-QDAVC</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>19</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>78.700000000000003</td>\n",
       "      <td>1495.099999999999909</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</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>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>11</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.600000000000001</td>\n",
       "      <td>346.449999999999989</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.400000000000006</td>\n",
       "      <td>306.600000000000023</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3875 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "0     7590-VHVEG  Female           0         Yes             No           No   \n",
       "2     3668-QPYBK    Male           0          No             No          Yes   \n",
       "4     9237-HQITU  Female           0          No             No          Yes   \n",
       "5     9305-CDSKC  Female           0          No             No          Yes   \n",
       "6     1452-KIOVK    Male           0          No            Yes          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "7033  9767-FFLEM    Male           0          No             No          Yes   \n",
       "7034  0639-TSIQW  Female           0          No             No          Yes   \n",
       "7035  8456-QDAVC    Male           0          No             No          Yes   \n",
       "7040  4801-JZAZL  Female           0         Yes            Yes           No   \n",
       "7041  8361-LTMKD    Male           1         Yes             No          Yes   \n",
       "\n",
       "         MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "0     No phone service             DSL             No          Yes  ...   \n",
       "2                   No             DSL            Yes          Yes  ...   \n",
       "4                   No     Fiber optic             No           No  ...   \n",
       "5                  Yes     Fiber optic             No           No  ...   \n",
       "6                  Yes     Fiber optic             No          Yes  ...   \n",
       "...                ...             ...            ...          ...  ...   \n",
       "7033                No     Fiber optic             No           No  ...   \n",
       "7034               Yes     Fiber optic            Yes          Yes  ...   \n",
       "7035                No     Fiber optic             No           No  ...   \n",
       "7040  No phone service             DSL            Yes           No  ...   \n",
       "7041               Yes     Fiber optic             No           No  ...   \n",
       "\n",
       "     StreamingMovies tenure        Contract PaperlessBilling  \\\n",
       "0                 No      1  Month-to-month              Yes   \n",
       "2                 No      2  Month-to-month              Yes   \n",
       "4                 No      2  Month-to-month              Yes   \n",
       "5                Yes      8  Month-to-month              Yes   \n",
       "6                 No     22  Month-to-month              Yes   \n",
       "...              ...    ...             ...              ...   \n",
       "7033              No     38  Month-to-month              Yes   \n",
       "7034              No     67  Month-to-month              Yes   \n",
       "7035              No     19  Month-to-month              Yes   \n",
       "7040              No     11  Month-to-month              Yes   \n",
       "7041              No      4  Month-to-month              Yes   \n",
       "\n",
       "                  PaymentMethod      MonthlyCharges         TotalCharges  \\\n",
       "0              Electronic check  29.850000000000001   29.850000000000001   \n",
       "2                  Mailed check  53.850000000000001  108.150000000000006   \n",
       "4              Electronic check  70.700000000000003  151.650000000000006   \n",
       "5              Electronic check  99.650000000000006  820.500000000000000   \n",
       "6       Credit card (automatic)  89.099999999999994 1949.400000000000091   \n",
       "...                         ...                 ...                  ...   \n",
       "7033    Credit card (automatic)  69.500000000000000 2625.250000000000000   \n",
       "7034    Credit card (automatic) 102.950000000000003 6886.250000000000000   \n",
       "7035  Bank transfer (automatic)  78.700000000000003 1495.099999999999909   \n",
       "7040           Electronic check  29.600000000000001  346.449999999999989   \n",
       "7041               Mailed check  74.400000000000006  306.600000000000023   \n",
       "\n",
       "     Churn  TempoMenor6Meses  MesAmes  \n",
       "0       No               Yes      Yes  \n",
       "2      Yes               Yes      Yes  \n",
       "4      Yes               Yes      Yes  \n",
       "5      Yes                no      Yes  \n",
       "6       No                no      Yes  \n",
       "...    ...               ...      ...  \n",
       "7033    No                no      Yes  \n",
       "7034   Yes                no      Yes  \n",
       "7035    No                no      Yes  \n",
       "7040    No                no      Yes  \n",
       "7041   Yes               Yes      Yes  \n",
       "\n",
       "[3875 rows x 23 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_churn_month[(df_churn_month.TotalCharges < limInf_TotalCharges_month) |\n",
    "               (df_churn_month.TotalCharges > limInf_TotalCharges_month) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ZScore (usado para distribuição normal)\n",
    "# Indica quantos desvios padrões um ponto especifico de dados está distante da média\n",
    "# zscore = (x - média) / desvio padrão\n",
    "from scipy.stats import zscore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = np.abs(zscore(df_churn_month.TotalCharges))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.83003585, 0.78151294, 0.75455577, ..., 0.07798705, 0.63383722,\n",
       "       0.65853247], shape=(3875,))"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "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>IDCliente</th>\n",
       "      <th>Genero</th>\n",
       "      <th>Mais65anos</th>\n",
       "      <th>TemParceiro</th>\n",
       "      <th>TemDependentes</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</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>TempoMenor6Meses</th>\n",
       "      <th>MesAmes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>6067-NGCEU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>65</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>111.049999999999997</td>\n",
       "      <td>7107.000000000000000</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>6168-YBYNP</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>59</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>111.349999999999994</td>\n",
       "      <td>6519.750000000000000</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>1343-EHPYB</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>63</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>103.400000000000006</td>\n",
       "      <td>6603.000000000000000</td>\n",
       "      <td>Yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>0979-PHULV</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>69</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>99.450000000000003</td>\n",
       "      <td>7007.600000000000364</td>\n",
       "      <td>Yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>7752-XUSCI</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>60</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>105.900000000000006</td>\n",
       "      <td>6396.449999999999818</td>\n",
       "      <td>Yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</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>6565</th>\n",
       "      <td>1548-FEHVL</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>61</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>106.200000000000003</td>\n",
       "      <td>6375.199999999999818</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6587</th>\n",
       "      <td>7426-GSWPO</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>64</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>103.500000000000000</td>\n",
       "      <td>6548.649999999999636</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6713</th>\n",
       "      <td>4989-LIXVT</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>68</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>95.900000000000006</td>\n",
       "      <td>6503.199999999999818</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7023</th>\n",
       "      <td>1035-IPQPU</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>63</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>103.500000000000000</td>\n",
       "      <td>6479.399999999999636</td>\n",
       "      <td>No</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7034</th>\n",
       "      <td>0639-TSIQW</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>67</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>102.950000000000003</td>\n",
       "      <td>6886.250000000000000</td>\n",
       "      <td>Yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>65 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDCliente  Genero  Mais65anos TemParceiro TemDependentes PhoneService  \\\n",
       "93    6067-NGCEU  Female           0          No             No          Yes   \n",
       "197   6168-YBYNP    Male           0          No             No          Yes   \n",
       "339   1343-EHPYB    Male           0         Yes             No          Yes   \n",
       "402   0979-PHULV    Male           0         Yes            Yes          Yes   \n",
       "445   7752-XUSCI  Female           0          No             No          Yes   \n",
       "...          ...     ...         ...         ...            ...          ...   \n",
       "6565  1548-FEHVL    Male           0         Yes             No          Yes   \n",
       "6587  7426-GSWPO    Male           1          No             No          Yes   \n",
       "6713  4989-LIXVT    Male           1          No             No          Yes   \n",
       "7023  1035-IPQPU  Female           1         Yes             No          Yes   \n",
       "7034  0639-TSIQW  Female           0          No             No          Yes   \n",
       "\n",
       "     MultipleLines InternetService OnlineSecurity OnlineBackup  ...  \\\n",
       "93             Yes     Fiber optic            Yes          Yes  ...   \n",
       "197            Yes     Fiber optic             No          Yes  ...   \n",
       "339            Yes     Fiber optic             No          Yes  ...   \n",
       "402            Yes     Fiber optic             No           No  ...   \n",
       "445            Yes     Fiber optic             No          Yes  ...   \n",
       "...            ...             ...            ...          ...  ...   \n",
       "6565           Yes     Fiber optic            Yes          Yes  ...   \n",
       "6587           Yes     Fiber optic            Yes          Yes  ...   \n",
       "6713           Yes     Fiber optic             No          Yes  ...   \n",
       "7023           Yes     Fiber optic             No          Yes  ...   \n",
       "7034           Yes     Fiber optic            Yes          Yes  ...   \n",
       "\n",
       "     StreamingMovies tenure        Contract PaperlessBilling  \\\n",
       "93               Yes     65  Month-to-month              Yes   \n",
       "197              Yes     59  Month-to-month              Yes   \n",
       "339              Yes     63  Month-to-month              Yes   \n",
       "402              Yes     69  Month-to-month              Yes   \n",
       "445              Yes     60  Month-to-month              Yes   \n",
       "...              ...    ...             ...              ...   \n",
       "6565             Yes     61  Month-to-month              Yes   \n",
       "6587             Yes     64  Month-to-month              Yes   \n",
       "6713             Yes     68  Month-to-month              Yes   \n",
       "7023             Yes     63  Month-to-month              Yes   \n",
       "7034              No     67  Month-to-month              Yes   \n",
       "\n",
       "                  PaymentMethod      MonthlyCharges         TotalCharges  \\\n",
       "93      Credit card (automatic) 111.049999999999997 7107.000000000000000   \n",
       "197            Electronic check 111.349999999999994 6519.750000000000000   \n",
       "339            Electronic check 103.400000000000006 6603.000000000000000   \n",
       "402     Credit card (automatic)  99.450000000000003 7007.600000000000364   \n",
       "445            Electronic check 105.900000000000006 6396.449999999999818   \n",
       "...                         ...                 ...                  ...   \n",
       "6565           Electronic check 106.200000000000003 6375.199999999999818   \n",
       "6587  Bank transfer (automatic) 103.500000000000000 6548.649999999999636   \n",
       "6713           Electronic check  95.900000000000006 6503.199999999999818   \n",
       "7023           Electronic check 103.500000000000000 6479.399999999999636   \n",
       "7034    Credit card (automatic) 102.950000000000003 6886.250000000000000   \n",
       "\n",
       "     Churn  TempoMenor6Meses  MesAmes  \n",
       "93      No                no      Yes  \n",
       "197     No                no      Yes  \n",
       "339    Yes                no      Yes  \n",
       "402    Yes                no      Yes  \n",
       "445    Yes                no      Yes  \n",
       "...    ...               ...      ...  \n",
       "6565    No                no      Yes  \n",
       "6587    No                no      Yes  \n",
       "6713    No                no      Yes  \n",
       "7023    No                no      Yes  \n",
       "7034   Yes                no      Yes  \n",
       "\n",
       "[65 rows x 23 columns]"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_churn_month[z > 3.0]"
   ]
  }
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