{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f417dc67-8099-4e04-bfdb-3cd8602a72c4",
   "metadata": {},
   "source": [
    "# Praxisbeispiel - Telko Kundenabgang-Vorhersage (Telco Customer Churn Prediction) bei Vertragskunden\n",
    "\n",
    "Die Vorhersage der Kundenabwanderung (bei Vertragssituationen) sagt die Wahrscheinlichkeit voraus, dass Kunden die Produkte oder Dienstleistungen eines Unternehmens kündigen. \n",
    "In den meisten Fällen sind Unternehmen mit Stammkunden oder Kunden im Abonnement bestrebt, ihren Kundenstamm zu erhalten. Daher ist es wichtig, die Kunden zu verfolgen, die ihr Abonnement kündigen, und diejenigen, die den Dienst weiter nutzen. Dieser Ansatz setzt voraus, dass das Unternehmen das Verhalten seiner Kunden kennt und versteht und die Eigenschaften, die zu dem Risiko führen, dass der Kunde das Unternehmen verlässt."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3642390f-8643-48d9-a24d-e556429e3d77",
   "metadata": {},
   "source": [
    "## Szenario\n",
    "\n",
    "Annahme: Wir sind ein Telekommunikations-Unternehmen, das über historische Daten darüber verfügt, wie seine Kunden mit seinen Dienstleistungen interagiert haben. Das Unternehmen möchte wissen, wie hoch die Wahrscheinlichkeit ist, dass Kunden abwandern, damit es gezielte Marketingkampagnen starten kann."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00f525a4-b2bf-4ee8-9d0f-17f952de0eed",
   "metadata": {},
   "source": [
    "## Datensatz\n",
    "\n",
    "Sage Kundenverhalten voraus, um die Kunden zu binden.\n",
    "\n",
    "Ihr könnt alle relevanten Kundendaten analysieren und gezielte Kundenbindungsprogramme entwickeln.\n",
    "\n",
    "https://www.kaggle.com/datasets/blastchar/telco-customer-churn "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8ee77e59-bc5e-49ce-9b96-a735aa3822e3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:51:37.087712Z",
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     "shell.execute_reply.started": "2026-04-09T19:51:37.087701Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "# !{sys.executable} -m pip install kagglehub\n",
    "# !{sys.executable} -m pip install @\n",
    "# !{sys.executable} -m pip install missingno"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3e492ddf-3d00-42f1-ba7e-8781f8ba1752",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:51:37.092323Z",
     "iopub.status.busy": "2026-04-09T19:51:37.092248Z",
     "iopub.status.idle": "2026-04-09T19:51:37.643581Z",
     "shell.execute_reply": "2026-04-09T19:51:37.643072Z",
     "shell.execute_reply.started": "2026-04-09T19:51:37.092316Z"
    }
   },
   "outputs": [],
   "source": [
    "import kagglehub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b58bd575-3ead-42fc-89fd-7f2fa8f86e09",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:51:37.644075Z",
     "iopub.status.busy": "2026-04-09T19:51:37.643928Z",
     "iopub.status.idle": "2026-04-09T19:52:02.914877Z",
     "shell.execute_reply": "2026-04-09T19:52:02.914339Z",
     "shell.execute_reply.started": "2026-04-09T19:51:37.644065Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import missingno as msno\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "import warnings\n",
    "\n",
    "pd.set_option(\"display.max_columns\", None)\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "db7881ec-b4ee-4b1d-8be4-6defa5ba0d44",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:02.915435Z",
     "iopub.status.busy": "2026-04-09T19:52:02.915266Z",
     "iopub.status.idle": "2026-04-09T19:52:10.304992Z",
     "shell.execute_reply": "2026-04-09T19:52:10.304307Z",
     "shell.execute_reply.started": "2026-04-09T19:52:02.915421Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import roc_curve\n",
    "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, confusion_matrix, classification_report\n",
    "\n",
    "# from xgboost import XGBClassifier\n",
    "# from catboost import CatBoostClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "342a585f-0c81-4945-ac31-e3cb18f0e5df",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:10.305569Z",
     "iopub.status.busy": "2026-04-09T19:52:10.305379Z",
     "iopub.status.idle": "2026-04-09T19:52:10.721935Z",
     "shell.execute_reply": "2026-04-09T19:52:10.720414Z",
     "shell.execute_reply.started": "2026-04-09T19:52:10.305560Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Path to files: /Users/veit/.cache/kagglehub/datasets/blastchar/telco-customer-churn/versions/1\n"
     ]
    }
   ],
   "source": [
    "# Download data from Kaggle\n",
    "path = kagglehub.dataset_download(\"blastchar/telco-customer-churn\")\n",
    "\n",
    "print(\"Path to files:\", path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c290009f-1838-445a-b214-eb8177f33f84",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:10.723063Z",
     "iopub.status.busy": "2026-04-09T19:52:10.722791Z",
     "iopub.status.idle": "2026-04-09T19:52:10.727537Z",
     "shell.execute_reply": "2026-04-09T19:52:10.726502Z",
     "shell.execute_reply.started": "2026-04-09T19:52:10.723035Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "~/.cache/kagglehub/datasets/blastchar/telco-customer-churn/versions/1/WA_Fn-UseC_-Telco-Customer-Churn.csv\n"
     ]
    }
   ],
   "source": [
    "path_file = \"~/.cache/kagglehub/datasets/blastchar/telco-customer-churn/versions/1/WA_Fn-UseC_-Telco-Customer-Churn.csv\"\n",
    "print(path_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ca0ade6-ace5-4ef1-9cc9-0f40bd4e1c45",
   "metadata": {},
   "source": [
    "## Datensatz "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ee8380c5-4ae6-4e3c-babc-bd8c77ee0cb4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:10.728788Z",
     "iopub.status.busy": "2026-04-09T19:52:10.728443Z",
     "iopub.status.idle": "2026-04-09T19:52:10.781846Z",
     "shell.execute_reply": "2026-04-09T19:52:10.781261Z",
     "shell.execute_reply.started": "2026-04-09T19:52:10.728759Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
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       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <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",
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       "    <tr>\n",
       "      <th>7038</th>\n",
       "      <td>6840-RESVB</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.5</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>72</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>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>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>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>4</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>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>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>66</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.65</td>\n",
       "      <td>6844.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerID  gender  SeniorCitizen Partner Dependents  tenure  \\\n",
       "0     7590-VHVEG  Female              0     Yes         No       1   \n",
       "1     5575-GNVDE    Male              0      No         No      34   \n",
       "2     3668-QPYBK    Male              0      No         No       2   \n",
       "3     7795-CFOCW    Male              0      No         No      45   \n",
       "4     9237-HQITU  Female              0      No         No       2   \n",
       "...          ...     ...            ...     ...        ...     ...   \n",
       "7038  6840-RESVB    Male              0     Yes        Yes      24   \n",
       "7039  2234-XADUH  Female              0     Yes        Yes      72   \n",
       "7040  4801-JZAZL  Female              0     Yes        Yes      11   \n",
       "7041  8361-LTMKD    Male              1     Yes         No       4   \n",
       "7042  3186-AJIEK    Male              0      No         No      66   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService OnlineSecurity  \\\n",
       "0              No  No phone service             DSL             No   \n",
       "1             Yes                No             DSL            Yes   \n",
       "2             Yes                No             DSL            Yes   \n",
       "3              No  No phone service             DSL            Yes   \n",
       "4             Yes                No     Fiber optic             No   \n",
       "...           ...               ...             ...            ...   \n",
       "7038          Yes               Yes             DSL            Yes   \n",
       "7039          Yes               Yes     Fiber optic             No   \n",
       "7040           No  No phone service             DSL            Yes   \n",
       "7041          Yes               Yes     Fiber optic             No   \n",
       "7042          Yes                No     Fiber optic            Yes   \n",
       "\n",
       "     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   \n",
       "...           ...              ...         ...         ...             ...   \n",
       "7038           No              Yes         Yes         Yes             Yes   \n",
       "7039          Yes              Yes          No         Yes             Yes   \n",
       "7040           No               No          No          No              No   \n",
       "7041           No               No          No          No              No   \n",
       "7042           No              Yes         Yes         Yes             Yes   \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 TotalCharges Churn  \n",
       "0              29.85        29.85    No  \n",
       "1              56.95       1889.5    No  \n",
       "2              53.85       108.15   Yes  \n",
       "3              42.30      1840.75    No  \n",
       "4              70.70       151.65   Yes  \n",
       "...              ...          ...   ...  \n",
       "7038           84.80       1990.5    No  \n",
       "7039          103.20       7362.9    No  \n",
       "7040           29.60       346.45    No  \n",
       "7041           74.40        306.6   Yes  \n",
       "7042          105.65       6844.5    No  \n",
       "\n",
       "[7043 rows x 21 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(path_file)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82bd0ec8-f6ee-49cc-9f01-110dbcf8bef8",
   "metadata": {},
   "source": [
    "Der Datensatz enthält Informationen über:\n",
    "\n",
    "- ob der Kunde innerhalb des letzten Monats gekündigt hat - Spalte \"Churn\"\n",
    "\n",
    "- Dienste, für die sich jeder Kunde angemeldet hat - \"PhoneService\", \"MultipleLines\", \"InternetService\", \"OnlineSecurity\", \"OnlineBackup\", \"DeviceProtection\", \"TechSupport\" sowie \"StreamingTV\" und \"StreamingMovies\". \n",
    "- Informationen zum Kundenkonto - \"tenure\" wie lange der Kunde bereits Kunde ist, \"Contract\" (Vertrag), \"PaperlessBilling\" (papierlose Abrechnung), \"PaymentMethod\" (Zahlungsmethode), \"MonthlyCharges\" (monatliche Gebühren) und \"TotalCharges\" (Gesamtgebühren).\n",
    "- Demografische Informationen über Kunden - \"gender\" (Geschlecht), \"SeniorCitizen\" (Alter) und ob sie \"Partner\" (Partner) und \"Dependents\" (Familienangehörige) haben."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9d3f3647-c960-4044-97d6-a5e26b3dc1ad",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:10.782258Z",
     "iopub.status.busy": "2026-04-09T19:52:10.782167Z",
     "iopub.status.idle": "2026-04-09T19:52:10.788952Z",
     "shell.execute_reply": "2026-04-09T19:52:10.788304Z",
     "shell.execute_reply.started": "2026-04-09T19:52:10.782249Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape:  (7043, 21)\n",
      "\n",
      "<class 'pandas.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 21 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   customerID        7043 non-null   str    \n",
      " 1   gender            7043 non-null   str    \n",
      " 2   SeniorCitizen     7043 non-null   int64  \n",
      " 3   Partner           7043 non-null   str    \n",
      " 4   Dependents        7043 non-null   str    \n",
      " 5   tenure            7043 non-null   int64  \n",
      " 6   PhoneService      7043 non-null   str    \n",
      " 7   MultipleLines     7043 non-null   str    \n",
      " 8   InternetService   7043 non-null   str    \n",
      " 9   OnlineSecurity    7043 non-null   str    \n",
      " 10  OnlineBackup      7043 non-null   str    \n",
      " 11  DeviceProtection  7043 non-null   str    \n",
      " 12  TechSupport       7043 non-null   str    \n",
      " 13  StreamingTV       7043 non-null   str    \n",
      " 14  StreamingMovies   7043 non-null   str    \n",
      " 15  Contract          7043 non-null   str    \n",
      " 16  PaperlessBilling  7043 non-null   str    \n",
      " 17  PaymentMethod     7043 non-null   str    \n",
      " 18  MonthlyCharges    7043 non-null   float64\n",
      " 19  TotalCharges      7043 non-null   str    \n",
      " 20  Churn             7043 non-null   str    \n",
      "dtypes: float64(1), int64(2), str(18)\n",
      "memory usage: 1.9 MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(\"shape: \", df.shape)\n",
    "print()\n",
    "\n",
    "print(df.info())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f15a863d-d81c-42b0-a2fa-298f3db98078",
   "metadata": {},
   "source": [
    "## ACHTUNG!! \n",
    "\n",
    "Wir sehen, dass \"TotalCharges\" hier als object auftaucht, erwarten hier aber einen numerischen Typ.\n",
    "Das muss geändert werden - wir zeigen euch aber erst, was passiert, wenn wir es nicht ändern."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "08303d27-f263-4e16-99cd-22b0766f4374",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:10.789341Z",
     "iopub.status.busy": "2026-04-09T19:52:10.789250Z",
     "iopub.status.idle": "2026-04-09T19:52:10.791775Z",
     "shell.execute_reply": "2026-04-09T19:52:10.791417Z",
     "shell.execute_reply.started": "2026-04-09T19:52:10.789334Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ArrowStringArray>\n",
       "[      'customerID',           'gender',    'SeniorCitizen',\n",
       "          'Partner',       'Dependents',           'tenure',\n",
       "     'PhoneService',    'MultipleLines',  'InternetService',\n",
       "   'OnlineSecurity',     'OnlineBackup', 'DeviceProtection',\n",
       "      'TechSupport',      'StreamingTV',  'StreamingMovies',\n",
       "         'Contract', 'PaperlessBilling',    'PaymentMethod',\n",
       "   'MonthlyCharges',     'TotalCharges',            'Churn']\n",
       "Length: 21, dtype: str"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7a1f6058-0ffe-48c1-b0e4-671bedae2753",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:10.792106Z",
     "iopub.status.busy": "2026-04-09T19:52:10.792031Z",
     "iopub.status.idle": "2026-04-09T19:52:10.794987Z",
     "shell.execute_reply": "2026-04-09T19:52:10.794497Z",
     "shell.execute_reply.started": "2026-04-09T19:52:10.792099Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "customerID              str\n",
       "gender                  str\n",
       "SeniorCitizen         int64\n",
       "Partner                 str\n",
       "Dependents              str\n",
       "tenure                int64\n",
       "PhoneService            str\n",
       "MultipleLines           str\n",
       "InternetService         str\n",
       "OnlineSecurity          str\n",
       "OnlineBackup            str\n",
       "DeviceProtection        str\n",
       "TechSupport             str\n",
       "StreamingTV             str\n",
       "StreamingMovies         str\n",
       "Contract                str\n",
       "PaperlessBilling        str\n",
       "PaymentMethod           str\n",
       "MonthlyCharges      float64\n",
       "TotalCharges            str\n",
       "Churn                   str\n",
       "dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a47a22e5-3042-4307-ad32-c9b2ebd4ca20",
   "metadata": {},
   "source": [
    "## Ermittle fehlende Werte und visualisiere sie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "89f71aec-8a6d-4fbf-b82f-9481472df5a0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:10.795473Z",
     "iopub.status.busy": "2026-04-09T19:52:10.795380Z",
     "iopub.status.idle": "2026-04-09T19:52:10.800182Z",
     "shell.execute_reply": "2026-04-09T19:52:10.799592Z",
     "shell.execute_reply.started": "2026-04-09T19:52:10.795466Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "customerID 0\n",
      "gender 0\n",
      "SeniorCitizen 0\n",
      "Partner 0\n",
      "Dependents 0\n",
      "tenure 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",
      "Contract 0\n",
      "PaperlessBilling 0\n",
      "PaymentMethod 0\n",
      "MonthlyCharges 0\n",
      "TotalCharges 0\n",
      "Churn 0\n"
     ]
    }
   ],
   "source": [
    "## wir kannten schon die isnull() Funktion in pandas\n",
    "\n",
    "for col in df.columns:\n",
    "    print(col, df[col].isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ad2fa925-79a9-452d-9659-03bc9c42a224",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:10.800638Z",
     "iopub.status.busy": "2026-04-09T19:52:10.800546Z",
     "iopub.status.idle": "2026-04-09T19:52:11.256378Z",
     "shell.execute_reply": "2026-04-09T19:52:11.255912Z",
     "shell.execute_reply.started": "2026-04-09T19:52:10.800628Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Zudem könnte man sich die fehlende Werte auch in einer Matrix anzeigen lassen \n",
    "# (nur haben wir hier keine fehlenden Werte)\n",
    "\n",
    "msno.matrix(df);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8662ad7-2893-4301-8c27-2cdf9e156190",
   "metadata": {},
   "source": [
    "## Daten Manipulation / Bereinigung"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3f2fb452-45e3-4f11-9983-4b66da22d973",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.256775Z",
     "iopub.status.busy": "2026-04-09T19:52:11.256690Z",
     "iopub.status.idle": "2026-04-09T19:52:11.264202Z",
     "shell.execute_reply": "2026-04-09T19:52:11.263463Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.256767Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 21 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   customerID        7043 non-null   str    \n",
      " 1   gender            7043 non-null   str    \n",
      " 2   SeniorCitizen     7043 non-null   int64  \n",
      " 3   Partner           7043 non-null   str    \n",
      " 4   Dependents        7043 non-null   str    \n",
      " 5   tenure            7043 non-null   int64  \n",
      " 6   PhoneService      7043 non-null   str    \n",
      " 7   MultipleLines     7043 non-null   str    \n",
      " 8   InternetService   7043 non-null   str    \n",
      " 9   OnlineSecurity    7043 non-null   str    \n",
      " 10  OnlineBackup      7043 non-null   str    \n",
      " 11  DeviceProtection  7043 non-null   str    \n",
      " 12  TechSupport       7043 non-null   str    \n",
      " 13  StreamingTV       7043 non-null   str    \n",
      " 14  StreamingMovies   7043 non-null   str    \n",
      " 15  Contract          7043 non-null   str    \n",
      " 16  PaperlessBilling  7043 non-null   str    \n",
      " 17  PaymentMethod     7043 non-null   str    \n",
      " 18  MonthlyCharges    7043 non-null   float64\n",
      " 19  TotalCharges      7032 non-null   float64\n",
      " 20  Churn             7043 non-null   str    \n",
      "dtypes: float64(2), int64(2), str(17)\n",
      "memory usage: 1.8 MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "df[\"TotalCharges\"] = pd.to_numeric(df.TotalCharges, errors=\"coerce\")\n",
    "# print(df.dtypes)\n",
    "print(df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0ea736b6-c2c0-4a57-bf20-900bd51a5e33",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.264783Z",
     "iopub.status.busy": "2026-04-09T19:52:11.264634Z",
     "iopub.status.idle": "2026-04-09T19:52:11.268952Z",
     "shell.execute_reply": "2026-04-09T19:52:11.268409Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.264775Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "customerID           0\n",
      "gender               0\n",
      "SeniorCitizen        0\n",
      "Partner              0\n",
      "Dependents           0\n",
      "tenure               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",
      "Contract             0\n",
      "PaperlessBilling     0\n",
      "PaymentMethod        0\n",
      "MonthlyCharges       0\n",
      "TotalCharges        11\n",
      "Churn                0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a6c9030a-81c1-4b56-bb32-83260d314af4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.269440Z",
     "iopub.status.busy": "2026-04-09T19:52:11.269307Z",
     "iopub.status.idle": "2026-04-09T19:52:11.393915Z",
     "shell.execute_reply": "2026-04-09T19:52:11.393365Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.269431Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualisierung\n",
    "\n",
    "msno.matrix(df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f851212a-01a2-4e2b-90cd-d91a5e7753d0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.394298Z",
     "iopub.status.busy": "2026-04-09T19:52:11.394221Z",
     "iopub.status.idle": "2026-04-09T19:52:11.406099Z",
     "shell.execute_reply": "2026-04-09T19:52:11.404811Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.394291Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>4472-LVYGI</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>52.55</td>\n",
       "      <td>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>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.25</td>\n",
       "      <td>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>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>80.85</td>\n",
       "      <td>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>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>25.75</td>\n",
       "      <td>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>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>56.05</td>\n",
       "      <td>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>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>19.85</td>\n",
       "      <td>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>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>25.35</td>\n",
       "      <td>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>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>20.00</td>\n",
       "      <td>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>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>19.70</td>\n",
       "      <td>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>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>73.35</td>\n",
       "      <td>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>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>61.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerID  gender  SeniorCitizen Partner Dependents  tenure  \\\n",
       "488   4472-LVYGI  Female              0     Yes        Yes       0   \n",
       "753   3115-CZMZD    Male              0      No        Yes       0   \n",
       "936   5709-LVOEQ  Female              0     Yes        Yes       0   \n",
       "1082  4367-NUYAO    Male              0     Yes        Yes       0   \n",
       "1340  1371-DWPAZ  Female              0     Yes        Yes       0   \n",
       "3331  7644-OMVMY    Male              0     Yes        Yes       0   \n",
       "3826  3213-VVOLG    Male              0     Yes        Yes       0   \n",
       "4380  2520-SGTTA  Female              0     Yes        Yes       0   \n",
       "5218  2923-ARZLG    Male              0     Yes        Yes       0   \n",
       "6670  4075-WKNIU  Female              0     Yes        Yes       0   \n",
       "6754  2775-SEFEE    Male              0      No        Yes       0   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService       OnlineSecurity  \\\n",
       "488            No  No phone service             DSL                  Yes   \n",
       "753           Yes                No              No  No internet service   \n",
       "936           Yes                No             DSL                  Yes   \n",
       "1082          Yes               Yes              No  No internet service   \n",
       "1340           No  No phone service             DSL                  Yes   \n",
       "3331          Yes                No              No  No internet service   \n",
       "3826          Yes               Yes              No  No internet service   \n",
       "4380          Yes                No              No  No internet service   \n",
       "5218          Yes                No              No  No internet service   \n",
       "6670          Yes               Yes             DSL                   No   \n",
       "6754          Yes               Yes             DSL                  Yes   \n",
       "\n",
       "             OnlineBackup     DeviceProtection          TechSupport  \\\n",
       "488                    No                  Yes                  Yes   \n",
       "753   No internet service  No internet service  No internet service   \n",
       "936                   Yes                  Yes                   No   \n",
       "1082  No internet service  No internet service  No internet service   \n",
       "1340                  Yes                  Yes                  Yes   \n",
       "3331  No internet service  No internet service  No internet service   \n",
       "3826  No internet service  No internet service  No internet service   \n",
       "4380  No internet service  No internet service  No internet service   \n",
       "5218  No internet service  No internet service  No internet service   \n",
       "6670                  Yes                  Yes                  Yes   \n",
       "6754                  Yes                   No                  Yes   \n",
       "\n",
       "              StreamingTV      StreamingMovies  Contract PaperlessBilling  \\\n",
       "488                   Yes                   No  Two year              Yes   \n",
       "753   No internet service  No internet service  Two year               No   \n",
       "936                   Yes                  Yes  Two year               No   \n",
       "1082  No internet service  No internet service  Two year               No   \n",
       "1340                  Yes                   No  Two year               No   \n",
       "3331  No internet service  No internet service  Two year               No   \n",
       "3826  No internet service  No internet service  Two year               No   \n",
       "4380  No internet service  No internet service  Two year               No   \n",
       "5218  No internet service  No internet service  One year              Yes   \n",
       "6670                  Yes                   No  Two year               No   \n",
       "6754                   No                   No  Two year              Yes   \n",
       "\n",
       "                  PaymentMethod  MonthlyCharges  TotalCharges Churn  \n",
       "488   Bank transfer (automatic)           52.55           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  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[np.isnan(df[\"TotalCharges\"])]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90c9639f-4291-4ef0-8cdd-5d28a20809de",
   "metadata": {},
   "source": [
    "Wir beobachten, dass die Spalte \"tenure\" 0 ist bei diesen Einträgen, wo \"TotalCharges\" NaN ist, obwohl die Spalte MonthlyCharges nicht leer ist.\n",
    "\n",
    "Lass uns die Spalte \"tenure\" näher anschauen und checken, ob es noch andere 0-Werte in diese Spalte gibt."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f174459b-12b3-4646-b618-6ad27a58460a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.406520Z",
     "iopub.status.busy": "2026-04-09T19:52:11.406440Z",
     "iopub.status.idle": "2026-04-09T19:52:11.410375Z",
     "shell.execute_reply": "2026-04-09T19:52:11.409882Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.406513Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([488, 753, 936, 1082, 1340, 3331, 3826, 4380, 5218, 6670, 6754], dtype='int64')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"tenure\"] == 0].index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58696713-857a-4bc6-a69c-cc10aab2b918",
   "metadata": {},
   "source": [
    "### Feststellung und Entscheidung \n",
    "\n",
    "Der Vergleich zeigt, dass es keine zusätzlichen fehlenden Werte in der \"tenure\"-Spalte gibt.\n",
    "\n",
    "Wir löschen die Zeilen mit den fehlenden Werten in \"tenure\" und \"TotalCharges\", da es nur 11 von 7043 Zeilen sind und wir nicht von gravierenden Konsequenzen durch das Löschen dieser Zeilen ausgehen.\n",
    "\n",
    "Wenn es nur die fehlenden Werte in \"TotalCharges\" wäre, könnte man auch versuchen, die Werte darin durch Extrapolation aufzufüllen mit z.B. mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5c2a9595-6a4c-4e04-aa55-d43614472ff6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.410741Z",
     "iopub.status.busy": "2026-04-09T19:52:11.410665Z",
     "iopub.status.idle": "2026-04-09T19:52:11.415891Z",
     "shell.execute_reply": "2026-04-09T19:52:11.415327Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.410732Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([], dtype='int64')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df.drop(df['tenure'] == 0, axis=0, inplace=False)\n",
    "\n",
    "df_new = df[df[\"tenure\"] != 0]\n",
    "\n",
    "df_new[df_new['tenure'] == 0].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a5254dce-116c-4acd-9180-ed50568340de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.416258Z",
     "iopub.status.busy": "2026-04-09T19:52:11.416188Z",
     "iopub.status.idle": "2026-04-09T19:52:11.421568Z",
     "shell.execute_reply": "2026-04-09T19:52:11.421178Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.416251Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([], dtype='int64')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new2 = df.drop(labels=df[df['tenure'] == 0].index, axis=0, inplace=False)\n",
    "df_new2[df_new2['tenure'] == 0].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4c943a9b-ea6a-4d43-b4ae-bd6bf42a16bc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.421981Z",
     "iopub.status.busy": "2026-04-09T19:52:11.421902Z",
     "iopub.status.idle": "2026-04-09T19:52:11.431203Z",
     "shell.execute_reply": "2026-04-09T19:52:11.430140Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.421974Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</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>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7038</th>\n",
       "      <td>6840-RESVB</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>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>72</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>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>11</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>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>4</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>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>66</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>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": [
       "      customerID  gender  SeniorCitizen Partner Dependents  tenure  \\\n",
       "0     7590-VHVEG  Female              0     Yes         No       1   \n",
       "1     5575-GNVDE    Male              0      No         No      34   \n",
       "2     3668-QPYBK    Male              0      No         No       2   \n",
       "3     7795-CFOCW    Male              0      No         No      45   \n",
       "4     9237-HQITU  Female              0      No         No       2   \n",
       "...          ...     ...            ...     ...        ...     ...   \n",
       "7038  6840-RESVB    Male              0     Yes        Yes      24   \n",
       "7039  2234-XADUH  Female              0     Yes        Yes      72   \n",
       "7040  4801-JZAZL  Female              0     Yes        Yes      11   \n",
       "7041  8361-LTMKD    Male              1     Yes         No       4   \n",
       "7042  3186-AJIEK    Male              0      No         No      66   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService OnlineSecurity  \\\n",
       "0              No  No phone service             DSL             No   \n",
       "1             Yes                No             DSL            Yes   \n",
       "2             Yes                No             DSL            Yes   \n",
       "3              No  No phone service             DSL            Yes   \n",
       "4             Yes                No     Fiber optic             No   \n",
       "...           ...               ...             ...            ...   \n",
       "7038          Yes               Yes             DSL            Yes   \n",
       "7039          Yes               Yes     Fiber optic             No   \n",
       "7040           No  No phone service             DSL            Yes   \n",
       "7041          Yes               Yes     Fiber optic             No   \n",
       "7042          Yes                No     Fiber optic            Yes   \n",
       "\n",
       "     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   \n",
       "...           ...              ...         ...         ...             ...   \n",
       "7038           No              Yes         Yes         Yes             Yes   \n",
       "7039          Yes              Yes          No         Yes             Yes   \n",
       "7040           No               No          No          No              No   \n",
       "7041           No               No          No          No              No   \n",
       "7042           No              Yes         Yes         Yes             Yes   \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  TotalCharges Churn  \n",
       "0              29.85         29.85    No  \n",
       "1              56.95       1889.50    No  \n",
       "2              53.85        108.15   Yes  \n",
       "3              42.30       1840.75    No  \n",
       "4              70.70        151.65   Yes  \n",
       "...              ...           ...   ...  \n",
       "7038           84.80       1990.50    No  \n",
       "7039          103.20       7362.90    No  \n",
       "7040           29.60        346.45    No  \n",
       "7041           74.40        306.60   Yes  \n",
       "7042          105.65       6844.50    No  \n",
       "\n",
       "[7032 rows x 21 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "524b5401-7ed4-4dc2-8d8c-4e2cdb519274",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.431636Z",
     "iopub.status.busy": "2026-04-09T19:52:11.431515Z",
     "iopub.status.idle": "2026-04-09T19:52:11.434866Z",
     "shell.execute_reply": "2026-04-09T19:52:11.434483Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.431627Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([488, 753, 936, 1082, 1340, 3331, 3826, 4380, 5218, 6670, 6754], dtype='int64')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"tenure\"]==0].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "224c58a4-af6c-4566-9d44-7fff26035870",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.435170Z",
     "iopub.status.busy": "2026-04-09T19:52:11.435111Z",
     "iopub.status.idle": "2026-04-09T19:52:11.445270Z",
     "shell.execute_reply": "2026-04-09T19:52:11.444917Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.435164Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7043, 21)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</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>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7038</th>\n",
       "      <td>6840-RESVB</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>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>72</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>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>11</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>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>4</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>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>66</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>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": [
       "      customerID  gender  SeniorCitizen Partner Dependents  tenure  \\\n",
       "0     7590-VHVEG  Female              0     Yes         No       1   \n",
       "1     5575-GNVDE    Male              0      No         No      34   \n",
       "2     3668-QPYBK    Male              0      No         No       2   \n",
       "3     7795-CFOCW    Male              0      No         No      45   \n",
       "4     9237-HQITU  Female              0      No         No       2   \n",
       "...          ...     ...            ...     ...        ...     ...   \n",
       "7038  6840-RESVB    Male              0     Yes        Yes      24   \n",
       "7039  2234-XADUH  Female              0     Yes        Yes      72   \n",
       "7040  4801-JZAZL  Female              0     Yes        Yes      11   \n",
       "7041  8361-LTMKD    Male              1     Yes         No       4   \n",
       "7042  3186-AJIEK    Male              0      No         No      66   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService OnlineSecurity  \\\n",
       "0              No  No phone service             DSL             No   \n",
       "1             Yes                No             DSL            Yes   \n",
       "2             Yes                No             DSL            Yes   \n",
       "3              No  No phone service             DSL            Yes   \n",
       "4             Yes                No     Fiber optic             No   \n",
       "...           ...               ...             ...            ...   \n",
       "7038          Yes               Yes             DSL            Yes   \n",
       "7039          Yes               Yes     Fiber optic             No   \n",
       "7040           No  No phone service             DSL            Yes   \n",
       "7041          Yes               Yes     Fiber optic             No   \n",
       "7042          Yes                No     Fiber optic            Yes   \n",
       "\n",
       "     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   \n",
       "...           ...              ...         ...         ...             ...   \n",
       "7038           No              Yes         Yes         Yes             Yes   \n",
       "7039          Yes              Yes          No         Yes             Yes   \n",
       "7040           No               No          No          No              No   \n",
       "7041           No               No          No          No              No   \n",
       "7042           No              Yes         Yes         Yes             Yes   \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  TotalCharges Churn  \n",
       "0              29.85         29.85    No  \n",
       "1              56.95       1889.50    No  \n",
       "2              53.85        108.15   Yes  \n",
       "3              42.30       1840.75    No  \n",
       "4              70.70        151.65   Yes  \n",
       "...              ...           ...   ...  \n",
       "7038           84.80       1990.50    No  \n",
       "7039          103.20       7362.90    No  \n",
       "7040           29.60        346.45    No  \n",
       "7041           74.40        306.60   Yes  \n",
       "7042          105.65       6844.50    No  \n",
       "\n",
       "[7032 rows x 21 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df.shape)\n",
    "df.drop(labels=df[df[\"tenure\"] == 0].index, axis=0, inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e9b19aa3-8cd1-4875-ba7f-1f5d241e6d2d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.446372Z",
     "iopub.status.busy": "2026-04-09T19:52:11.446284Z",
     "iopub.status.idle": "2026-04-09T19:52:11.455204Z",
     "shell.execute_reply": "2026-04-09T19:52:11.454744Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.446364Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</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>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7038</th>\n",
       "      <td>6840-RESVB</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>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>72</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>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>11</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>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>4</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>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>66</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>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": [
       "      customerID  gender  SeniorCitizen Partner Dependents  tenure  \\\n",
       "0     7590-VHVEG  Female              0     Yes         No       1   \n",
       "1     5575-GNVDE    Male              0      No         No      34   \n",
       "2     3668-QPYBK    Male              0      No         No       2   \n",
       "3     7795-CFOCW    Male              0      No         No      45   \n",
       "4     9237-HQITU  Female              0      No         No       2   \n",
       "...          ...     ...            ...     ...        ...     ...   \n",
       "7038  6840-RESVB    Male              0     Yes        Yes      24   \n",
       "7039  2234-XADUH  Female              0     Yes        Yes      72   \n",
       "7040  4801-JZAZL  Female              0     Yes        Yes      11   \n",
       "7041  8361-LTMKD    Male              1     Yes         No       4   \n",
       "7042  3186-AJIEK    Male              0      No         No      66   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService OnlineSecurity  \\\n",
       "0              No  No phone service             DSL             No   \n",
       "1             Yes                No             DSL            Yes   \n",
       "2             Yes                No             DSL            Yes   \n",
       "3              No  No phone service             DSL            Yes   \n",
       "4             Yes                No     Fiber optic             No   \n",
       "...           ...               ...             ...            ...   \n",
       "7038          Yes               Yes             DSL            Yes   \n",
       "7039          Yes               Yes     Fiber optic             No   \n",
       "7040           No  No phone service             DSL            Yes   \n",
       "7041          Yes               Yes     Fiber optic             No   \n",
       "7042          Yes                No     Fiber optic            Yes   \n",
       "\n",
       "     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   \n",
       "...           ...              ...         ...         ...             ...   \n",
       "7038           No              Yes         Yes         Yes             Yes   \n",
       "7039          Yes              Yes          No         Yes             Yes   \n",
       "7040           No               No          No          No              No   \n",
       "7041           No               No          No          No              No   \n",
       "7042           No              Yes         Yes         Yes             Yes   \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  TotalCharges Churn  \n",
       "0              29.85         29.85    No  \n",
       "1              56.95       1889.50    No  \n",
       "2              53.85        108.15   Yes  \n",
       "3              42.30       1840.75    No  \n",
       "4              70.70        151.65   Yes  \n",
       "...              ...           ...   ...  \n",
       "7038           84.80       1990.50    No  \n",
       "7039          103.20       7362.90    No  \n",
       "7040           29.60        346.45    No  \n",
       "7041           74.40        306.60   Yes  \n",
       "7042          105.65       6844.50    No  \n",
       "\n",
       "[7032 rows x 21 columns]"
      ]
     },
     "execution_count": 23,
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       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
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       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
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       "      <th>0</th>\n",
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       "      <td>0</td>\n",
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       "      <td>No</td>\n",
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       "      <td>Yes</td>\n",
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       "      <td>No</td>\n",
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       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>5575-GNVDE</td>\n",
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       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>7795-CFOCW</td>\n",
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       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
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       "      <th>4</th>\n",
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       "      <td>9237-HQITU</td>\n",
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       "      <td>0</td>\n",
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       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
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       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>7027</th>\n",
       "      <td>7038</td>\n",
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       "      <td>24</td>\n",
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       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
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       "      <td>84.80</td>\n",
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       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7028</th>\n",
       "      <td>7039</td>\n",
       "      <td>2234-XADUH</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.90</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7029</th>\n",
       "      <td>7040</td>\n",
       "      <td>4801-JZAZL</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>11</td>\n",
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       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7030</th>\n",
       "      <td>7041</td>\n",
       "      <td>8361-LTMKD</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.60</td>\n",
       "      <td>Yes</td>\n",
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       "    <tr>\n",
       "      <th>7031</th>\n",
       "      <td>7042</td>\n",
       "      <td>3186-AJIEK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>66</td>\n",
       "      <td>Yes</td>\n",
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       "      <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>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 × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      index  customerID  gender  SeniorCitizen Partner Dependents  tenure  \\\n",
       "0         0  7590-VHVEG  Female              0     Yes         No       1   \n",
       "1         1  5575-GNVDE    Male              0      No         No      34   \n",
       "2         2  3668-QPYBK    Male              0      No         No       2   \n",
       "3         3  7795-CFOCW    Male              0      No         No      45   \n",
       "4         4  9237-HQITU  Female              0      No         No       2   \n",
       "...     ...         ...     ...            ...     ...        ...     ...   \n",
       "7027   7038  6840-RESVB    Male              0     Yes        Yes      24   \n",
       "7028   7039  2234-XADUH  Female              0     Yes        Yes      72   \n",
       "7029   7040  4801-JZAZL  Female              0     Yes        Yes      11   \n",
       "7030   7041  8361-LTMKD    Male              1     Yes         No       4   \n",
       "7031   7042  3186-AJIEK    Male              0      No         No      66   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService OnlineSecurity  \\\n",
       "0              No  No phone service             DSL             No   \n",
       "1             Yes                No             DSL            Yes   \n",
       "2             Yes                No             DSL            Yes   \n",
       "3              No  No phone service             DSL            Yes   \n",
       "4             Yes                No     Fiber optic             No   \n",
       "...           ...               ...             ...            ...   \n",
       "7027          Yes               Yes             DSL            Yes   \n",
       "7028          Yes               Yes     Fiber optic             No   \n",
       "7029           No  No phone service             DSL            Yes   \n",
       "7030          Yes               Yes     Fiber optic             No   \n",
       "7031          Yes                No     Fiber optic            Yes   \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   \n",
       "...           ...              ...         ...         ...             ...   \n",
       "7027           No              Yes         Yes         Yes             Yes   \n",
       "7028          Yes              Yes          No         Yes             Yes   \n",
       "7029           No               No          No          No              No   \n",
       "7030           No               No          No          No              No   \n",
       "7031           No              Yes         Yes         Yes             Yes   \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",
       "7027        One year              Yes               Mailed check   \n",
       "7028        One year              Yes    Credit card (automatic)   \n",
       "7029  Month-to-month              Yes           Electronic check   \n",
       "7030  Month-to-month              Yes               Mailed check   \n",
       "7031        Two year              Yes  Bank transfer (automatic)   \n",
       "\n",
       "      MonthlyCharges  TotalCharges Churn  \n",
       "0              29.85         29.85    No  \n",
       "1              56.95       1889.50    No  \n",
       "2              53.85        108.15   Yes  \n",
       "3              42.30       1840.75    No  \n",
       "4              70.70        151.65   Yes  \n",
       "...              ...           ...   ...  \n",
       "7027           84.80       1990.50    No  \n",
       "7028          103.20       7362.90    No  \n",
       "7029           29.60        346.45    No  \n",
       "7030           74.40        306.60   Yes  \n",
       "7031          105.65       6844.50    No  \n",
       "\n",
       "[7032 rows x 22 columns]"
      ]
     },
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       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
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       "      <td>No</td>\n",
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       "    <tr>\n",
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       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <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>7027</th>\n",
       "      <td>6840-RESVB</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7028</th>\n",
       "      <td>2234-XADUH</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.90</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7029</th>\n",
       "      <td>4801-JZAZL</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7030</th>\n",
       "      <td>8361-LTMKD</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.60</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7031</th>\n",
       "      <td>3186-AJIEK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>66</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.65</td>\n",
       "      <td>6844.50</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7032 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerID  gender  SeniorCitizen Partner Dependents  tenure  \\\n",
       "0     7590-VHVEG  Female              0     Yes         No       1   \n",
       "1     5575-GNVDE    Male              0      No         No      34   \n",
       "2     3668-QPYBK    Male              0      No         No       2   \n",
       "3     7795-CFOCW    Male              0      No         No      45   \n",
       "4     9237-HQITU  Female              0      No         No       2   \n",
       "...          ...     ...            ...     ...        ...     ...   \n",
       "7027  6840-RESVB    Male              0     Yes        Yes      24   \n",
       "7028  2234-XADUH  Female              0     Yes        Yes      72   \n",
       "7029  4801-JZAZL  Female              0     Yes        Yes      11   \n",
       "7030  8361-LTMKD    Male              1     Yes         No       4   \n",
       "7031  3186-AJIEK    Male              0      No         No      66   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService OnlineSecurity  \\\n",
       "0              No  No phone service             DSL             No   \n",
       "1             Yes                No             DSL            Yes   \n",
       "2             Yes                No             DSL            Yes   \n",
       "3              No  No phone service             DSL            Yes   \n",
       "4             Yes                No     Fiber optic             No   \n",
       "...           ...               ...             ...            ...   \n",
       "7027          Yes               Yes             DSL            Yes   \n",
       "7028          Yes               Yes     Fiber optic             No   \n",
       "7029           No  No phone service             DSL            Yes   \n",
       "7030          Yes               Yes     Fiber optic             No   \n",
       "7031          Yes                No     Fiber optic            Yes   \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   \n",
       "...           ...              ...         ...         ...             ...   \n",
       "7027           No              Yes         Yes         Yes             Yes   \n",
       "7028          Yes              Yes          No         Yes             Yes   \n",
       "7029           No               No          No          No              No   \n",
       "7030           No               No          No          No              No   \n",
       "7031           No              Yes         Yes         Yes             Yes   \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",
       "7027        One year              Yes               Mailed check   \n",
       "7028        One year              Yes    Credit card (automatic)   \n",
       "7029  Month-to-month              Yes           Electronic check   \n",
       "7030  Month-to-month              Yes               Mailed check   \n",
       "7031        Two year              Yes  Bank transfer (automatic)   \n",
       "\n",
       "      MonthlyCharges  TotalCharges Churn  \n",
       "0              29.85         29.85    No  \n",
       "1              56.95       1889.50    No  \n",
       "2              53.85        108.15   Yes  \n",
       "3              42.30       1840.75    No  \n",
       "4              70.70        151.65   Yes  \n",
       "...              ...           ...   ...  \n",
       "7027           84.80       1990.50    No  \n",
       "7028          103.20       7362.90    No  \n",
       "7029           29.60        346.45    No  \n",
       "7030           74.40        306.60   Yes  \n",
       "7031          105.65       6844.50    No  \n",
       "\n",
       "[7032 rows x 21 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if \"index\" in df:\n",
    "    df.drop(\"index\", axis=1, inplace=True) \n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f308e670-6769-4041-bf1f-c3d6a572dc77",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.472843Z",
     "iopub.status.busy": "2026-04-09T19:52:11.472778Z",
     "iopub.status.idle": "2026-04-09T19:52:11.477604Z",
     "shell.execute_reply": "2026-04-09T19:52:11.477145Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.472837Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [customerID, gender, SeniorCitizen, Partner, Dependents, tenure, PhoneService, MultipleLines, InternetService, OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport, StreamingTV, StreamingMovies, Contract, PaperlessBilling, PaymentMethod, MonthlyCharges, TotalCharges, Churn]\n",
       "Index: []"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"TotalCharges\"].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "34da2dbf-2da1-462b-87f9-bbda14ceb309",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.477991Z",
     "iopub.status.busy": "2026-04-09T19:52:11.477910Z",
     "iopub.status.idle": "2026-04-09T19:52:11.486379Z",
     "shell.execute_reply": "2026-04-09T19:52:11.485884Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.477983Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</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>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <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>7027</th>\n",
       "      <td>6840-RESVB</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7028</th>\n",
       "      <td>2234-XADUH</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.90</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7029</th>\n",
       "      <td>4801-JZAZL</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7030</th>\n",
       "      <td>8361-LTMKD</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.60</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7031</th>\n",
       "      <td>3186-AJIEK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>66</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.65</td>\n",
       "      <td>6844.50</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7032 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerID  gender  SeniorCitizen Partner Dependents  tenure  \\\n",
       "0     7590-VHVEG  Female              0     Yes         No       1   \n",
       "1     5575-GNVDE    Male              0      No         No      34   \n",
       "2     3668-QPYBK    Male              0      No         No       2   \n",
       "3     7795-CFOCW    Male              0      No         No      45   \n",
       "4     9237-HQITU  Female              0      No         No       2   \n",
       "...          ...     ...            ...     ...        ...     ...   \n",
       "7027  6840-RESVB    Male              0     Yes        Yes      24   \n",
       "7028  2234-XADUH  Female              0     Yes        Yes      72   \n",
       "7029  4801-JZAZL  Female              0     Yes        Yes      11   \n",
       "7030  8361-LTMKD    Male              1     Yes         No       4   \n",
       "7031  3186-AJIEK    Male              0      No         No      66   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService OnlineSecurity  \\\n",
       "0              No  No phone service             DSL             No   \n",
       "1             Yes                No             DSL            Yes   \n",
       "2             Yes                No             DSL            Yes   \n",
       "3              No  No phone service             DSL            Yes   \n",
       "4             Yes                No     Fiber optic             No   \n",
       "...           ...               ...             ...            ...   \n",
       "7027          Yes               Yes             DSL            Yes   \n",
       "7028          Yes               Yes     Fiber optic             No   \n",
       "7029           No  No phone service             DSL            Yes   \n",
       "7030          Yes               Yes     Fiber optic             No   \n",
       "7031          Yes                No     Fiber optic            Yes   \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   \n",
       "...           ...              ...         ...         ...             ...   \n",
       "7027           No              Yes         Yes         Yes             Yes   \n",
       "7028          Yes              Yes          No         Yes             Yes   \n",
       "7029           No               No          No          No              No   \n",
       "7030           No               No          No          No              No   \n",
       "7031           No              Yes         Yes         Yes             Yes   \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",
       "7027        One year              Yes               Mailed check   \n",
       "7028        One year              Yes    Credit card (automatic)   \n",
       "7029  Month-to-month              Yes           Electronic check   \n",
       "7030  Month-to-month              Yes               Mailed check   \n",
       "7031        Two year              Yes  Bank transfer (automatic)   \n",
       "\n",
       "      MonthlyCharges  TotalCharges Churn  \n",
       "0              29.85         29.85    No  \n",
       "1              56.95       1889.50    No  \n",
       "2              53.85        108.15   Yes  \n",
       "3              42.30       1840.75    No  \n",
       "4              70.70        151.65   Yes  \n",
       "...              ...           ...   ...  \n",
       "7027           84.80       1990.50    No  \n",
       "7028          103.20       7362.90    No  \n",
       "7029           29.60        346.45    No  \n",
       "7030           74.40        306.60   Yes  \n",
       "7031          105.65       6844.50    No  \n",
       "\n",
       "[7032 rows x 21 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[~df[\"TotalCharges\"].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "1844d118-70c4-46f8-b7fc-7bf9987df5a0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.486834Z",
     "iopub.status.busy": "2026-04-09T19:52:11.486750Z",
     "iopub.status.idle": "2026-04-09T19:52:11.490304Z",
     "shell.execute_reply": "2026-04-09T19:52:11.489806Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.486828Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "customerID          0\n",
       "gender              0\n",
       "SeniorCitizen       0\n",
       "Partner             0\n",
       "Dependents          0\n",
       "tenure              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",
       "Contract            0\n",
       "PaperlessBilling    0\n",
       "PaymentMethod       0\n",
       "MonthlyCharges      0\n",
       "TotalCharges        0\n",
       "Churn               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e06cfdf-0f87-4187-8384-f6aa8e2ee73d",
   "metadata": {},
   "source": [
    "## EDA - Explorative Data Analysis (Daten Exploration)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f513b8cc-1033-4f27-93b1-c24c3edaef3f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.490710Z",
     "iopub.status.busy": "2026-04-09T19:52:11.490639Z",
     "iopub.status.idle": "2026-04-09T19:52:11.493957Z",
     "shell.execute_reply": "2026-04-09T19:52:11.493680Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.490704Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count            7032\n",
       "unique              3\n",
       "top       Fiber optic\n",
       "freq             3096\n",
       "Name: InternetService, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"InternetService\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b8442823-7001-4303-929f-629b4ae17237",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.494414Z",
     "iopub.status.busy": "2026-04-09T19:52:11.494326Z",
     "iopub.status.idle": "2026-04-09T19:52:11.497585Z",
     "shell.execute_reply": "2026-04-09T19:52:11.497183Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.494407Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ArrowStringArray>\n",
       "['DSL', 'Fiber optic', 'No']\n",
       "Length: 3, dtype: str"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"InternetService\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2d6e3c99-586a-4f30-ab58-75499617a3c6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.498019Z",
     "iopub.status.busy": "2026-04-09T19:52:11.497928Z",
     "iopub.status.idle": "2026-04-09T19:52:11.501234Z",
     "shell.execute_reply": "2026-04-09T19:52:11.500722Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.498012Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InternetService\n",
       "Fiber optic    3096\n",
       "DSL            2416\n",
       "No             1520\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"InternetService\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "de238e7a-f1e0-4216-ae17-efd1b5c0ab1d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.501628Z",
     "iopub.status.busy": "2026-04-09T19:52:11.501564Z",
     "iopub.status.idle": "2026-04-09T19:52:11.508060Z",
     "shell.execute_reply": "2026-04-09T19:52:11.507599Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.501622Z"
    }
   },
   "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>tenure</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7032.000000</td>\n",
       "      <td>7032.000000</td>\n",
       "      <td>7032.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>32.421786</td>\n",
       "      <td>64.798208</td>\n",
       "      <td>2283.300441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>24.545260</td>\n",
       "      <td>30.085974</td>\n",
       "      <td>2266.771362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>18.250000</td>\n",
       "      <td>18.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>9.000000</td>\n",
       "      <td>35.587500</td>\n",
       "      <td>401.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>70.350000</td>\n",
       "      <td>1397.475000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>55.000000</td>\n",
       "      <td>89.862500</td>\n",
       "      <td>3794.737500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>72.000000</td>\n",
       "      <td>118.750000</td>\n",
       "      <td>8684.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            tenure  MonthlyCharges  TotalCharges\n",
       "count  7032.000000     7032.000000   7032.000000\n",
       "mean     32.421786       64.798208   2283.300441\n",
       "std      24.545260       30.085974   2266.771362\n",
       "min       1.000000       18.250000     18.800000\n",
       "25%       9.000000       35.587500    401.450000\n",
       "50%      29.000000       70.350000   1397.475000\n",
       "75%      55.000000       89.862500   3794.737500\n",
       "max      72.000000      118.750000   8684.800000"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerical_cols = [\"tenure\", \"MonthlyCharges\", \"TotalCharges\"]\n",
    "df[numerical_cols].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2c1a2b9c-f471-46ba-aeef-a36e06a13098",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.508415Z",
     "iopub.status.busy": "2026-04-09T19:52:11.508343Z",
     "iopub.status.idle": "2026-04-09T19:52:11.511130Z",
     "shell.execute_reply": "2026-04-09T19:52:11.510746Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.508409Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gender\n",
       "Male      3549\n",
       "Female    3483\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"gender\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "6a123a77-6d73-4c13-96ab-43ee49a3c602",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.511446Z",
     "iopub.status.busy": "2026-04-09T19:52:11.511387Z",
     "iopub.status.idle": "2026-04-09T19:52:11.515460Z",
     "shell.execute_reply": "2026-04-09T19:52:11.514843Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.511440Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Churn\n",
       "No     5163\n",
       "Yes    1869\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Churn\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "6ab8bde8-37ee-4acf-ac25-d87025b25e0c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.515975Z",
     "iopub.status.busy": "2026-04-09T19:52:11.515879Z",
     "iopub.status.idle": "2026-04-09T19:52:11.522691Z",
     "shell.execute_reply": "2026-04-09T19:52:11.522205Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.515969Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Churned Customers\n",
      "gender\n",
      "Female    939\n",
      "Male      930\n",
      "Name: Churn, dtype: int64\n",
      "\n",
      "Not-yet-churned Customers\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "gender\n",
       "Female    2544\n",
       "Male      2619\n",
       "Name: Churn, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Anzahl der gechurnten Kunden pro Geschlecht ermitteln\n",
    "print(\"Churned Customers\")\n",
    "print(df[\"Churn\"][df[\"Churn\"]==\"Yes\"].groupby(by=df[\"gender\"]).count()) \n",
    "print()\n",
    "print(\"Not-yet-churned Customers\")\n",
    "df[\"Churn\"][df[\"Churn\"]==\"No\"].groupby(by=df[\"gender\"]).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5b96a7a6-58e0-4020-bda5-739bac89917b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.523087Z",
     "iopub.status.busy": "2026-04-09T19:52:11.522975Z",
     "iopub.status.idle": "2026-04-09T19:52:11.565144Z",
     "shell.execute_reply": "2026-04-09T19:52:11.564252Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.523080Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Visualizierung der Churn Verteilung vs. Geschlecht\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "labels =[\"Churn: Yes\",\"Churn:No\"]\n",
    "values = [1869,5163]\n",
    "labels_gender = [\"F\",\"M\",\"F\",\"M\"]\n",
    "sizes_gender = [939,930 , 2544,2619]\n",
    "colors = [\"#ff6666\", \"#66b3ff\"]\n",
    "colors_gender = [\"#c2c2f0\", \"#ffb3e6\", \"#c2c2f0\", \"#ffb3e6\"]\n",
    "explode = (0.3,0.3) \n",
    "explode_gender = (0.1,0.1,0.1,0.1)\n",
    "textprops = {\"fontsize\":15}\n",
    "#Plot\n",
    "plt.pie(values, labels=labels,autopct=\"%1.1f%%\",pctdistance=1.08, labeldistance=0.8,colors=colors, startangle=90,frame=True, explode=explode,radius=10, textprops =textprops, counterclock = True, )\n",
    "plt.pie(sizes_gender,labels=labels_gender,colors=colors_gender,startangle=90, explode=explode_gender,radius=7, textprops =textprops, counterclock = True, )\n",
    "#Draw circle\n",
    "centre_circle = plt.Circle((0,0),5,color=\"black\", fc=\"white\",linewidth=0)\n",
    "fig = plt.gcf()\n",
    "fig.gca().add_artist(centre_circle)\n",
    "\n",
    "plt.title(\"Churn Distribution w.r.t Gender: Male(M), Female(F)\", fontsize=15, y=1.1)\n",
    "\n",
    "# show plot \n",
    " \n",
    "plt.axis(\"equal\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "47c3a5e4-fc27-44be-a728-097a1499e8db",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:11.565914Z",
     "iopub.status.busy": "2026-04-09T19:52:11.565772Z",
     "iopub.status.idle": "2026-04-09T19:52:12.866913Z",
     "shell.execute_reply": "2026-04-09T19:52:12.866323Z",
     "shell.execute_reply.started": "2026-04-09T19:52:11.565905Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "bingroup": "x",
         "hovertemplate": "Contract=Month-to-month<br>Churn=%{x}<br>count=%{y}<extra></extra>",
         "legendgroup": "Month-to-month",
         "marker": {
          "color": "#636efa",
          "pattern": {
           "shape": ""
          }
         },
         "name": "Month-to-month",
         "offsetgroup": "Month-to-month",
         "orientation": "v",
         "showlegend": true,
         "type": "histogram",
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Visualisierung Verteilung: Churn vs. Kundenvertrag\n",
    "\n",
    "fig = px.histogram(df, x=\"Churn\", color=\"Contract\", barmode=\"group\", title=\"<b>Verteilung: Churn vs. Kundenvertrag<b>\")\n",
    "fig.update_layout(width=700, height=500, bargap=0.1)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "94785210-311a-4f12-98f1-27313ee60564",
   "metadata": {
    "execution": {
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Verteilung: Churn vs. Kunden Zahlungsmethod distribution w.r.t. Churn\n",
    "\n",
    "fig = px.histogram(df, x=\"Churn\", color=\"PaymentMethod\", title=\"<b>Verteilung: Churn vs. Kunden Zahlungsmethod distribution w.r.t. Churn</b>\")\n",
    "fig.update_layout(width=700, height=500, bargap=0.1)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4444686-386e-4af0-9da5-99ff294a7660",
   "metadata": {},
   "source": [
    "Wir beobachten folgendes: \n",
    "- Die meisten Kunden, die abgewandert sind, hatten einen elektronischen Scheck als Zahlungsmethode.\n",
    "- Kunden, die sich für die automatische Überweisung per Kreditkarte oder Banküberweisung und den Versand von Schecks als Zahlungsmethode entschieden, sind seltener abgewandert."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "f5717457-afa8-445f-b03d-9dd55115ab88",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:12.894421Z",
     "iopub.status.busy": "2026-04-09T19:52:12.894321Z",
     "iopub.status.idle": "2026-04-09T19:52:12.898629Z",
     "shell.execute_reply": "2026-04-09T19:52:12.897354Z",
     "shell.execute_reply.started": "2026-04-09T19:52:12.894412Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ArrowStringArray>\n",
       "['DSL', 'Fiber optic', 'No']\n",
       "Length: 3, dtype: str"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"InternetService\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "a5a2b3c3-4954-4f00-bd48-ea78905975c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:12.899064Z",
     "iopub.status.busy": "2026-04-09T19:52:12.898974Z",
     "iopub.status.idle": "2026-04-09T19:52:12.906755Z",
     "shell.execute_reply": "2026-04-09T19:52:12.906335Z",
     "shell.execute_reply.started": "2026-04-09T19:52:12.899054Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InternetService  Churn\n",
       "DSL              No       992\n",
       "Fiber optic      No       910\n",
       "No               No       717\n",
       "Fiber optic      Yes      633\n",
       "DSL              Yes      240\n",
       "No               Yes       57\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"gender\"]==\"Male\"][[\"InternetService\", \"Churn\"]].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "64213bdf-b7db-4c80-8a89-f62e7badd159",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:12.907287Z",
     "iopub.status.busy": "2026-04-09T19:52:12.907218Z",
     "iopub.status.idle": "2026-04-09T19:52:12.912366Z",
     "shell.execute_reply": "2026-04-09T19:52:12.911786Z",
     "shell.execute_reply.started": "2026-04-09T19:52:12.907281Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InternetService  Churn\n",
       "DSL              No       965\n",
       "Fiber optic      No       889\n",
       "No               No       690\n",
       "Fiber optic      Yes      664\n",
       "DSL              Yes      219\n",
       "No               Yes       56\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"gender\"]==\"Female\"][[\"InternetService\", \"Churn\"]].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "df48744b-1748-4ddb-82be-1c4ac704e8f9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:12.913452Z",
     "iopub.status.busy": "2026-04-09T19:52:12.913363Z",
     "iopub.status.idle": "2026-04-09T19:52:12.919704Z",
     "shell.execute_reply": "2026-04-09T19:52:12.919154Z",
     "shell.execute_reply.started": "2026-04-09T19:52:12.913444Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = go.Figure()\n",
    "\n",
    "fig.add_trace(go.Bar(\n",
    "  x = [[\"Churn:No\", \"Churn:No\", \"Churn:Yes\", \"Churn:Yes\"],\n",
    "       [\"Female\", \"Male\", \"Female\", \"Male\"]],\n",
    "  y = [965, 992, 219, 240],\n",
    "  name = 'DSL',\n",
    "))\n",
    "\n",
    "fig.add_trace(go.Bar(\n",
    "  x = [[\"Churn:No\", \"Churn:No\", \"Churn:Yes\", \"Churn:Yes\"],\n",
    "       [\"Female\", \"Male\", \"Female\", \"Male\"]],\n",
    "  y = [889, 910, 664, 633],\n",
    "  name = \"Fiber optic\",\n",
    "))\n",
    "\n",
    "fig.add_trace(go.Bar(\n",
    "  x = [[\"Churn:No\", \"Churn:No\", \"Churn:Yes\", \"Churn:Yes\"],\n",
    "       [\"Female\", \"Male\", \"Female\", \"Male\"]],\n",
    "  y = [690, 717, 56, 57],\n",
    "  name = \"No Internet\",\n",
    "))\n",
    "\n",
    "fig.update_layout(title_text=\"<b>Verteilung: Churn vs. InternetService und Geschlecht</b>\")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dff0b75a-3862-4662-8384-2f45b4b143cb",
   "metadata": {},
   "source": [
    "Viele Kunden hatten sich für den Glasfaserdienst (Fiber optic) entschieden. Diese scheinen eine hohe Abwanderungsrate zu haben, was auf eine Unzufriedenheit mit dieser Art von Internetdienst hindeuten könnte.\n",
    "\n",
    "Kunden, die einen DSL-Dienst nutzen, sind in der Mehrzahl und haben eine geringere Abwanderungsrate als Glasfaserkunden."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "73a4d491-84b7-41bd-831a-483d351d1bae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:12.921126Z",
     "iopub.status.busy": "2026-04-09T19:52:12.921023Z",
     "iopub.status.idle": "2026-04-09T19:52:12.944712Z",
     "shell.execute_reply": "2026-04-09T19:52:12.944053Z",
     "shell.execute_reply.started": "2026-04-09T19:52:12.921118Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "bingroup": "x",
         "hovertemplate": "Dependents=No<br>Churn=%{x}<br>count=%{y}<extra></extra>",
         "legendgroup": "No",
         "marker": {
          "color": "#AB63FA",
          "pattern": {
           "shape": ""
          }
         },
         "name": "No",
         "offsetgroup": "No",
         "orientation": "v",
         "showlegend": true,
         "type": "histogram",
         "x": [
          "No",
          "No",
          "Yes",
          "No",
          "Yes",
          "Yes",
          "No",
          "Yes",
          "No",
          "No",
          "Yes",
          "No",
          "No",
          "No",
          "Yes",
          "No",
          "Yes",
          "No",
          "No",
          "No",
          "No",
          "No",
          "No",
          "No",
          "Yes",
          "No",
          "Yes",
          "Yes",
          "No",
          "No",
          "No",
          "No",
          "Yes",
          "No",
          "No",
          "Yes",
          "No",
          "Yes",
          "Yes",
          "No",
          "No",
          "No",
          "No",
          "Yes",
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_map = {\"Yes\": \"#FF97FF\", \"No\": \"#AB63FA\"}\n",
    "fig = px.histogram(df, x=\"Churn\", color=\"Dependents\", barmode=\"group\", title=\"<b>Verteilung: Churn vs. Familienangehörige</b>\", color_discrete_map=color_map)\n",
    "fig.update_layout(width=700, height=500, bargap=0.1)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cddbd28-5808-427e-8624-bca8b8090888",
   "metadata": {},
   "source": [
    "Es scheint, dass die Kunden ohne Familienangehörige (\"dependents\") wahrscheinlicher abwandern."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "ea5a0f45-02d8-46b7-a2fe-de71c3003e73",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:12.945432Z",
     "iopub.status.busy": "2026-04-09T19:52:12.945242Z",
     "iopub.status.idle": "2026-04-09T19:52:12.973368Z",
     "shell.execute_reply": "2026-04-09T19:52:12.972771Z",
     "shell.execute_reply.started": "2026-04-09T19:52:12.945423Z"
    }
   },
   "outputs": [
    {
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_map = {\"Yes\": '#FFA15A', \"No\": '#00CC96'}\n",
    "fig = px.histogram(df, x=\"Churn\", color=\"Partner\", barmode=\"group\", title=\"<b>Verteilung: Churn vs. Partners</b>\", color_discrete_map=color_map)\n",
    "fig.update_layout(width=700, height=500, bargap=0.1)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f4bab41-134d-40d3-8e9b-1b14f4c0c4b6",
   "metadata": {},
   "source": [
    "Kunden OHNE Partner scheinen eher dazu zu tendieren abzuwandern. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "eac6af2b-435c-499b-be24-8ba30c2e75e6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:12.973833Z",
     "iopub.status.busy": "2026-04-09T19:52:12.973760Z",
     "iopub.status.idle": "2026-04-09T19:52:13.002603Z",
     "shell.execute_reply": "2026-04-09T19:52:13.002197Z",
     "shell.execute_reply.started": "2026-04-09T19:52:12.973826Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "config": {
        "plotlyServerURL": "https://plot.ly"
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       "data": [
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         "hovertemplate": "SeniorCitizen=0<br>Churn=%{x}<br>count=%{y}<extra></extra>",
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_map = {\"Yes\": \"#00CC96\", \"No\": \"#B6E880\"}\n",
    "fig = px.histogram(df, x=\"Churn\", color=\"SeniorCitizen\", title=\"<b>Verteilung: Churn vs. Senior Citizen</b>\", color_discrete_map=color_map)\n",
    "fig.update_layout(width=700, height=500, bargap=0.1)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2feaf009-f22f-4224-af0c-4ec97caa0ca5",
   "metadata": {},
   "source": [
    "- Wir stellen fest, dass generell der Anteil an \"seniorigen\" Kunden recht niedrig ist. \n",
    "- Dazu kann man sagen, dass ein die seniorigen Kunden eher dazu tendieren abzuwandern. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "09dcbc1b-28bf-4150-b358-a0dba0cf8baa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.003038Z",
     "iopub.status.busy": "2026-04-09T19:52:13.002895Z",
     "iopub.status.idle": "2026-04-09T19:52:13.033756Z",
     "shell.execute_reply": "2026-04-09T19:52:13.033080Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.003028Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "bingroup": "x",
         "hovertemplate": "OnlineSecurity=No<br>Churn=%{x}<br>count=%{y}<extra></extra>",
         "legendgroup": "No",
         "marker": {
          "color": "#AB63FA",
          "pattern": {
           "shape": ""
          }
         },
         "name": "No",
         "offsetgroup": "No",
         "orientation": "v",
         "showlegend": true,
         "type": "histogram",
         "x": [
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_map = {\"Yes\": \"#FF97FF\", \"No\": \"#AB63FA\"}\n",
    "fig = px.histogram(df, x=\"Churn\", color=\"OnlineSecurity\", barmode=\"group\", title=\"<b>Verteilung: Churn vs. Online Security</b>\", color_discrete_map=color_map)\n",
    "fig.update_layout(width=700, height=500, bargap=0.1)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b22deef-923c-493e-82eb-90c3129767f7",
   "metadata": {},
   "source": [
    "Kunden OHNE Online Security tendieren stark dazu abzuwandern. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "dcac6ef6-4db2-44e7-90d6-f3c00c734d7f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.034328Z",
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_map = {\"Yes\": \"#FFA15A\", \"No\": \"#00CC96\"}\n",
    "fig = px.histogram(df, x=\"Churn\", color=\"PaperlessBilling\",  title=\"<b>Verteilung: Churn vs. Papierlose Rechnung</b>\", color_discrete_map=color_map)\n",
    "fig.update_layout(width=700, height=500, bargap=0.1)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8c6e431-b685-4bab-9149-5dc30b0c8db2",
   "metadata": {},
   "source": [
    "Kunden mit Papierlosen Zahlen scheinen dazu zu tendieren, abzuwandern."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "8304703b-7985-4740-92b4-757b86fdfa15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.057132Z",
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.histogram(df, x=\"Churn\", color=\"TechSupport\",barmode=\"group\",  title=\"<b>Verteilung: Churn vs. TechSupport</b>\")\n",
    "fig.update_layout(width=700, height=500, bargap=0.1)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e155073b-54ba-4f0c-9816-7acf7cea4e98",
   "metadata": {},
   "source": [
    "Kunden OHNE TechSupport scheinen stark dazu zu tendieren abzuwandern"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "645e29da-ed05-4ead-b2e0-ed3b0ffdf637",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.083999Z",
     "iopub.status.busy": "2026-04-09T19:52:13.083877Z",
     "iopub.status.idle": "2026-04-09T19:52:13.174472Z",
     "shell.execute_reply": "2026-04-09T19:52:13.174068Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.083971Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"paper\",font_scale=1.1)\n",
    "ax = sns.kdeplot(df.MonthlyCharges[(df[\"Churn\"] == \"No\") ],\n",
    "                color=\"Red\", shade = True);\n",
    "ax = sns.kdeplot(df.MonthlyCharges[(df[\"Churn\"] == \"Yes\") ],\n",
    "                ax =ax, color=\"Blue\", shade= True);\n",
    "ax.legend([\"Not Churn\",\"Churn\"],loc='upper right');\n",
    "ax.set_ylabel(\"Density\");\n",
    "ax.set_xlabel(\"Monthly Charges\");\n",
    "ax.set_title(\"Verteilung: Churn vs. Monthly Charges\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c044ee4-b4f8-4afd-9162-53f22cf1a7fd",
   "metadata": {},
   "source": [
    "Kunden MIT höheren monatlichen Kosten tendieren eher dazu abzuwandern\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "7779675d-f06d-4a26-b2fe-16bab39c96b0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.175029Z",
     "iopub.status.busy": "2026-04-09T19:52:13.174952Z",
     "iopub.status.idle": "2026-04-09T19:52:13.248962Z",
     "shell.execute_reply": "2026-04-09T19:52:13.248276Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.175022Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.kdeplot(df.TotalCharges[(df[\"Churn\"] == \"No\") ],\n",
    "                color=\"Gold\", shade = True);\n",
    "ax = sns.kdeplot(df.TotalCharges[(df[\"Churn\"] == \"Yes\") ],\n",
    "                ax =ax, color=\"Green\", shade= True);\n",
    "ax.legend([\"Not Chu0rn\",\"Churn\"],loc=\"upper right\");\n",
    "ax.set_ylabel(\"Density\");\n",
    "ax.set_xlabel(\"Total Charges\");\n",
    "ax.set_title(\"Verteilung: Churn vs. Total Charges\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f8e9f7c-262e-469a-a56e-254b203e6a6f",
   "metadata": {},
   "source": [
    "Interessanterweise scheint der höhere Total Charge keine direkte Auswirkung auf erhöhte Abwanderungwahrscheinlichkeit zu haben."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "641b5ab4-ec04-4887-a9bf-961e292d9805",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.249393Z",
     "iopub.status.busy": "2026-04-09T19:52:13.249311Z",
     "iopub.status.idle": "2026-04-09T19:52:13.275844Z",
     "shell.execute_reply": "2026-04-09T19:52:13.275420Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.249385Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "hovertemplate": "Churn=%{x}<br>tenure=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#636efa"
         },
         "name": "",
         "notched": false,
         "offsetgroup": "",
         "orientation": "v",
         "showlegend": false,
         "type": "box",
         "x": [
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.box(df, x=\"Churn\", y = \"tenure\")\n",
    "\n",
    "# Update yaxis properties\n",
    "fig.update_yaxes(title_text=\"Tenure (Months)\", row=1, col=1)\n",
    "# Update xaxis properties\n",
    "fig.update_xaxes(title_text=\"Churn\", row=1, col=1)\n",
    "\n",
    "# Update size and title\n",
    "fig.update_layout(autosize=True, width=750, height=600,\n",
    "    title_font=dict(size=25, family=\"Courier\"),\n",
    "    title=\"<b>Tenure vs Churn</b>\",\n",
    ")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63fc1cb9-f398-425a-9c8a-decb1249a469",
   "metadata": {},
   "source": [
    "NEUE Kunden scheinen tendenziell eher abzuwandern. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "ca9dd0fe-ff23-4dd9-9184-d38ac4fe58da",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.276343Z",
     "iopub.status.busy": "2026-04-09T19:52:13.276257Z",
     "iopub.status.idle": "2026-04-09T19:52:13.602570Z",
     "shell.execute_reply": "2026-04-09T19:52:13.601678Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.276335Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotte den Correlation Heatmap (pandas nutzt Pearson Correlation by default)\n",
    "\n",
    "plt.figure(figsize=(25, 10))\n",
    "\n",
    "corr = df.apply(lambda x: pd.factorize(x)[0]).corr()\n",
    "\n",
    "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
    "\n",
    "ax = sns.heatmap(corr, mask=mask, xticklabels=corr.columns, yticklabels=corr.columns, annot=True, linewidths=.2, cmap=\"coolwarm\", vmin=-1, vmax=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "57120e6d-7416-49af-90a8-8d30a4c8153a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.603195Z",
     "iopub.status.busy": "2026-04-09T19:52:13.603029Z",
     "iopub.status.idle": "2026-04-09T19:52:13.608758Z",
     "shell.execute_reply": "2026-04-09T19:52:13.608048Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.603111Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OnlineSecurity\n",
       "No                     3497\n",
       "Yes                    2015\n",
       "No internet service    1520\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.OnlineSecurity.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91170819-b916-42af-a143-918a4435583d",
   "metadata": {},
   "source": [
    "## Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "036158be",
   "metadata": {},
   "source": [
    "### Zielvariable **CHURN** \n",
    "\n",
    "Da es sich um ein binäres Klassifikationsproblem hanaelt, sollte die Target-Variable eine binäre Variable sein (numerisch ausgedrückt).\n",
    "Da sie aktuell noch nur String ist, wird nun die Churn-Spalte als Erstes in binary umgewandelt."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "360ffc71",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.609386Z",
     "iopub.status.busy": "2026-04-09T19:52:13.609193Z",
     "iopub.status.idle": "2026-04-09T19:52:13.622000Z",
     "shell.execute_reply": "2026-04-09T19:52:13.621520Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.609379Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0  7590-VHVEG  Female              0     Yes         No       1           No   \n",
       "1  5575-GNVDE    Male              0      No         No      34          Yes   \n",
       "2  3668-QPYBK    Male              0      No         No       2          Yes   \n",
       "3  7795-CFOCW    Male              0      No         No      45           No   \n",
       "4  9237-HQITU  Female              0      No         No       2          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
       "0  No phone service             DSL             No          Yes   \n",
       "1                No             DSL            Yes           No   \n",
       "2                No             DSL            Yes          Yes   \n",
       "3  No phone service             DSL            Yes           No   \n",
       "4                No     Fiber optic             No           No   \n",
       "\n",
       "  DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
       "0               No          No          No              No  Month-to-month   \n",
       "1              Yes          No          No              No        One year   \n",
       "2               No          No          No              No  Month-to-month   \n",
       "3              Yes         Yes          No              No        One year   \n",
       "4               No          No          No              No  Month-to-month   \n",
       "\n",
       "  PaperlessBilling              PaymentMethod  MonthlyCharges  TotalCharges  \\\n",
       "0              Yes           Electronic check           29.85         29.85   \n",
       "1               No               Mailed check           56.95       1889.50   \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",
       "   Churn  \n",
       "0      0  \n",
       "1      0  \n",
       "2      1  \n",
       "3      0  \n",
       "4      1  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Churn\"] = df[\"Churn\"].map({\"Yes\": 1, \"No\": 0})\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17af3597",
   "metadata": {},
   "source": [
    "Wir entfernen die customerID-Spalte."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "7cc1708b-786f-4bdd-85d0-c651db3bc87c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.623343Z",
     "iopub.status.busy": "2026-04-09T19:52:13.623174Z",
     "iopub.status.idle": "2026-04-09T19:52:13.636347Z",
     "shell.execute_reply": "2026-04-09T19:52:13.635828Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.623334Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7027</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7028</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.90</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7029</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7030</th>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.60</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7031</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>66</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.65</td>\n",
       "      <td>6844.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7032 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0     Female              0     Yes         No       1           No   \n",
       "1       Male              0      No         No      34          Yes   \n",
       "2       Male              0      No         No       2          Yes   \n",
       "3       Male              0      No         No      45           No   \n",
       "4     Female              0      No         No       2          Yes   \n",
       "...      ...            ...     ...        ...     ...          ...   \n",
       "7027    Male              0     Yes        Yes      24          Yes   \n",
       "7028  Female              0     Yes        Yes      72          Yes   \n",
       "7029  Female              0     Yes        Yes      11           No   \n",
       "7030    Male              1     Yes         No       4          Yes   \n",
       "7031    Male              0      No         No      66          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",
       "7027               Yes             DSL            Yes           No   \n",
       "7028               Yes     Fiber optic             No          Yes   \n",
       "7029  No phone service             DSL            Yes           No   \n",
       "7030               Yes     Fiber optic             No           No   \n",
       "7031                No     Fiber optic            Yes           No   \n",
       "\n",
       "     DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
       "0                  No          No          No              No  Month-to-month   \n",
       "1                 Yes          No          No              No        One year   \n",
       "2                  No          No          No              No  Month-to-month   \n",
       "3                 Yes         Yes          No              No        One year   \n",
       "4                  No          No          No              No  Month-to-month   \n",
       "...               ...         ...         ...             ...             ...   \n",
       "7027              Yes         Yes         Yes             Yes        One year   \n",
       "7028              Yes          No         Yes             Yes        One year   \n",
       "7029               No          No          No              No  Month-to-month   \n",
       "7030               No          No          No              No  Month-to-month   \n",
       "7031              Yes         Yes         Yes             Yes        Two year   \n",
       "\n",
       "     PaperlessBilling              PaymentMethod  MonthlyCharges  \\\n",
       "0                 Yes           Electronic check           29.85   \n",
       "1                  No               Mailed check           56.95   \n",
       "2                 Yes               Mailed check           53.85   \n",
       "3                  No  Bank transfer (automatic)           42.30   \n",
       "4                 Yes           Electronic check           70.70   \n",
       "...               ...                        ...             ...   \n",
       "7027              Yes               Mailed check           84.80   \n",
       "7028              Yes    Credit card (automatic)          103.20   \n",
       "7029              Yes           Electronic check           29.60   \n",
       "7030              Yes               Mailed check           74.40   \n",
       "7031              Yes  Bank transfer (automatic)          105.65   \n",
       "\n",
       "      TotalCharges  Churn  \n",
       "0            29.85      0  \n",
       "1          1889.50      0  \n",
       "2           108.15      1  \n",
       "3          1840.75      0  \n",
       "4           151.65      1  \n",
       "...            ...    ...  \n",
       "7027       1990.50      0  \n",
       "7028       7362.90      0  \n",
       "7029        346.45      0  \n",
       "7030        306.60      1  \n",
       "7031       6844.50      0  \n",
       "\n",
       "[7032 rows x 20 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Verwerfe ID-columns\n",
    "if \"customerID\" in df:\n",
    "    df.drop(\"customerID\", axis=1, inplace=True)\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83f5872d-050b-4f54-b8e2-4b0ac2978725",
   "metadata": {},
   "source": [
    "#### Nun haben wir uns schon sehr vieles angeschaut und viel getan ...\n",
    "\n",
    "#### Muessten wir noch etwas tun, bevor wir die Daten splitten? Können wir den Datensatz nun direkt dem Modell zuführen?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20076771-b32f-4219-9599-239c7dd8ba3c",
   "metadata": {},
   "source": [
    "\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e24c36be-f44f-4e69-b454-79a5af6adfa9",
   "metadata": {},
   "source": [
    "#### Kategorische Spalten umwandeln\n",
    "\n",
    "Um die kategorischen Spalten richtig in numerische Spalten umzuwandeln, lass uns sie genauer anschauen und identifizieren, was sich hinter den Strings wirklich verbirgt."
   ]
  },
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    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7027</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7028</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.90</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7029</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7030</th>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.60</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7031</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>66</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>105.65</td>\n",
       "      <td>6844.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7032 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0     Female              0     Yes         No       1           No   \n",
       "1       Male              0      No         No      34          Yes   \n",
       "2       Male              0      No         No       2          Yes   \n",
       "3       Male              0      No         No      45           No   \n",
       "4     Female              0      No         No       2          Yes   \n",
       "...      ...            ...     ...        ...     ...          ...   \n",
       "7027    Male              0     Yes        Yes      24          Yes   \n",
       "7028  Female              0     Yes        Yes      72          Yes   \n",
       "7029  Female              0     Yes        Yes      11           No   \n",
       "7030    Male              1     Yes         No       4          Yes   \n",
       "7031    Male              0      No         No      66          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",
       "7027               Yes             DSL            Yes           No   \n",
       "7028               Yes     Fiber optic             No          Yes   \n",
       "7029  No phone service             DSL            Yes           No   \n",
       "7030               Yes     Fiber optic             No           No   \n",
       "7031                No     Fiber optic            Yes           No   \n",
       "\n",
       "     DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
       "0                  No          No          No              No  Month-to-month   \n",
       "1                 Yes          No          No              No        One year   \n",
       "2                  No          No          No              No  Month-to-month   \n",
       "3                 Yes         Yes          No              No        One year   \n",
       "4                  No          No          No              No  Month-to-month   \n",
       "...               ...         ...         ...             ...             ...   \n",
       "7027              Yes         Yes         Yes             Yes        One year   \n",
       "7028              Yes          No         Yes             Yes        One year   \n",
       "7029               No          No          No              No  Month-to-month   \n",
       "7030               No          No          No              No  Month-to-month   \n",
       "7031              Yes         Yes         Yes             Yes        Two year   \n",
       "\n",
       "     PaperlessBilling              PaymentMethod  MonthlyCharges  \\\n",
       "0                 Yes           Electronic check           29.85   \n",
       "1                  No               Mailed check           56.95   \n",
       "2                 Yes               Mailed check           53.85   \n",
       "3                  No  Bank transfer (automatic)           42.30   \n",
       "4                 Yes           Electronic check           70.70   \n",
       "...               ...                        ...             ...   \n",
       "7027              Yes               Mailed check           84.80   \n",
       "7028              Yes    Credit card (automatic)          103.20   \n",
       "7029              Yes           Electronic check           29.60   \n",
       "7030              Yes               Mailed check           74.40   \n",
       "7031              Yes  Bank transfer (automatic)          105.65   \n",
       "\n",
       "      TotalCharges  Churn  \n",
       "0            29.85      0  \n",
       "1          1889.50      0  \n",
       "2           108.15      1  \n",
       "3          1840.75      0  \n",
       "4           151.65      1  \n",
       "...            ...    ...  \n",
       "7027       1990.50      0  \n",
       "7028       7362.90      0  \n",
       "7029        346.45      0  \n",
       "7030        306.60      1  \n",
       "7031       6844.50      0  \n",
       "\n",
       "[7032 rows x 20 columns]"
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  {
   "cell_type": "markdown",
   "id": "9b1e7349-5dae-4796-8627-8a5c8a997f0d",
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   "source": [
    "### DatenAnalyse:\n",
    "\n",
    "Ist die Spalte: \n",
    "\n",
    "- binary? \n",
    "- boolean? \n",
    "- categorical? \n",
    "- numeric? "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72796faa-19ee-4c59-9c1b-2eb6be5b988e",
   "metadata": {},
   "source": [
    "### Datentypen und ihre Spalten: \n",
    "\n",
    "- binary: \n",
    "gender;\n",
    "- boolean: \n",
    "SeniorCitizen(*), Partner, Dependents, PhoneService, OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport, StreamingTV, StreamingMovies, PaperlessBilling\n",
    "- categorical:\n",
    "MultipleLines, InternetService, Contract, PaymentMethod\n",
    "- numeric:\n",
    "tenure, MonthlyCharges, TotalCharges\n",
    "\n",
    "(*)SeniorCitizen: In diesem Datensatz ist die Spalte bereits durch 0 und 1 ausgedrückt, d.h. rein rechnerisch bräuchte sie nicht nochmal extra als boolean aufgenommen werden. Allerdings sorgt es für mehr Robustheit und Stabilität in der Pipeline und somit Best Practice, doch alle Datentypen entsprechend zu identifizieren."
   ]
  },
  {
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   "id": "8d0972d3-0a8a-4b4d-8ffb-22b3f8315dc6",
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   "source": [
    "#### Recap: \n",
    "\n",
    "- **OrdinalEncoder**: gut für kategorische Werte, die eine innere Ordnung bzw Rang haben, z.B. \"niedrig\", \"medium\", \"hoch\" in Umfrageantworte\n",
    "- **OneHotEncoder**: gut für kategorische Features ohne bestimmte innere Ordnung in einem \"one-hot numerischen Array\".\n",
    "\n",
    "  **Achtung**: OneHotEncoder kann die Dimension (Anzahl Spalten) der Feature-Matrix drastisch erhöhen und \"spärliche Matrizen\" (scarce matrices) mit lauter \"0\" in der Spalte kreieren, wenn die Originalspalte viele verschieden Werte hat (hohe Kardinalität), was wiederum schlechte Datenqualität bedeuten würde.\n",
    "  **Alternativen**: Es gibt auch weitere Alternativen zum One-Hot-Encoding, z.B. kann man auf *Frequency (Count) Encoding* ausweichen:\n",
    "\n",
    "  * hier werden Kategorien basierend auf der Frequency (Häufigkeit, in denen sie auftreten) im Datensatz. Das kann helfen, die Wichtigkeit dieser Kategorie im Datensatz direkt zu erfassen und mitzugeben. Hat aber auch Pitfalls, z.B. wenn das ein biased Datensatz ist. \n",
    "\n",
    "**Achtung!!**\n",
    "\n",
    "- Label-Encoder (in scikit-learn: https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html):\n",
    "\n",
    "  transformiert die ZIELVARIABLE in integers von 0 bis n-1 (n=Anzahl Klassen), gut geeignet bei \"gleichwertigen\" Klassen\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0cec4a64-4e8c-4923-90d6-42e9fa0927cd",
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   "source": [
    "### Unterteile die Columns in 3 Kategorien: Standardisierung, Ordinal-Encoding and One-Hot-Encoding\n",
    "\n",
    "**binary** (direkte Umwandlung zu 0-1): \n",
    "gender\n",
    "\n",
    "**boolean** (direkte Umwandlung zu 0-1): \n",
    "SeniorCitizen, Partner, Dependents, PhoneService, OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport, StreamingTV, StreamingMovies, PaperlessBilling\n",
    "\n",
    "**categorical** (One-Hot oder Frequency Encoding etc):\n",
    "MultipleLines, InternetService, Contract, PaymentMethod\n",
    "\n",
    "**numeric**:\n",
    "tenure, MonthlyCharges, TotalCharges"
   ]
  },
  {
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    "cols_binary = [\"gender\"]\n",
    "cols_boolean = [\"SeniorCitizen\", \"Partner\", \"Dependents\", \"PhoneService\", \"OnlineSecurity\", \"OnlineBackup\", \n",
    "               \"DeviceProtection\", \"TechSupport\", \"StreamingTV\", \"StreamingMovies\", \"PaperlessBilling\"]\n",
    "cols_cat = [\"MultipleLines\", \"InternetService\", \"Contract\", \"PaymentMethod\"]\n",
    "cols_numeric = [\"tenure\", \"MonthlyCharges\", \"TotalCharges\"]"
   ]
  },
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       "<div>\n",
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       "    .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>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>PhoneService</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>PaperlessBilling</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</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>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</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>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</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>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>No</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7027</th>\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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7028</th>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7029</th>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7030</th>\n",
       "      <td>1</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>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7031</th>\n",
       "      <td>0</td>\n",
       "      <td>No</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>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7032 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      SeniorCitizen Partner Dependents PhoneService OnlineSecurity  \\\n",
       "0                 0     Yes         No           No             No   \n",
       "1                 0      No         No          Yes            Yes   \n",
       "2                 0      No         No          Yes            Yes   \n",
       "3                 0      No         No           No            Yes   \n",
       "4                 0      No         No          Yes             No   \n",
       "...             ...     ...        ...          ...            ...   \n",
       "7027              0     Yes        Yes          Yes            Yes   \n",
       "7028              0     Yes        Yes          Yes             No   \n",
       "7029              0     Yes        Yes           No            Yes   \n",
       "7030              1     Yes         No          Yes             No   \n",
       "7031              0      No         No          Yes            Yes   \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   \n",
       "...           ...              ...         ...         ...             ...   \n",
       "7027           No              Yes         Yes         Yes             Yes   \n",
       "7028          Yes              Yes          No         Yes             Yes   \n",
       "7029           No               No          No          No              No   \n",
       "7030           No               No          No          No              No   \n",
       "7031           No              Yes         Yes         Yes             Yes   \n",
       "\n",
       "     PaperlessBilling  \n",
       "0                 Yes  \n",
       "1                  No  \n",
       "2                 Yes  \n",
       "3                  No  \n",
       "4                 Yes  \n",
       "...               ...  \n",
       "7027              Yes  \n",
       "7028              Yes  \n",
       "7029              Yes  \n",
       "7030              Yes  \n",
       "7031              Yes  \n",
       "\n",
       "[7032 rows x 11 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[cols_boolean]"
   ]
  },
  {
   "cell_type": "code",
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    "execution": {
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    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaymentMethod</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Electronic check</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>One year</td>\n",
       "      <td>Mailed check</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>No</td>\n",
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       "    </tr>\n",
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       "      <th>3</th>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>One year</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Month-to-month</td>\n",
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       "      <th>...</th>\n",
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       "      <td>DSL</td>\n",
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       "    <tr>\n",
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       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>One year</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7029</th>\n",
       "      <td>No phone service</td>\n",
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       "      <td>No</td>\n",
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       "      <td>Bank transfer (automatic)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>7032 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         MultipleLines InternetService        Contract  \\\n",
       "0     No phone service             DSL  Month-to-month   \n",
       "1                   No             DSL        One year   \n",
       "2                   No             DSL  Month-to-month   \n",
       "3     No phone service             DSL        One year   \n",
       "4                   No     Fiber optic  Month-to-month   \n",
       "...                ...             ...             ...   \n",
       "7027               Yes             DSL        One year   \n",
       "7028               Yes     Fiber optic        One year   \n",
       "7029  No phone service             DSL  Month-to-month   \n",
       "7030               Yes     Fiber optic  Month-to-month   \n",
       "7031                No     Fiber optic        Two year   \n",
       "\n",
       "                  PaymentMethod  \n",
       "0              Electronic check  \n",
       "1                  Mailed check  \n",
       "2                  Mailed check  \n",
       "3     Bank transfer (automatic)  \n",
       "4              Electronic check  \n",
       "...                         ...  \n",
       "7027               Mailed check  \n",
       "7028    Credit card (automatic)  \n",
       "7029           Electronic check  \n",
       "7030               Mailed check  \n",
       "7031  Bank transfer (automatic)  \n",
       "\n",
       "[7032 rows x 4 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
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    }
   ],
   "source": [
    "df[cols_cat]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "94c3ce3c-d99e-4582-8746-6f437d836360",
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1       0\n",
       "2       0\n",
       "3       0\n",
       "4       1\n",
       "       ..\n",
       "7027    0\n",
       "7028    1\n",
       "7029    1\n",
       "7030    0\n",
       "7031    0\n",
       "Name: gender, Length: 7032, dtype: int64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Mapping von \"Female\" zu 1 und \"Male\" zu 0\n",
    "\n",
    "df[\"gender\"] = df[\"gender\"].map({\"Female\": 1, \"Male\": 0})\n",
    "df[\"gender\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "64173f27-37d7-41b8-a90e-e0e3a8d4e5cf",
   "metadata": {
    "execution": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['SeniorCitizen',\n",
       " 'Partner',\n",
       " 'Dependents',\n",
       " 'PhoneService',\n",
       " 'OnlineSecurity',\n",
       " 'OnlineBackup',\n",
       " 'DeviceProtection',\n",
       " 'TechSupport',\n",
       " 'StreamingTV',\n",
       " 'StreamingMovies',\n",
       " 'PaperlessBilling']"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols_boolean"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ecb1e3f",
   "metadata": {},
   "source": [
    "### One-Hot-Encoding Spalten mit Werten auffüllen. \n",
    "\n",
    "Von den original-kartegorischen Spaltenwerten zu den neuen Werten in den neuen One-Hot-Encoded Spalten:\n",
    "\n",
    "Wir erinnern uns: Ziel liegt darin, die die Spalten mit dem Textwert 'yes' / 'no' in numerische Binärwerte umzuwandeln\n",
    "\n",
    "- `eq(\"yes\")`:\n",
    "\n",
    "    - vergleicht elementweise: Ist der Wert in der Spalte gleich `\"yes\"`?\n",
    "    - Ergebnis ist eine Boolean-Serie: True für `\"yes\"`, False für `\"no\"`.\n",
    "    - falls Spalte bereits als boolean vorliegt, bräuchte man das ggf nicht, da direkt multipliziert werden kann.\n",
    "\n",
    "- `mul(1)`\n",
    "\n",
    "    - elementweise Multiplikation und mappt Booleans zu Zahlen (True wird intern als 1 interpretiert und False als 0), daher wird `True * 1 => 1` und `False * 1 => 0`. Somit wird aus 'yes/no' effektiv 1/0. \n",
    "    \n",
    "=> d.h. man könnte auch `df[col].map({\"yes\":1,\"no\":0})` nutzen anstatt `df[col].eq(\"yes\").mul(1)`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "10d5bda8-22f8-4bba-8767-8c77ddbae614",
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       "  <thead>\n",
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       "      <th></th>\n",
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       "      <th>OnlineBackup</th>\n",
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       "      <th>TechSupport</th>\n",
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       "      <th>1</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "<p>7032 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      SeniorCitizen  Partner  Dependents  PhoneService  OnlineSecurity  \\\n",
       "0                 0        0           0             0               0   \n",
       "1                 0        0           0             0               0   \n",
       "2                 0        0           0             0               0   \n",
       "3                 0        0           0             0               0   \n",
       "4                 0        0           0             0               0   \n",
       "...             ...      ...         ...           ...             ...   \n",
       "7027              0        0           0             0               0   \n",
       "7028              0        0           0             0               0   \n",
       "7029              0        0           0             0               0   \n",
       "7030              0        0           0             0               0   \n",
       "7031              0        0           0             0               0   \n",
       "\n",
       "      OnlineBackup  DeviceProtection  TechSupport  StreamingTV  \\\n",
       "0                0                 0            0            0   \n",
       "1                0                 0            0            0   \n",
       "2                0                 0            0            0   \n",
       "3                0                 0            0            0   \n",
       "4                0                 0            0            0   \n",
       "...            ...               ...          ...          ...   \n",
       "7027             0                 0            0            0   \n",
       "7028             0                 0            0            0   \n",
       "7029             0                 0            0            0   \n",
       "7030             0                 0            0            0   \n",
       "7031             0                 0            0            0   \n",
       "\n",
       "      StreamingMovies  PaperlessBilling  \n",
       "0                   0                 0  \n",
       "1                   0                 0  \n",
       "2                   0                 0  \n",
       "3                   0                 0  \n",
       "4                   0                 0  \n",
       "...               ...               ...  \n",
       "7027                0                 0  \n",
       "7028                0                 0  \n",
       "7029                0                 0  \n",
       "7030                0                 0  \n",
       "7031                0                 0  \n",
       "\n",
       "[7032 rows x 11 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for col in cols_boolean: \n",
    "    df[col] = df[col].eq(\"yes\").mul(1)\n",
    "\n",
    "df[cols_boolean]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "74b3572a-1171-467d-a258-639f3e485a8c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.682377Z",
     "iopub.status.busy": "2026-04-09T19:52:13.682309Z",
     "iopub.status.idle": "2026-04-09T19:52:13.694875Z",
     "shell.execute_reply": "2026-04-09T19:52:13.694435Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.682371Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7032, 29)\n"
     ]
    },
    {
     "data": {
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7032 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      gender  SeniorCitizen  Partner  Dependents  tenure  PhoneService  \\\n",
       "0          1              0        0           0       1             0   \n",
       "1          0              0        0           0      34             0   \n",
       "2          0              0        0           0       2             0   \n",
       "3          0              0        0           0      45             0   \n",
       "4          1              0        0           0       2             0   \n",
       "...      ...            ...      ...         ...     ...           ...   \n",
       "7027       0              0        0           0      24             0   \n",
       "7028       1              0        0           0      72             0   \n",
       "7029       1              0        0           0      11             0   \n",
       "7030       0              0        0           0       4             0   \n",
       "7031       0              0        0           0      66             0   \n",
       "\n",
       "      OnlineSecurity  OnlineBackup  DeviceProtection  TechSupport  \\\n",
       "0                  0             0                 0            0   \n",
       "1                  0             0                 0            0   \n",
       "2                  0             0                 0            0   \n",
       "3                  0             0                 0            0   \n",
       "4                  0             0                 0            0   \n",
       "...              ...           ...               ...          ...   \n",
       "7027               0             0                 0            0   \n",
       "7028               0             0                 0            0   \n",
       "7029               0             0                 0            0   \n",
       "7030               0             0                 0            0   \n",
       "7031               0             0                 0            0   \n",
       "\n",
       "      StreamingTV  StreamingMovies  PaperlessBilling  MonthlyCharges  \\\n",
       "0               0                0                 0           29.85   \n",
       "1               0                0                 0           56.95   \n",
       "2               0                0                 0           53.85   \n",
       "3               0                0                 0           42.30   \n",
       "4               0                0                 0           70.70   \n",
       "...           ...              ...               ...             ...   \n",
       "7027            0                0                 0           84.80   \n",
       "7028            0                0                 0          103.20   \n",
       "7029            0                0                 0           29.60   \n",
       "7030            0                0                 0           74.40   \n",
       "7031            0                0                 0          105.65   \n",
       "\n",
       "      TotalCharges  Churn  MultipleLines_No  MultipleLines_No phone service  \\\n",
       "0            29.85      0             False                            True   \n",
       "1          1889.50      0              True                           False   \n",
       "2           108.15      1              True                           False   \n",
       "3          1840.75      0             False                            True   \n",
       "4           151.65      1              True                           False   \n",
       "...            ...    ...               ...                             ...   \n",
       "7027       1990.50      0             False                           False   \n",
       "7028       7362.90      0             False                           False   \n",
       "7029        346.45      0             False                            True   \n",
       "7030        306.60      1             False                           False   \n",
       "7031       6844.50      0              True                           False   \n",
       "\n",
       "      MultipleLines_Yes  InternetService_DSL  InternetService_Fiber optic  \\\n",
       "0                 False                 True                        False   \n",
       "1                 False                 True                        False   \n",
       "2                 False                 True                        False   \n",
       "3                 False                 True                        False   \n",
       "4                 False                False                         True   \n",
       "...                 ...                  ...                          ...   \n",
       "7027               True                 True                        False   \n",
       "7028               True                False                         True   \n",
       "7029              False                 True                        False   \n",
       "7030               True                False                         True   \n",
       "7031              False                False                         True   \n",
       "\n",
       "      InternetService_No  Contract_Month-to-month  Contract_One year  \\\n",
       "0                  False                     True              False   \n",
       "1                  False                    False               True   \n",
       "2                  False                     True              False   \n",
       "3                  False                    False               True   \n",
       "4                  False                     True              False   \n",
       "...                  ...                      ...                ...   \n",
       "7027               False                    False               True   \n",
       "7028               False                    False               True   \n",
       "7029               False                     True              False   \n",
       "7030               False                     True              False   \n",
       "7031               False                    False              False   \n",
       "\n",
       "      Contract_Two year  PaymentMethod_Bank transfer (automatic)  \\\n",
       "0                 False                                    False   \n",
       "1                 False                                    False   \n",
       "2                 False                                    False   \n",
       "3                 False                                     True   \n",
       "4                 False                                    False   \n",
       "...                 ...                                      ...   \n",
       "7027              False                                    False   \n",
       "7028              False                                    False   \n",
       "7029              False                                    False   \n",
       "7030              False                                    False   \n",
       "7031               True                                     True   \n",
       "\n",
       "      PaymentMethod_Credit card (automatic)  PaymentMethod_Electronic check  \\\n",
       "0                                     False                            True   \n",
       "1                                     False                           False   \n",
       "2                                     False                           False   \n",
       "3                                     False                           False   \n",
       "4                                     False                            True   \n",
       "...                                     ...                             ...   \n",
       "7027                                  False                           False   \n",
       "7028                                   True                           False   \n",
       "7029                                  False                            True   \n",
       "7030                                  False                           False   \n",
       "7031                                  False                           False   \n",
       "\n",
       "      PaymentMethod_Mailed check  \n",
       "0                          False  \n",
       "1                           True  \n",
       "2                           True  \n",
       "3                          False  \n",
       "4                          False  \n",
       "...                          ...  \n",
       "7027                        True  \n",
       "7028                       False  \n",
       "7029                       False  \n",
       "7030                        True  \n",
       "7031                       False  \n",
       "\n",
       "[7032 rows x 29 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# One-Hot-Encoding für die drei kategorischen Spalten\n",
    "\n",
    "df_onehot_encoded = pd.get_dummies(df, columns=cols_cat) # dtype=int\n",
    "\n",
    "print(df_onehot_encoded.shape)\n",
    "df_onehot_encoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "1b125ae7-0688-49ff-a17f-0ba75392a275",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.695256Z",
     "iopub.status.busy": "2026-04-09T19:52:13.695175Z",
     "iopub.status.idle": "2026-04-09T19:52:13.698790Z",
     "shell.execute_reply": "2026-04-09T19:52:13.698307Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.695248Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['gender',\n",
       " 'SeniorCitizen',\n",
       " 'Partner',\n",
       " 'Dependents',\n",
       " 'tenure',\n",
       " 'PhoneService',\n",
       " 'OnlineSecurity',\n",
       " 'OnlineBackup',\n",
       " 'DeviceProtection',\n",
       " 'TechSupport',\n",
       " 'StreamingTV',\n",
       " 'StreamingMovies',\n",
       " 'PaperlessBilling',\n",
       " 'MonthlyCharges',\n",
       " 'TotalCharges',\n",
       " 'Churn',\n",
       " 'MultipleLines_No',\n",
       " 'MultipleLines_No phone service',\n",
       " 'MultipleLines_Yes',\n",
       " 'InternetService_DSL',\n",
       " 'InternetService_Fiber optic',\n",
       " 'InternetService_No',\n",
       " 'Contract_Month-to-month',\n",
       " 'Contract_One year',\n",
       " 'Contract_Two year',\n",
       " 'PaymentMethod_Bank transfer (automatic)',\n",
       " 'PaymentMethod_Credit card (automatic)',\n",
       " 'PaymentMethod_Electronic check',\n",
       " 'PaymentMethod_Mailed check']"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_onehot_encoded.columns.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "cd8ef306-4f02-4f3d-ae2c-228e42dea370",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.699635Z",
     "iopub.status.busy": "2026-04-09T19:52:13.699458Z",
     "iopub.status.idle": "2026-04-09T19:52:13.702817Z",
     "shell.execute_reply": "2026-04-09T19:52:13.702465Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.699627Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PaperlessBilling\n",
      "13\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['MultipleLines_No',\n",
       " 'MultipleLines_No phone service',\n",
       " 'MultipleLines_Yes',\n",
       " 'InternetService_DSL',\n",
       " 'InternetService_Fiber optic',\n",
       " 'InternetService_No',\n",
       " 'Contract_Month-to-month',\n",
       " 'Contract_One year',\n",
       " 'Contract_Two year',\n",
       " 'PaymentMethod_Bank transfer (automatic)',\n",
       " 'PaymentMethod_Credit card (automatic)',\n",
       " 'PaymentMethod_Electronic check',\n",
       " 'PaymentMethod_Mailed check']"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index_label = df_onehot_encoded.columns.tolist().index(\"Churn\")\n",
    "print(df.columns.tolist()[index_label])\n",
    "cols_onehot_encoded = df_onehot_encoded.columns.tolist()[index_label+1:]\n",
    "print(len(cols_onehot_encoded))\n",
    "cols_onehot_encoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "981310d5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "f3c2c1e2-7f45-4e6a-a2c6-9e2d3f4a5b6c",
   "metadata": {},
   "source": [
    "### One-Hot-Encoding Spalten mit Werten auffüllen. (genaue Erklärung siehe oben)\n",
    "\n",
    "Die `df[col].eq(\"yes\").mul(1)` transformiert lediglich von `\"yes\"` zu `1` und alles andere zu `0`. D.h. man könnte auch `df[col].map({\"yes\":1, \"no\":0})` nutzen anstatt `df[col].eq(\"yes\").mul(1)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "b96f4cd6-5c29-4c0b-9bd1-2908eb966ef4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.703274Z",
     "iopub.status.busy": "2026-04-09T19:52:13.703196Z",
     "iopub.status.idle": "2026-04-09T19:52:13.707152Z",
     "shell.execute_reply": "2026-04-09T19:52:13.706690Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.703267Z"
    }
   },
   "outputs": [],
   "source": [
    "for col in cols_onehot_encoded: \n",
    "    df_onehot_encoded[col] = df_onehot_encoded[col].eq('yes').mul(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "8ab24cd8-c2b2-47b0-9e65-c442832ce4f9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.707480Z",
     "iopub.status.busy": "2026-04-09T19:52:13.707420Z",
     "iopub.status.idle": "2026-04-09T19:52:13.714990Z",
     "shell.execute_reply": "2026-04-09T19:52:13.714626Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.707474Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "      <th>MultipleLines_No</th>\n",
       "      <th>MultipleLines_No phone service</th>\n",
       "      <th>MultipleLines_Yes</th>\n",
       "      <th>InternetService_DSL</th>\n",
       "      <th>InternetService_Fiber optic</th>\n",
       "      <th>InternetService_No</th>\n",
       "      <th>Contract_Month-to-month</th>\n",
       "      <th>Contract_One year</th>\n",
       "      <th>Contract_Two year</th>\n",
       "      <th>PaymentMethod_Bank transfer (automatic)</th>\n",
       "      <th>PaymentMethod_Credit card (automatic)</th>\n",
       "      <th>PaymentMethod_Electronic check</th>\n",
       "      <th>PaymentMethod_Mailed check</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>29.85</td>\n",
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       "      <td>56.95</td>\n",
       "      <td>1889.50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <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",
       "      <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",
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       "      <td>24</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7028</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>72</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.90</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7029</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7030</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.60</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7031</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>66</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>105.65</td>\n",
       "      <td>6844.50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7032 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      gender  SeniorCitizen  Partner  Dependents  tenure  PhoneService  \\\n",
       "0          1              0        0           0       1             0   \n",
       "1          0              0        0           0      34             0   \n",
       "2          0              0        0           0       2             0   \n",
       "3          0              0        0           0      45             0   \n",
       "4          1              0        0           0       2             0   \n",
       "...      ...            ...      ...         ...     ...           ...   \n",
       "7027       0              0        0           0      24             0   \n",
       "7028       1              0        0           0      72             0   \n",
       "7029       1              0        0           0      11             0   \n",
       "7030       0              0        0           0       4             0   \n",
       "7031       0              0        0           0      66             0   \n",
       "\n",
       "      OnlineSecurity  OnlineBackup  DeviceProtection  TechSupport  \\\n",
       "0                  0             0                 0            0   \n",
       "1                  0             0                 0            0   \n",
       "2                  0             0                 0            0   \n",
       "3                  0             0                 0            0   \n",
       "4                  0             0                 0            0   \n",
       "...              ...           ...               ...          ...   \n",
       "7027               0             0                 0            0   \n",
       "7028               0             0                 0            0   \n",
       "7029               0             0                 0            0   \n",
       "7030               0             0                 0            0   \n",
       "7031               0             0                 0            0   \n",
       "\n",
       "      StreamingTV  StreamingMovies  PaperlessBilling  MonthlyCharges  \\\n",
       "0               0                0                 0           29.85   \n",
       "1               0                0                 0           56.95   \n",
       "2               0                0                 0           53.85   \n",
       "3               0                0                 0           42.30   \n",
       "4               0                0                 0           70.70   \n",
       "...           ...              ...               ...             ...   \n",
       "7027            0                0                 0           84.80   \n",
       "7028            0                0                 0          103.20   \n",
       "7029            0                0                 0           29.60   \n",
       "7030            0                0                 0           74.40   \n",
       "7031            0                0                 0          105.65   \n",
       "\n",
       "      TotalCharges  Churn  MultipleLines_No  MultipleLines_No phone service  \\\n",
       "0            29.85      0                 0                               0   \n",
       "1          1889.50      0                 0                               0   \n",
       "2           108.15      1                 0                               0   \n",
       "3          1840.75      0                 0                               0   \n",
       "4           151.65      1                 0                               0   \n",
       "...            ...    ...               ...                             ...   \n",
       "7027       1990.50      0                 0                               0   \n",
       "7028       7362.90      0                 0                               0   \n",
       "7029        346.45      0                 0                               0   \n",
       "7030        306.60      1                 0                               0   \n",
       "7031       6844.50      0                 0                               0   \n",
       "\n",
       "      MultipleLines_Yes  InternetService_DSL  InternetService_Fiber optic  \\\n",
       "0                     0                    0                            0   \n",
       "1                     0                    0                            0   \n",
       "2                     0                    0                            0   \n",
       "3                     0                    0                            0   \n",
       "4                     0                    0                            0   \n",
       "...                 ...                  ...                          ...   \n",
       "7027                  0                    0                            0   \n",
       "7028                  0                    0                            0   \n",
       "7029                  0                    0                            0   \n",
       "7030                  0                    0                            0   \n",
       "7031                  0                    0                            0   \n",
       "\n",
       "      InternetService_No  Contract_Month-to-month  Contract_One year  \\\n",
       "0                      0                        0                  0   \n",
       "1                      0                        0                  0   \n",
       "2                      0                        0                  0   \n",
       "3                      0                        0                  0   \n",
       "4                      0                        0                  0   \n",
       "...                  ...                      ...                ...   \n",
       "7027                   0                        0                  0   \n",
       "7028                   0                        0                  0   \n",
       "7029                   0                        0                  0   \n",
       "7030                   0                        0                  0   \n",
       "7031                   0                        0                  0   \n",
       "\n",
       "      Contract_Two year  PaymentMethod_Bank transfer (automatic)  \\\n",
       "0                     0                                        0   \n",
       "1                     0                                        0   \n",
       "2                     0                                        0   \n",
       "3                     0                                        0   \n",
       "4                     0                                        0   \n",
       "...                 ...                                      ...   \n",
       "7027                  0                                        0   \n",
       "7028                  0                                        0   \n",
       "7029                  0                                        0   \n",
       "7030                  0                                        0   \n",
       "7031                  0                                        0   \n",
       "\n",
       "      PaymentMethod_Credit card (automatic)  PaymentMethod_Electronic check  \\\n",
       "0                                         0                               0   \n",
       "1                                         0                               0   \n",
       "2                                         0                               0   \n",
       "3                                         0                               0   \n",
       "4                                         0                               0   \n",
       "...                                     ...                             ...   \n",
       "7027                                      0                               0   \n",
       "7028                                      0                               0   \n",
       "7029                                      0                               0   \n",
       "7030                                      0                               0   \n",
       "7031                                      0                               0   \n",
       "\n",
       "      PaymentMethod_Mailed check  \n",
       "0                              0  \n",
       "1                              0  \n",
       "2                              0  \n",
       "3                              0  \n",
       "4                              0  \n",
       "...                          ...  \n",
       "7027                           0  \n",
       "7028                           0  \n",
       "7029                           0  \n",
       "7030                           0  \n",
       "7031                           0  \n",
       "\n",
       "[7032 rows x 29 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_onehot_encoded"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3094b418-ecb1-4f56-b29e-b34173e56188",
   "metadata": {},
   "source": [
    "## Split the Data to x_train, x_test, y_train, y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "b30f3010-ae54-40cf-bd72-0fc8b88a5d38",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.715431Z",
     "iopub.status.busy": "2026-04-09T19:52:13.715343Z",
     "iopub.status.idle": "2026-04-09T19:52:13.717969Z",
     "shell.execute_reply": "2026-04-09T19:52:13.717479Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.715425Z"
    }
   },
   "outputs": [],
   "source": [
    "# Split X and y\n",
    "X = df_onehot_encoded.drop(columns = [\"Churn\"])\n",
    "y = df_onehot_encoded[\"Churn\"].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "e1c15d59-37c5-4bec-a577-38f4ae248316",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.718311Z",
     "iopub.status.busy": "2026-04-09T19:52:13.718232Z",
     "iopub.status.idle": "2026-04-09T19:52:13.724848Z",
     "shell.execute_reply": "2026-04-09T19:52:13.724481Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.718305Z"
    }
   },
   "outputs": [],
   "source": [
    "# Splitting the data into train and test sets\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = 0.30, random_state = 42, stratify=y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "ed594414-a54d-4a20-a953-03cd2cf2aac9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.725244Z",
     "iopub.status.busy": "2026-04-09T19:52:13.725172Z",
     "iopub.status.idle": "2026-04-09T19:52:13.931226Z",
     "shell.execute_reply": "2026-04-09T19:52:13.930422Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.725237Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def distplot(feature, frame, color=\"r\"):\n",
    "    plt.figure(figsize=(8,3))\n",
    "    plt.title(\"Verteilung für {}\".format(feature))\n",
    "    ax = sns.distplot(frame[feature], color= color)\n",
    "\n",
    "num_cols = [\"tenure\", \"MonthlyCharges\", \"TotalCharges\"]\n",
    "for feat in num_cols: distplot(feat, df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e823d8f-d538-42c8-9edc-944a6e5a82de",
   "metadata": {},
   "source": [
    "### Überlegung: Welchen Scaler sollte ich nutzen?\n",
    "\n",
    "Da die numerischen Features über verschiedene Wertebereiche (value ranges) verteilt sind, können wir hier den Standard Scalar nutzen, um sie alle auf den gleichen Bereich runterzuskalieren."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95dc68f7-14b6-4e38-93c9-4d617807dcb0",
   "metadata": {},
   "source": [
    "## Normalisiere die numerischen Attribute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "ee55e0a7-5331-4bc0-b41c-1fe106fe6890",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:13.931723Z",
     "iopub.status.busy": "2026-04-09T19:52:13.931568Z",
     "iopub.status.idle": "2026-04-09T19:52:14.110882Z",
     "shell.execute_reply": "2026-04-09T19:52:14.110533Z",
     "shell.execute_reply.started": "2026-04-09T19:52:13.931714Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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WrZtD2g8AAADHcoqgVkdaJ06cKMOHD5e2bdvKN998IytWrDCBakpKirnUfSo+Pl4++ugjWbRokURGRprUgi+//FI++eQTk4cLAAAA9+PwnFrl4eEhM2fONFtdcXFxx9Srvfjii80GAAAAOM1ILQAAAHAqCGoBAABgeQS1AAAAsDyCWgAAAFgeQS0AAAAsj6AWAAAAlkdQCwAAAMsjqAUAAIDlEdQCAADA8ghqAQAAYHkEtQAAALA8gloAAABYHkEtAAAALI+gFgAAAJZHUAsAAADLI6gFAACA5RHUAgAAwPIIagEAAGB5BLUAAACwPIJaAAAAWB5BLQAAACyPoBYAAACWR1ALAAAAyyOoBQAAgOUR1AIAAMDyCGoBAABgeQS1AAAAsDyCWgAAAFgeQS0AAADcM6hdvXp187cEAAAAaM2g9vzzz5fOnTvLjBkzZM+ePU19bQAAAMBxQe2OHTtk7NixsmTJEjnttNNk6NCh8o9//EPy8vKap1UAAABAI9ikCbp27SozZ840m6YiaHA7bdo0+cMf/iBXXXWVTJgwQS6++GLx8PBoytMDAAAY89PSWrUnbo2JoefddaLYueeeK6+++qps3rxZzjjjDHnrrbfk0ksvlQ4dOpj0hIKCguZpKQAAANASQW1paam8//77ZnRWR2/37dsnjzzyiKxdu1buvPNOmTt3rowZM+akz2O322X69OkSExMjAQEBJlDesmXLCX9m8eLF0qdPH/P4du3amVFiAAAAuKcmpR+sWbPGpBy88847UlRUJKNHj5bly5fLsGHDqh+jo7b9+vUz953M7NmzZeHChbJy5crq1IYRI0bI9u3bJTAw8JjHP/vss/LSSy+ZNgwePFiKi4vNYwEAAOCemhTUDhkyRM466yx58skn5frrr5fg4OB6H9erV68GjdTqiK7m5OrIq5o1a5ZJaVi2bJmMGzeu1mN1MpqO6r755ptmgpp5EzabDBgwoN7nTk9PN1td27Zta9B7BQAAgIsGtRoQdu/e/aSPi4+Pl0WLFp3wMbm5uZKUlCSDBg36/0bZbNK/f3/ZsGHDMUHtd999J0ePHjUVGLTygv68Pvbpp582I8N1zZs3z+T2AgAAwHU1KadWJ4Jt2rSp3vs0F1Zr2DZUVRmw0NDQWvvDwsLqLRGWlZVlLj/88ENZtWqVJCcnS2JiolxyySUmwK1r8uTJsn79+mO2pUuXNriNAAAAcMGRWh1Z1TzW+ugoampqaoOfqyp1IScnp9b+7OxsiY2NPe7jH3jgger7n3jiCXnxxRfNKK4G3DVFR0ebDQAAAK7L1phAtubqYevWrZP8/Pxaj9FAV0dAExISGtyAkJAQ83itmKCTvlRZWZls3LjxmNQDpakGihq4AAAAaHRQ+9prr1XnpmpAOXXq1OMGqQsWLJDGmDJliqmAoNUTunTpIo899ph4e3vLqFGjjnlsx44d5eqrrzajsxrgatqCtkvTFXQCGwAAANxPg4Pau+++WyZOnGhqymrO7AcffFA9alrFx8dHoqKiGj2KqpUPjhw5IsOHDzd5tGeeeaasWLHClPNKSUkxVRS0ZFhVtQMNsLU9PXr0EE9PTxk4cKApB3a8KgwAAABwbQ0OanUEVje1d+9es1CCjqY2Bw2Cq5bdrSsuLu6YNAcNXrWurW4AAABAg4NazafVU/8ayJaXl5vVw06kMRUQAAAAgFYJanWlr++//97Uk9Xrx0sx0PQEvU8DXwAAAMCpgtqvvvrK5LZWXQcAAAAsF9Sed9559V4HAAAALLmimC6usH379urbmmrw8ssvmzJfy5Yta872AQAAAC2zotjNN98svXv3lmeffbZ6da/nn39e+vbtK/Pnz5dXXnnFPAZoLdmlpbIhP1/SS0rkQEmJHK2okBAvLwnz9pYYHx8ZEBhorgMAANfUpKB2w4YNZsGEqlFaXWzhmWeekbvuusssivC3v/2NoBatYm9hoXyRkyM/HTkiFZX7fD08JMhmM8FtaUGB2fdOZqZ09fOTc0JC5DdBQeLZyFrKAADABYNaXShBV/BSWhEhNzdXbrjhBnP7nHPOkccff7x5WwnUUVpRIe9mZsrXubnmdk9/fzkvJEQ6+/lJsJeXqcChlTh0xHZHQYGsO3JENh89KrsKC+Xzw4fl6ogI6RsQwHLLAAC4c1AbHx9vglld4UtXFktMTJR27dqZ+7KysiQgIKC52wlUSy8ullfT02V/SYl08/OTMe3aSayv7zE9pIFtoJeXDAgKMltBebl8np0tX2Rny9y0NOnt7y/jo6LoWQAA3DWo/eMf/2gmhb3zzjsmFaHmyl5ff/21ya0FWsLuwkL52/79UmK3y8i2beXS8PAGpxL4e3mZEdoLQkPlg6ws+T4vT2YmJUkXPz+5JjKSXxgAAO5W/eDWW2+Vf//73zJmzBhZuXKljB8/vvq+8PBwE/QCzS25qEheSE0Vu4jc3aGDXN62bZNyY0NsNvldVJRMjo42t6/95ReZumOHSWkAAABuNFJbVau2vnq106dPP9U2AcdILS42I7TldrtMjY2VHv7+p9xLmpKgo7SfHT4sL6elydaCAnm3d29pS5UEAADcJ6gtKyuTH374wdSsLSoqOiaXcdy4cc3RPkCOlJXJC/v3S1FFhUxppoC25qjt5337yt27dpk820Hr18unffpID/LCAQBw/aBWJ4lde+21kpaWVu/9BLVoLhV2uyzMyJCc8nKTMnB6CwSb3p6e8nK3btInIECm7twp52zYIJ/17SuDgoOb/bUAAIAT5dRqjdq4uDhZt26dHD16VEpLS2ttJSUlzd9SuCWtVqBpAUOCg+WsFg4yb4uNlY/69JGCigoZtnGjrDx8uEVfDwAAODio1SVyH330URkwYID4+fmJl5fXMRtwqrSm7EdZWWZFMC3b1Rp08tmX/fqJj6enXPHzz/JBZmarvC4AAHBAUKvBbEpKyim+NHB8JRUVsigjQ2weHnJLdLQJMlvL4JAQ+W///hLh7S2//eUXefvgQX5VAAA4uSZFCn//+99l7ty58u6778rhw4eloqLimA04FcsPH5as0lIZGREhMfUsrNDSegUEyNeJiRLl4yM3bt0qSzMyWr0NAACghSeK9enTx1xqndrjKS8vb8pTA5JRUmLyWTv4+Miw0FCH9Ug3f3/5un9/uWDjRhn/669SarfL7ypr2wIAABcIanUFMa1wADQ3u90ubxw4IPqV6Mb27cXLwceZ1rHVEdthmzbJpO3bTWB7a0yMQ9sEAACaKaidOHFiU34MOKk3Dx6U7YWFMjQkxASUzqBTVWC7caNM3rHD5PtO7dDB0c0CAAA1nNLsm02bNsmiRYtk5syZklGZc6iVEXJzc0/laeGmiisq5IE9e8Tf01NGRUSIM4lr08akInTz85M7d+0yq5sBAACLj9Rq0Dp+/Hj5+OOPJSQkRPLy8uSKK66QqKgos0xuTEyMPPfcc83fWri0eWlpklxcLKMjIiTACcvCxfr6yqrKVARdgUyX7P1Tx46ObhYAAGjqSO1dd90lW7ZskbVr10pmZqbJg6xy6aWXyooVK+hcNHop3MeSk01N2gscODnsZKJ9feWrfv2kl7+/3LN7tzxDaTsAAKwb1H700Ufy17/+Vc4444xjJozFx8dTwxaN9vz+/ZJZWiqPJiS0ak3apojSwDYxUXr7+8uf9+yRJ5OTHd0kAADcXpOih7KyMgkICKj3vpycHPF1QF1RWFdmSYnM3rfP5Kv+LipKrKCdj48JbPsEBMhf9u6VxwlsAQCwXlA7ZMgQmTdvXq19VSO2S5YskfPPP795Wge38Oy+fXKkvFxmduokNicfpa0p0sdH/tOvn/QLCJCH9u6VR/burZWKAwAAnHyi2FNPPSXnnnuuWS531KhRJqDVYPb++++XH374QdasWdP8LYVLyiktlblpadLD31+ui4wUq4nw8ZEvExPlks2bZVZysuSUlcmcrl3FkzrOAAA4f1Dbr18/WbdunSnl9corr4iXl5e8+eabMmzYMPnxxx+lW7duzd9SuCQNaHWU9v64OIcFgvPT0k75Oca2ayd5ZWXyYmqq/JiXJxOioo67cASLNwAA4CRB7ZEjRyQtLU1Gjhxptvbt25tJY8fLswXqU1BeLnP275c4X1+5sV07S3eSn5eX3BkbKwvS0+WHI0ekqKJCbomOFm8LpVMAAOA2Qa1OAtNyXm+99ZaZLKb5g1W5tN7e3nLTTTeZ+rRauxY4mX+kp5uKBy927eoSwZ9WbbgtJkZey8gwge0LqalyR2ystHGB9wYAgMsEtUVFRSaPNikpSe655x656KKLJDY21gS2qamp8vnnn8vcuXNlw4YNJqeWCgg4kdKKClPxoJ23t9wcHe0ynaUpBxOjoszI7aqcHHlu3z4T2IbYmnRSBAAANFCD/9JqtYPk5GQzEaxnz5617uvevbvJpx03bpycffbZsmDBApk6dWpDnxpu6N3MTEkpLpbHO3UyAaAr0dzgMZGREujpKZ8cPixPpqSYwLYDpe4AAGgxDT4vumzZMrntttuOCWhr6t27t0yePFnee++95mofXJCO7utiC36Vp+tdkablXBkRIRPbt5fcsjJ5OiVFfs7Pd3SzAABwWQ0Oan/55ReTfnAy5513nnlsY4Oc6dOnS0xMjJlspq+jy/CeTF5eniQkJJgAQnN8YQ1r8vJk3ZEjpkJAuLe3uLLBISFyd4cOYvPwkJfT0uTL7Gxq2QIA4MigVieJtW3b9qSP08fk5uY2qhGzZ8+WhQsXysqVKyUrK8ss7jBixAjJP8nI1t13321SH2AtWvFA/SE2VtxBN39/U7JM84ffycyUKTt3mpxiAADggKC2vLzc1KM9GR011cc2hk4wmzZtmvTp00f8/Pxk1qxZUlJSYlIejufjjz+Wn3/+We69994TPnd6err89NNPx2zbtm1rVBvRPJKLiuT9zEwZERYmPd2oBJwuq3tfXJxZZOLvaWkyYvNmySgudnSzAABwGY2akn3rrbdKUFDQSWvYNoaO6mpFhUGDBv1/o2w26d+/v6mkoJPP6jp06JCZiPbpp5+akd2TTXCbMWNGo9qElvNyaqroGKWeknc3AV5eZnR6y9GjZtGJxHXr5I1evWRYWJijmwYAgPsEtRMmTGjwkyYmJjb4sZoXq0JDQ2vtDwsLq76vrttvv11uueUWOf3002XVqlUnfH6duKYLRNSlI7Vjx45tcDtx6o6Wl5vFCXS08uLwcLfsUi359XK3bjI0JERu2bFDhm/aJNMTEuSh+PjjrkAGAACaMahdtGiRtITg4ODqnN2asrOzTR3cunThh927d8sbb7zRoOePjo42GxzvzQMHJKesTB7r1MlhS+I6izG6Cl9QkFz3yy/yaFKSfJOTI//s1Uva+/g4umkAAFiSw5c60tXHtILB2rVrq/dpJYONGzeaFIS6VqxYIb/++qtERUVJRESEXHXVVWa/3n7ttddate1oXIULPeUe4Okp49q3p+tE5DR/f/l+wABT1uzLnBzpt3atLD90iL4BAMCKQa2aMmWKqYCgZbwKCwtNeS9ddnfUqFHHPPb555+X7du3m6BXt1dffdXsX79+vVx77bUOaD0a4scjR2RDfr6Mi4qSYFbXqtbGy0te6dZN3uzZUwoqKuSyn3+WSb/+KjmlpRxYAAA0glOs3amVD3SC2fDhw00e7ZlnnmlGZAMDAyUlJUV69eoly5cvl6FDh5pcW92qREZGmktNVdAJZnBOc1NTzeXtLrrYQnOkI5wdEiK3bt8uizIyZOXhwzKvWze5IiLC0U0DAMASnGKkVsuAzZw5UzIyMqSgoEBWr15tynupuLg4U69WA9r6nH/++ebUNgGt8zpUWipvHzwo54SESN/AQEc3x2nFtWkjy/v2lX907y755eVy5ZYtMn7bNjnMqC0AACfF0CZa3KL0dCm22xmlrTQ/Le2kffZAXJwsPXhQXj9wQD7KypLRkZHym6CgRk+wu5WRcQCAm3CKkVq4rgq73Sw2EOntLddUporg5MK8vWVqTIxMbN/e1PVdnJEhT+/bJ0lFRXQfAAD1IKhFi/oqJ0d2FxXJ76KixNeTw62xaTmDQ0JkZkKCDAsNNauxPZmSIksyMiSvrKzFfmcAAFgR6QdoUQsqT7XfQq3gU1qJ7Pp27cyCDW9nZsq3eXmyPj9fLgsPlwtCQ8WHLwsA3EBuWZnsLCyUXYWFklFSYuqe62YXER8PD/NZGO3jI/G+vpLQpo1Z6Mebz0e3QlCLFpNZUiIfZGWZUcau/v709CmK8fWVu2NjTWm09zIzTd9+kZ1tgludhMeHNwBXs6ewUJYfPizr8vJkf0lJ9X4NYsNsNonz9TWrMZbY7VJYXi5bjx6Vn48eNY/RuuiDgoNlSEiIdPT1deC7QGshqEWLeS0jQ0rtdiYrNXNKwoCgIOkTECD/zc2Vzw4flrcyM+Xz7Gy5vG1bGRwczHK7ACytrKJC/nXokLyYmiqrKlcb1QBVP99O8/Mzm87T0M/DukorKiS1pES2FxTImrw8kwKn28CgIBkVESFtvb0d8I7QWghq0SK0zNqC9HRpa7PJ1dRabXY6KntBWJgZgdAPbK1rq5US9HJEeLiplMDILQAr0ZFW/bvx7L59klJcLN4eHnJDu3YS4e0tPf39G/SFXT/3NPVAt4vDwmRvUZH58r/2yBHZmJ9v9ukAQEOeC9ZDUIsWsTo3V3YUFso9HTowQawFaQ6ZBrHnhoTIf3Jy5N/Z2dVlwDTf9trISAlnZAKAkwezuoz6MykpcqC0VNp5e8uMhAS5NTpaonx9G1QGsT46ktvZz0+mxsbKtqNH5Z3MTPn08GH5taDAzPPQKjNwLUxHR4uo+hC6hTqprcLPy8uMPvy1UycTyOooxEeHDknHNWvkDzt3mrw0AHAm5Xa7LE5Pl24//ijTdu8Wm4eH/K1rV0k66yx5JCHBBLTNpWdAgDwYHy/Dw8JMRZ5ZycnyS2XuLVwHI7VokRXEdCKTjh52Z4JYqwe3F4WFmcl5644ckZ/y801e2kupqWZEV0cnrmzbltQEAA5NT1tx+LDct2ePmdQVbrPJ8126yO2xsS16Zk+D5usiI01Ors750M/FiVFR8pvg4BZ7TbQuglo0O62jqjNRWc3KcXSkVj+oX+3eXb7MzpaX09Lk46ws84ekvbe3TIqOlt9HR5tTcwDQWtYfOSJ/3r3bpEu18fSU++Pi5L6OHSW0FVMBEgMDJSouTubs3y+LMjKksKJCzg8NbbXXR8shqEWLTBDTUivXMEHM4TSnbHh4uNnSiovNymT6+/lrSorZzgsJMTVwdbW3dj4+jm4uABe1t7BQHty7V948eFB0ipYuyKMLy3Ro08Yh7Yny8ZF7O3Y0ga22SasmXBQe7pC2oPkQ1KJZfZubK9sKCuSu2Fhp4+VF7zpZndsH4uPNyIiO3mpw+/GhQ/J1bq5M3blThoWFyfWRkTKayWUAmklWSYk8npIiL6emmhKPWlf7yc6dpU9goMP7WMt7aWD7/P798l5WlgR6eZlVHGFdBLVoVvPT080lE8Scl6eHhxmR0O1IWZmpB/n2wYMmNUEXc7h9504ZEhwsl7VtK5eGh8vpAQH11oMEgOM5Wl5uRkGfTkmRvPJyOTMoSJ7u3NmUInQmwTab/CE2Vp7et0+WHDhgAltYF0Etmk12aam8m5kpZwcHS++AAHrWAoJsNrmpfXuz5ZSWyodZWWaSn+a76QiuTuTo4Osrl4SHy4iwMBkaGirtSVMA3NqJSmxpRQNdGOaTQ4dMMKvluTTFaUBgoFniVjdno6W97urQwQTgOjAzLirKrEQG6yGoRbPR+qhFFRVMELMonagxMTrabEXl5SaoXX7okFmi8tX0dLOpbn5+ZlneoSEh5rKLnx8juYCb02BWFzj49NAhOVhaKsFeXnJju3bmM8IKCx1oju2dsbHy7P79MnrLFll/5pl8gbcgglo02wSxeWlpEuLlZUqmwNo0H1pLgOk2p3L9dc3D1REY3RZmZJhN6apxunSvjsQcLisza7HrCkCa5tDSqLABOJZOsPo+L09WZGdLVmmpqWgwsm1buTAszFy3kk5+fjK2fXtTEeG6X36RL/v1o/yhxRDUotkmiG0tKDDfdP3JSXI5WvpLt6pc6dTiYvM7/yY319TD1UBXVzOron/Mon18zOhHzcvWCnYBtKySigrz//7z7GzJLiuTgMpgVktjBVj4b8BZwcFmlPlvqalyz+7d8sJppzm6SWgEglo0i3mVp6Yns4KYW4j19ZXftmtnNlVWUSHbCwv/t2Z7UZHsKy6W9JISs+563eLnWie3KshtX2Oz2qgO4K6luT7IzJRv8/Ikv7xcgry8ZHREhJwXGuoy/4ef6dJFNlYuXKNzRMa0b+/oJqGBCGrRLCuIvXvwoMmdYoKYe7J5eprfvY5y6FZzBrQGtxklJeYyvbjYXF+fn3/Mc2jqiga3GvBqzdwob29zqaO7VsjJA1w5X1ZzZf+elmaqpNhFzASwy8PDzee+j4sEs1W8PT3l7d69pd/atTJ5xw7zmZbAQjWWQFCLU6bLDRbb7XIbo7SoQ09DdvXzM1tNxRUVclCD3dLS/12WlMiBkhJJKS6WHXVmR+uJzEgdzfX2/v+R3crrmstNuTGg+en/LV3CViva6CqR+n9T/y9eHRFh8uZ7+Pu7dCqRfr681rOnXLJ5s9y0bZt8nZhovrzDuRHUolkmiOlkIVYQQ0Pp+u4d27QxW93jScsAaYBrttLS6uv6B3bT0aO1Hq9F3bUaQ3d/f+np7y99AgJMUXf9o0uwCzT+83xTfr4JZLW0X9UXzBgfH5keH29y6jX16EQlvVyJTpT9U4cO8tz+/TIrOVlmdOrk6CbhJAhqcUpW5eSYD757OnRgBTGcMg1EQ2w2s3Xz9z/mFKjOrtZR3apRXh050lzeH48cqfVYneihi0ZUBbnmMiDA1KMEUHvFL/0c/yonR1YePiy7K/PgNQ3ojpgYuc5CZblawhOdO5u63Y8lJ5vFaM5ixTGnRlCLU6I5VorSSmhp+ke1Kv2grsLyckkrKTFVGVJLSiStuNiMOH2Xl1frcaE2m8T6+JjRJrNV5vBqDl1DcJzD6iOxyUVF8lN+vqyuDGQ31zj70dHX11Sw0bKMZ7txIFv3rNI/e/aU/uvWycRff5UNZ54pfhau7uDqCGrRZDpatiwrS4aFhh4zqga0Jv0jo4tA6FbzD3huefn/At3KYFcvdWT3l4KC6sdpOKuBsp5i1UC3qgSZTlLTag1wDa19yrw1vwDVfW967BdUVEhmaamZoLmvsiLJ/uJis7/mGY2BQUHSvTKFJ9Lb25wt2VZQYDb8T6+AAJnVqZNZYfHhvXtldteudI2TIqhFk2mB6lK7nTJecEr6x1lHZnWrWZVD0xj0j31q5R/5qoBXKzLUrMpQFezWrLP7m+Bgk8PLSA0cRQNWrQureeYZldsX2dmSW1Zm0nP02NbLwhrBq/L18DA57Lrsteacd2rTxhzT5J43zD0dO5pSZppfOyoyUoaQhuCUCGrRJBV2uxkd0LIuOhsWzsldJnQ0hp5S1SBVtzOCgqr36xLPVUGClh4zJchKSmRDfr4pYaT+kZEhOnbbuU0bM/tbqzp0qbEltGljTlfCvekXJw0ytaRdQXm5HK2oMNertxq3C05w3zH3V1SY56sdrv4/PTbDbDaTRqCjrloOT7+Y6W0WPjn1z43FPXpI4rp18rtff5VNpCE4JYJaNImODOwpKpL74+JcrkYh3JMWjtegVLe6y4BqFYaaga5uWq+z/DhBhQYUuoXrZrOZCWq6X683NH9XkcPb+qOg+uVGFxWo2jSQ1BJ0OvJZVON6ceXtmtd1K7Hbpcxulyk7dza5Hd4eHqYcnq7SpSs0BttsZlTV7PPykrYarFYuYqKbTpTUVIKwRh5faJweAQEyszIN4fHkZHmsc2e60MkQ1KLJE8T0D/gt0dH0IFyaBgl6yla3umcr9DSwnu7N1IoMlad99XZyZe5ufYIqgw+zVQa94ZVpElr1QQMYV1mZyRlGTA9V/k52FBTIkRrB6vGua0DaUPp7auPhYUbn9feqX2T0S77e7hsQUB2EVgWnVder9x/nvsYGpofLyprQO2iKP3boIG8cOCBP7dsnY9q1k9MDA+lIJ0JQi0bTmeX/ysqSi8PCpDOrrMBNaeF5HTHTTVMR6o74aYCkwYYGvodLS81l1XXdr/m8xzuNrPmPGuAuPXCgOp+35qVuEZWv3Vz5vc6eqqJ9qou81BxFPSYoLSuT/IoKOaKXlafu7Q0ITAMrv2joaXq9rgFqYOWmQaYJXutsPh4eJ1x8gFF216RfOBZ07y6/+eknuXXHDvlv//4uvQiF1RDUokmjtHra9fbYWHoPqIdOvgmy2cwWf4JRxDwNciu33MpN92nVBr2uM9C/yc09YR/7e3qa4FaD3KpA11zabNW3NUDWQC248rLqemvn/+rods3T9kV1rlflj5rT/jVTACov66Z71KWhRVUwqpUsqq7XDFLNdZtNAiuDWU7Xo7EGBgeb0mcvpKaaxYf4W+g8CGrRKPoHSf8Ta97hFW3b0nvAKUw8Mbm23t7S5QSjfSant2oCW40Z74cq0x0OVc5619u7CgvNqGVjcjerAj4NKrWEmbbLVs+mAaOOepqRz8pT9DVHQXXUWauhaHv1Uk/j17zU/TrS2lAelQG7tk0D87g2bWqNnuqpehOga4BauV8fz6gZWsNjnTrJB1lZcv+ePXJVRITE1ElPgmMQ1KJR3jl40OQOzo6LozA30Fo5vVqKqc4EtuMpqaj4/4C38lKXHtZgV0eB9dJsOipceV1HQnUiXFnlz2sgWndTNU+yetS41JFpj8ogWQNgvdR260hwYOVt3V/z9L1f5WZue3lV39aAlQAVzk6/TL182mly1ZYt8oedO+W90093dJPgDEGt5kk9+uijsmDBAsnNzZUzzjhD5s6dK6fXc4AcPHhQ7r33Xlm9erVkZmZKRESE3HDDDebnffmW1Cq/q7/t329GQyZFRbX8CwJoNJ2oFK2LSDTyM9HZc2oBZzMyIkKuiYiQ97OyzDwTvQ3HcvgU29mzZ8vChQtl5cqVkpWVJUOGDJERI0ZIfo0i6FV0X/fu3eWLL76QvLw8c/npp5/Kfffd55C2u5vv8/JMcfpx7dubU6YAALizF047zZRTu2PnTnP2A24e1Oqo7LRp06RPnz7i5+cns2bNkhJdfnXZsmMe27lzZ3nggQekS5cu4unpKV27dpVJkybJV1995ZC2uxtNild3dujg6KYAAOBwmkv7ZOfOpprJQ3v3Oro5bs+h6QeabpCUlCSDBg2q3mez2aR///6yYcMGGTdu3Emf4/PPPzePP5709HSz1bVt27ZTaLn72V9UJO9lZsqw0NBaS44CAI5FOof7mBwTI68fOCAvpaaaM5lnBgc7ukluy6FBraYQqNDQ0Fr7w8LCqu87ER3V1eB37dq1x33MvHnzZMaMGc3QWvc2Z/9+M1lE178GAAD/oxU35nXrJgPWr5fJO3bIDwMGiI0FVNwvqA2u/DaTk5NTa392drbEnqQG6sMPPyyLFy+WVatWSYcTnA6fPHmyjBw5st6R2rFjxza57e5E62XOT0+X3v7+cml4uKObAwCAU+kTGCj3dOhgVhrTEdu7GQByv6A2JCREEhISzEjr4MGDzb6ysjLZuHHjcVMPdAb+1KlTzcSyb775xvz8iURHR5sNp3YaTcv+TOvY0ZTuAdA6OIUNWMcjCQnydmamPJyUJNdERkrHBpbhgwtNFJsyZYqpgLBlyxYpLCyU6dOni7e3t4waNeqYx2rAq6OrOjrbkIAWp05rVmoZrxgfH7mxfXu6FACAevh7ecnc004zq9/9Ydcu+sgdg1qtfDBx4kQZPny4tG3b1gSrK1askMDAQElJSTGXuk99++238sYbb8ju3bvltNNOM/dVbWgZbx48KKklJXJXhw6m/iUAAKjfpW3byvWRkfJhVpZ8mJlJN7nb4gt6OnvmzJlmqysuLq5WvdrzzjvPpB+g9dZpfyYlxSxFqbM7AQDAiT3ftausOHxY7ty1Sy4MCzOrj6F1MPSG4/ogM1N+KSiQ22NiJIT/lAAAnFR0jdq1jyQl0WOtiKAWxx2lnZmcbJbE1QliAACgYW6NiZGzgoPlhf37ZV0DSpSieRDUol6aD/Tz0aMyJTZWIn186CUAABoaXHl4yPxu3czlzdu3S2lFBX3XCghqUf8obVKS+DFKCwBAk2vX/iUuTjYfPSpP79tHL7YCgloc419ZWbLp6FGTS9ueUVoAAJrkwfh46eXvbwaKth49Si+2MIJa1FJut8v0pCRp4+kp95JLCwBAk/l6eso/uneXUrvdpCHo31i0HIJa1LL0wAFzquTuDh0kyteX3gEA4BScFRJiar1/n5cnz5OG0KIIalGtsLxcHtq7V9rabHJ/XBw9AwBAM3i8Uyfp5ucnD+7dK7+QhtBiCGpR7YXUVFNX76H4eOrSAgDQjEvovtajh5TZ7TJ+2zaqIbQQgloYWSUl8kRysnRq00Zuj42lVwAAaOY0BD0L+lN+vjyWnEzftgCCWhiPJiVJXnm5PNGpk0lsBwAAzWt6QoL0CwiQx5OT5dvcXLq3mRG9QNYfOSKvpKXJ2cHB8tt27egRAABagI+np7zRq5e5vHHrVskuLaWfmxFBrZvT8iK379ghHiLySuXqJwAAoGX0CgiQv3XtKinFxXLL9u1ip8xXsyGodXML0tJk7ZEjptxI38BARzcHAACX9/voaLkuMlLez8qS+enpjm6OyyCodWMHS0rkL3v3SqyPjzyakODo5gAA4BY8PDxkfrduktCmjfxh505Zm5fn6Ca5BIJaN6WnOybv2CE5ZWUyp2tXCbLZHN0kAADcRqi3t7zfu7dJ+xv9yy9moAmnhqDWTS3OyJAPs7Lk+shIuSYy0tHNAQDA7QwICpJ53bqZGvHXb90qZRUVjm6SpRHUuqG9hYXyh127TNrB3G7dzGkQAADQ+sZHRcnU2FhZlZMjf9y9m4ljp4Cg1g2rHYz/9VfJLy+XRT16SLi3t6ObBACAW3uuSxc5PzRUXkpNlef373d0cyyLoNbNPLhnj/w3N1fujI2Vi8LDHd0cAADcnrenp3zQu7f08veXe3bvlncPHnT7PmkKglo38vbBg/LUvn1yVnCwPNOli6ObAwAAKoV5e8tnfftKlI+PjNu2Tb7OyaFvGomg1k1sys+XSb/+av6z6GxLlsIFAMC5xLdpI5/26WNWHLt882aW0m0kglo3kFZcLFdv2SKldrs5vRHj6+voJgEAgONURFjet6+5fsnmzbImN5d+aiCCWheXVVIiF23aJElFRaZsyOCQEEc3CQAAnMCQkBAT2FbY7Saw/YZUhAYhqHVheWVl5j/D1oICebZLF/lddLSjmwQAABpgaGioSUXQyrU6OPV+Zib9dhIEtS7qcGmpXLp5s6zPz5fp8fHyp44dHd0kAADQCOeHhcnXiYkSarPJdb/8Ii9R7uuECGpdUEpRkZyzYYN8l5cnf+7YUaYnJDi6SQAAoIk5tmsGDJDT/Pzkzl275OZff5XC8nL6sh4EtS5m45EjMvinn2RbQYEp5vxUly6sGAYAgIV18vOT7wYMkEvCw2VhRoacvWGD7C4sdHSznA5BrYuw2+0yLy1NBm/YIFmlpfJWr17yR1IOAABwCW29vU2O7YyEBFOmM3HdOvl7aqqZTIb/Iah1AdmlpXL91q1y244dpg6t5t9c366do5sFAACakaeHhzySkCCf9+0rYTab3L5zpwzbuFF2FhTQzwS11qbfzhalp0v3H3+UdzMz5ZqICNlwxhlyFmW7AABwWcPDw2XLwIFye0yMfJ2bK73XrpW7d+6UQ6Wl4s4YqbVoqoEun6eTwSZt3y4eIvJajx7ybu/eEurt7ejmAQCAFhZss8ncbt1kdWKiJAYGyt9SU6XL99/Lo3v3SmZJiVv2P0GtxUZmlx86JOdu3Cjnb9woP+TlyZ2xsbJ90CAZHxXFhDAAANywnu33AwaYuTSadzsjOVnivv9ebt+xw+TeuhOboxuAk9tTWChLMjJkcUaGJBcXi7eHh/w+Olru69hRuvr704UAALh5ru317dqZNMQPsrLkmX375O9paWbrFxAg46KiZFREhHT28xNX5uksp9OnT58uMTExEhAQIOeee65s2bLluI/Pzs6Wm266SUJCQiQ0NNRcz3GhJeQKystlVXa2/GXPHumzdq10+eEH882r1G6Xv8TFye7f/EYWdO9OQAsAAKrZPD3lt+3ayY8DBsh3/fvL5OhoSSoqkmm7d5tYouePP8o9u3bJR1lZLpmi4BQjtbNnz5aFCxfKypUrpWvXrjJz5kwZMWKEbN++XQIDA495/NixY6W4uFh2795tbo8ZM0YmTJggH330kVhJWUWFpJeUyJ6iItly9KjZ1h05Ihvz86WsskRHO29v+V1UlFwXGSkXh4eLl4dm0AIAANTPw8NDBoeEmG1O166y4vBh+VS3Q4fkuf37zaa6+vmZkdy+gYHS099f4tu0kYQ2bSTS29uSKY1OEdTOnTtXpk2bJn369DG3Z82aJa+++qosW7ZMxo0bV+uxycnJ8tlnn8nGjRslIiLC7Hv22WclMTFRUlJSJC4uTpxRUmGhvJiaKvuKi/+3FRWZgFbXdK4pwttbLgsPlyEhIXJeaKgMDAoypxUAAAAaq42Xl1wdGWk2nZuz9ehR+TYvT77JyTEDacuysuT9rKxaP+Pn6WkC3HhfXxOXhHt7mxJi1Zc2m1wQFiYBXl5O9QtxeFCbm5srSUlJMmjQoOp9NptN+vfvLxs2bDgmqNVg1tfXV/r161e9T6/7+PiY++oGtenp6WarSx+rtm3bJq1Ba8g9t3Wrua6J3O18fKSbt7e09/ExtWW7+PmZJfD04PHQkhx6gGVlyf9a6V5SMjMd3QQAgJv6KSNDXN3Ayk28vaXQ09PM3dEBNx1sS9PL0lJJLy6Wr0tKpKii7vDb/+hCEFG+vi3e1qo4rbABK6g5PKjNy8szl5obW1NYWFj1fXUfr7m0denP1/f4efPmyYwZM477+prK0NoOVW6tE04DAICGepyuapDLpXXpAOiQIUOcO6gNDg42l3UneulksNjY2Hofr6O7denPVz1XTZMnT5aRI0ces1+fX6N/HRH2c/HZgI2hfaKB/tKlS6Vnz56Obo7ToX/oI44h/o/xGeS8+Ix2vf7REVoNaHWu1ck4PKjVUdeEhARZu3atDB482OwrKysz6QF1Uw+U5s7qJLHNmzdL3759zT69XlJSYu6rKzo62mz1ufDCC5v9/bgKPdgHDBjg6GY4LfqHPuIY4v8Yn0HOi89o1+qfk43QOlVJrylTppgKCFrGSyNyLe/l7e0to0aNOuax8fHxctlll5mJZVlZWWbT61deeaXTThIDAABAy3KKoFaD0okTJ8rw4cOlbdu28s0338iKFStMOS+taKCXuq/K66+/biofdOnSxWyRkZGyZMkSh74HAAAAOI7D0w+U1kLT2rS61aWjr/l1lnkLDw+XN954oxVbCAAAAGfmFCO1AAAAwKkgqEUtOqlOc5qPN7nO3dE/9BHHEP/H+AxyXnxGu3f/eNjtleuxAgAAABbFSC0AAAAsj6AWAAAAlkdQCwAAAMsjqAUAAIDlEdRCNm3aJJdeeqlERUWZmsFffPHFSXvl0UcfFS8vL7MwRtV2ww03uGRvNqV/dP6lzjCNiYmRgIAAOffcc82Kea7qvffekx49eoifn59ZfvGDDz5w2+Onsb/77Oxsuemmm8yS4aGhoeZ6Tk6OuKrG9s/5558vPj4+tY6VuXPniit66623ZOjQoRIcHGw+a3TJ+BNxt2Onsf3jTseOuv/++6VPnz6mf7S6gX6m7tu374Q/U1xcLHfccYdZ0CooKEiuuOKKk/6MMyOohflPP3r0aPnkk08a1RuDBw82C2NUbW+++aZL9mZT+keXfV64cKGsXLnSLOWs61aPGDHimIVEXMEPP/wgY8eOlccff1zy8vLkscceM39c161b55bHT2N/99p3Bw4ckN27d8uuXbvM9QkTJoirasr/jT//+c+1jhVdWt0VhYWFmfc2Z86cBj3e3Y6dxvaPOx07ysPDQxYvXmz+X23bts3cvvLKK0/4M3/605/Miq3r16+X1NRUs7jVyJEjpaKiQixJS3oBVfSQ+Pe//33SDpk+fbp9yJAhbtdxDe2fhIQE+5w5c6pvl5aW2iMiIuxLliyxu5qJEyfar7766lr79PakSZPc8vhpzO8+KSnJHFMbN26s3qfXdV9ycrLdFTX2/8Z5551nf/DBB+3u5KuvvjLHgPbN8bjjsdOY/nHXY6emDRs2mH46fPiwvT6FhYV2Pz8/+4cffli9LzMz026z2eyrV6+2WxEjtWiyDRs2SGRkpMTHx8uNN94oe/fupTdFJDc3V5KSkmTQoEHV/WGz2aR///6mz1zNxo0ba71XNXDgwJO+V1c8fhr7u9e+8/X1lX79+lXv0+t6dkDvczVN/b/xyiuvmFE6TXHRU6yueMajsdzt2Gkqdz52Pv/8c/P5qu+/Ptu3b5fCwsJa/x81DaFTp06W/VtFUOvCJk6caE4/HG/TfKOmuvbaa2Xr1q1y8OBB+e6778zzDR8+3FIfGC3VP3oKXmmOW036wVJ1nyv1j76nxr5XVzh+muN3r/s0H7Iu/XkrHSst+X/jiSeekJ07d8qhQ4fk7bffNmkLN998s7g7dzt2msKdj50vvvhCZsyYIX//+99d/m9VTTZHNwAt56WXXjL5a8fj7e3d5Oc+/fTTq6/HxsaaHDn9gNUA5eKLLxZ37h9N0ld1J2zopA7tK6toaP/o+63vvVb1g6seP83xu9fH6+hlXfrzJ+o/q2rK/42zzz671kjk888/b74A6QiTTkx0V+527DSFux47n3zyicm3Xrp0qVxyySUN+v9Ysz9O9vntzBipdWE601NPJRxvq+9bflNVjd5ZadXlluof/bmEhARZu3Zt9T6dpaunBPU0q6v1T2JiYq33qnSSWGPeqxWPn+b43Wvf6ezjzZs3V+/T6yUlJeY+V9Mc/zc8Pf/3Z8vqx8qpcrdjpzm4w7Hzz3/+00zU1ZHpUaNGnfCx3bt3N8Fszf+POslMU4Ss9LeqFkcn9cLxKioqTMK4bnpIfPbZZ+b6iZLw3377bZNQrjIyMuzjxo2zx8fH2/Py8uyupin98/TTT9s7duxo//nnn+0FBQX2Bx54wB4TE2M/cuSI3dWsWbPG7uvra//ggw/sJSUl5rJNmzb2H3/80S2Pn8b+7i+77DL7RRddZPpDN71+5ZVX2l1VY/pHj43ly5fb8/Pzzf/DLVu22M844wz7qFGj7K6orKzMfLasXLnSfNbo+9bb5eXl9T7e3Y6dxvSPux076sUXX7SHhoY2apLXlClT7P369TOTC/Xzd/z48eb28Y45Z0dQC/vevXvNB0TdTWeoV+nVq5f98ccfr76tH5w6Y1lnTuofpDFjxth37tzpkr3ZlP7RD9GHH37Y3r59e9NHQ4cOtW/evNnuqt555x179+7dTXCrl++9916t+93p+DnR717/cAQEBNT6o3Po0CH7DTfcYA8ODjbbjTfeaM/Ozra7qsb0j87wHzhwoOkX3d+lSxf7vffe6xJffuqzaNGiej9rdLY/x07j+sfdjh0lIqZygb7fmlvNzxu9vXTp0urbRUVFJrANDw839+kXpZSUFLtVeeg/jh4tBgAAAE4FObUAAACwPIJaAAAAWB5BLQAAACyPoBYAAACWR1ALAAAAyyOoBQAAgOUR1AIAAMDyCGoBwAE+/PBDWbhwIX0PAM2EoBYAHICgFgCaF0EtAMAoLCykJwBYFkEtALSyiRMnymuvvSbffvuteHh4mG3x4sVSXl4us2bNkk6dOomvr6/07t3bjOjWlJCQIA899JA89thj0r59e4mMjJQ777xTSktLaz3/OeecU+vnvvjiC/M6SUlJ5rZe6u23335bfvvb30pQUJDcfvvt5r5NmzbJiBEjJDAwUEJDQ2XChAmSk5PTKn0DAE1la/JPAgCa5OGHH5bMzEzZv3+/zJs3z+zr0qWLTJkyRd566y2ZMWOGCWg//vhjueaaa2TNmjUyaNCg6p/XgPiss84yl1u2bJH7779funXrZoLbxrr77rvlpptuMsGzn5+f7NixQ4YOHWq2N998U44ePSoPPPCAjBs3zrQHAJwVQS0AtDINYHWENTc31wSnaufOnbJgwQJ555135NprrzX7LrroItmzZ4888cQTtUZsg4ODzQirp6enXHLJJfL111+b+5sS1F544YUye/bs6ttjx46Vzp07y7/+9S/x8vIy+7p27SoDBw6UDRs2SP/+/ZuhBwCg+ZF+AABO4D//+Y/4+PjI5ZdfLmVlZdXbsGHDZP369bUee8EFF5iAtkrPnj0lNTW1Sa976aWX1rr95ZdfyqhRo8Rut1e3ITExUUJCQuSnn35q4rsDgJbHSC0AOIGsrCwpLi4Wf3//Y+7TALaioqI6kNU815o0GC4qKmrS67Zr1+6Ydjz66KNmq2vfvn1Neg0AaA0EtQDgBMLDw01O6+rVq+u9v+bI7MnoJLOSkpJa+7Kzs+t9rE4Wq9uOMWPGmBzaumJiYhrcBgBobQS1AOAAOrqqI7M1Uwq0pJbuGzJkyCk9d4cOHeT99983qQM2m626+kFDaLrD1q1b5cwzzzylNgBAayOoBQAH6N69uyxdulQ++ugjiY2NNWW8br31Vhk9erTcd999Jo81Pz/flNfSy6eeeqrBz33VVVfJI488Ykp0XX/99WYi2cqVKxv0s5p2oJPCNK92/PjxJtUhJSVFPvvsM3Of5u8CgDMiqAUAB7j55pvlu+++MzVgtQrCokWL5JVXXpHTTjtN5s+fL3v37jUBZb9+/WTq1KmNeu6+ffua59CqCVqWa+TIkfLcc8+Z8mANCba1hJjWwp00aZIZOY6LizNVFqKiok7hHQNAy/Kw6xRXAAAAwMIo6QUAAADLI6gFAACA5RHUAgAAwPIIagEAAGB5BLUAAACwPIJaAAAAWB5BLQAAACyPoBYAAACWR1ALAAAAyyOoBQAAgOUR1AIAAMDyCGoBAAAgVvd/ZVnwA4qT0sMAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_std = pd.DataFrame(StandardScaler().fit_transform(df[num_cols].astype('float64')),\n",
    "                       columns=num_cols)\n",
    "for feat in numerical_cols: distplot(feat, df_std, color='c')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d91c7572-c18b-475f-862a-b118106b316f",
   "metadata": {},
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "bb54e2c0-cb05-4b80-a294-6fe08b28f079",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.111411Z",
     "iopub.status.busy": "2026-04-09T19:52:14.111332Z",
     "iopub.status.idle": "2026-04-09T19:52:14.117668Z",
     "shell.execute_reply": "2026-04-09T19:52:14.116982Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.111403Z"
    }
   },
   "outputs": [],
   "source": [
    "scaler= StandardScaler()\n",
    "\n",
    "X_train[num_cols] = scaler.fit_transform(X_train[num_cols])\n",
    "X_test[num_cols] = scaler.transform(X_test[num_cols])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57b63fef-2efc-440d-86b0-925ddfc32d60",
   "metadata": {},
   "source": [
    "## Modellieren\n",
    "\n",
    "Es handelt sich hierbei um einen Datensatz mit klar definierten Labels (Churn: Yes oder No), die eine Klassifikationsproblematik beschreiben. \n",
    "\n",
    "Dazu werden wir nun mehrere Klassifikationsmodelle testen."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "243aeaa3-c14b-4fa8-9842-53dd511f30b3",
   "metadata": {},
   "source": [
    "### K-Nearest Neighbor Classifier\n",
    "\n",
    "Der K-Nearest-Neighbor Classifier ist eine nichtparametrische Methode zur Schätzung von Wahrscheinlichkeitsdichtefunktionen, mehr Details: https://de.wikipedia.org/wiki/N%C3%A4chste-Nachbarn-Klassifikation\n",
    "\n",
    "Hier nutzen wir die kNN-Implemtation von scikit-learn: https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5c7e3b0f-c27c-4562-ae4a-70088b92c5aa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.118173Z",
     "iopub.status.busy": "2026-04-09T19:52:14.118070Z",
     "iopub.status.idle": "2026-04-09T19:52:14.119887Z",
     "shell.execute_reply": "2026-04-09T19:52:14.119440Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.118165Z"
    }
   },
   "outputs": [],
   "source": [
    "# Initiere das knn-Modell\n",
    "\n",
    "knn_model = KNeighborsClassifier(n_neighbors = 11) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "89492ad8-b601-45b6-8ef2-0be3b2b46edd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.120262Z",
     "iopub.status.busy": "2026-04-09T19:52:14.120194Z",
     "iopub.status.idle": "2026-04-09T19:52:14.129669Z",
     "shell.execute_reply": "2026-04-09T19:52:14.129129Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.120255Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "}\n",
       "\n",
       "#sk-container-id-1.light {\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: black;\n",
       "  --sklearn-color-background: white;\n",
       "  --sklearn-color-border-box: black;\n",
       "  --sklearn-color-icon: #696969;\n",
       "}\n",
       "\n",
       "#sk-container-id-1.dark {\n",
       "  --sklearn-color-text-on-default-background: white;\n",
       "  --sklearn-color-background: #111;\n",
       "  --sklearn-color-border-box: white;\n",
       "  --sklearn-color-icon: #878787;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: center;\n",
       "  justify-content: center;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  display: none;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  overflow: visible;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-3) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  border: var(--sklearn-color-fitted-level-0) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-0);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  border: var(--sklearn-color-fitted-level-0) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-0);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".estimator-table {\n",
       "    font-family: monospace;\n",
       "}\n",
       "\n",
       ".estimator-table summary {\n",
       "    padding: .5rem;\n",
       "    cursor: pointer;\n",
       "}\n",
       "\n",
       ".estimator-table summary::marker {\n",
       "    font-size: 0.7rem;\n",
       "}\n",
       "\n",
       ".estimator-table details[open] {\n",
       "    padding-left: 0.1rem;\n",
       "    padding-right: 0.1rem;\n",
       "    padding-bottom: 0.3rem;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table {\n",
       "    margin-left: auto !important;\n",
       "    margin-right: auto !important;\n",
       "    margin-top: 0;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
       "    background-color: #fff;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:nth-child(even) {\n",
       "    background-color: #f6f6f6;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:hover {\n",
       "    background-color: #e0e0e0;\n",
       "}\n",
       "\n",
       ".estimator-table table td {\n",
       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
       "}\n",
       "\n",
       "/*\n",
       "    `table td`is set in notebook with right text-align.\n",
       "    We need to overwrite it.\n",
       "*/\n",
       ".estimator-table table td.param {\n",
       "    text-align: left;\n",
       "    position: relative;\n",
       "    padding: 0;\n",
       "}\n",
       "\n",
       ".user-set td {\n",
       "    color:rgb(255, 94, 0);\n",
       "    text-align: left !important;\n",
       "}\n",
       "\n",
       ".user-set td.value {\n",
       "    color:rgb(255, 94, 0);\n",
       "    background-color: transparent;\n",
       "}\n",
       "\n",
       ".default td {\n",
       "    color: black;\n",
       "    text-align: left !important;\n",
       "}\n",
       "\n",
       ".user-set td i,\n",
       ".default td i {\n",
       "    color: black;\n",
       "}\n",
       "\n",
       "/*\n",
       "    Styles for parameter documentation links\n",
       "    We need styling for visited so jupyter doesn't overwrite it\n",
       "*/\n",
       "a.param-doc-link,\n",
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       "</style><body><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(n_neighbors=11)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>KNeighborsClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html\">?<span>Documentation for KNeighborsClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"\">\n",
       "        <div class=\"estimator-table\">\n",
       "            <details>\n",
       "                <summary>Parameters</summary>\n",
       "                <table class=\"parameters-table\">\n",
       "                  <tbody>\n",
       "                    \n",
       "        <tr class=\"user-set\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('n_neighbors',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">\n",
       "        <a class=\"param-doc-link\"\n",
       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=n_neighbors,-int%2C%20default%3D5\">\n",
       "            n_neighbors\n",
       "            <span class=\"param-doc-description\">n_neighbors: int, default=5<br><br>Number of neighbors to use by default for :meth:`kneighbors` queries.</span>\n",
       "        </a>\n",
       "    </td>\n",
       "            <td class=\"value\">11</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('weights',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">\n",
       "        <a class=\"param-doc-link\"\n",
       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=weights,-%7B%27uniform%27%2C%20%27distance%27%7D%2C%20callable%20or%20None%2C%20default%3D%27uniform%27\">\n",
       "            weights\n",
       "            <span class=\"param-doc-description\">weights: {'uniform', 'distance'}, callable or None, default='uniform'<br><br>Weight function used in prediction.  Possible values:<br><br>- 'uniform' : uniform weights.  All points in each neighborhood<br>  are weighted equally.<br>- 'distance' : weight points by the inverse of their distance.<br>  in this case, closer neighbors of a query point will have a<br>  greater influence than neighbors which are further away.<br>- [callable] : a user-defined function which accepts an<br>  array of distances, and returns an array of the same shape<br>  containing the weights.<br><br>Refer to the example entitled<br>:ref:`sphx_glr_auto_examples_neighbors_plot_classification.py`<br>showing the impact of the `weights` parameter on the decision<br>boundary.</span>\n",
       "        </a>\n",
       "    </td>\n",
       "            <td class=\"value\">&#x27;uniform&#x27;</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('algorithm',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">\n",
       "        <a class=\"param-doc-link\"\n",
       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=algorithm,-%7B%27auto%27%2C%20%27ball_tree%27%2C%20%27kd_tree%27%2C%20%27brute%27%7D%2C%20default%3D%27auto%27\">\n",
       "            algorithm\n",
       "            <span class=\"param-doc-description\">algorithm: {'auto', 'ball_tree', 'kd_tree', 'brute'}, default='auto'<br><br>Algorithm used to compute the nearest neighbors:<br><br>- 'ball_tree' will use :class:`BallTree`<br>- 'kd_tree' will use :class:`KDTree`<br>- 'brute' will use a brute-force search.<br>- 'auto' will attempt to decide the most appropriate algorithm<br>  based on the values passed to :meth:`fit` method.<br><br>Note: fitting on sparse input will override the setting of<br>this parameter, using brute force.</span>\n",
       "        </a>\n",
       "    </td>\n",
       "            <td class=\"value\">&#x27;auto&#x27;</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('leaf_size',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">\n",
       "        <a class=\"param-doc-link\"\n",
       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=leaf_size,-int%2C%20default%3D30\">\n",
       "            leaf_size\n",
       "            <span class=\"param-doc-description\">leaf_size: int, default=30<br><br>Leaf size passed to BallTree or KDTree.  This can affect the<br>speed of the construction and query, as well as the memory<br>required to store the tree.  The optimal value depends on the<br>nature of the problem.</span>\n",
       "        </a>\n",
       "    </td>\n",
       "            <td class=\"value\">30</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('p',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">\n",
       "        <a class=\"param-doc-link\"\n",
       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=p,-float%2C%20default%3D2\">\n",
       "            p\n",
       "            <span class=\"param-doc-description\">p: float, default=2<br><br>Power parameter for the Minkowski metric. When p = 1, this is equivalent<br>to using manhattan_distance (l1), and euclidean_distance (l2) for p = 2.<br>For arbitrary p, minkowski_distance (l_p) is used. This parameter is expected<br>to be positive.</span>\n",
       "        </a>\n",
       "    </td>\n",
       "            <td class=\"value\">2</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('metric',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">\n",
       "        <a class=\"param-doc-link\"\n",
       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=metric,-str%20or%20callable%2C%20default%3D%27minkowski%27\">\n",
       "            metric\n",
       "            <span class=\"param-doc-description\">metric: str or callable, default='minkowski'<br><br>Metric to use for distance computation. Default is \"minkowski\", which<br>results in the standard Euclidean distance when p = 2. See the<br>documentation of `scipy.spatial.distance<br><https://docs.scipy.org/doc/scipy/reference/spatial.distance.html>`_ and<br>the metrics listed in<br>:class:`~sklearn.metrics.pairwise.distance_metrics` for valid metric<br>values.<br><br>If metric is \"precomputed\", X is assumed to be a distance matrix and<br>must be square during fit. X may be a :term:`sparse graph`, in which<br>case only \"nonzero\" elements may be considered neighbors.<br><br>If metric is a callable function, it takes two arrays representing 1D<br>vectors as inputs and must return one value indicating the distance<br>between those vectors. This works for Scipy's metrics, but is less<br>efficient than passing the metric name as a string.</span>\n",
       "        </a>\n",
       "    </td>\n",
       "            <td class=\"value\">&#x27;minkowski&#x27;</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('metric_params',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">\n",
       "        <a class=\"param-doc-link\"\n",
       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=metric_params,-dict%2C%20default%3DNone\">\n",
       "            metric_params\n",
       "            <span class=\"param-doc-description\">metric_params: dict, default=None<br><br>Additional keyword arguments for the metric function.</span>\n",
       "        </a>\n",
       "    </td>\n",
       "            <td class=\"value\">None</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('n_jobs',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">\n",
       "        <a class=\"param-doc-link\"\n",
       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=n_jobs,-int%2C%20default%3DNone\">\n",
       "            n_jobs\n",
       "            <span class=\"param-doc-description\">n_jobs: int, default=None<br><br>The number of parallel jobs to run for neighbors search.<br>``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.<br>``-1`` means using all processors. See :term:`Glossary <n_jobs>`<br>for more details.<br>Doesn't affect :meth:`fit` method.</span>\n",
       "        </a>\n",
       "    </td>\n",
       "            <td class=\"value\">None</td>\n",
       "        </tr>\n",
       "    \n",
       "                  </tbody>\n",
       "                </table>\n",
       "            </details>\n",
       "        </div>\n",
       "    </div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
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      ],
      "text/plain": [
       "KNeighborsClassifier(n_neighbors=11)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Trainiere das Modell mit unseren Trainingsdaten\n",
    "\n",
    "knn_model.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "28bd4a9d-7abf-4f80-960e-bb22ec3c0ed8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.130351Z",
     "iopub.status.busy": "2026-04-09T19:52:14.130249Z",
     "iopub.status.idle": "2026-04-09T19:52:14.199107Z",
     "shell.execute_reply": "2026-04-09T19:52:14.198049Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.130343Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KNN accuracy: 0.7611374407582938\n",
      "0.7611374407582938\n"
     ]
    }
   ],
   "source": [
    "# die \"score\"-Funktion scoret direkt die predicted Resultate vom X_test gegen die wahren y-Werte und gibt die Accuracy zurück\n",
    "\n",
    "accuracy_knn = knn_model.score(X_test,y_test)\n",
    "print(\"KNN accuracy:\",accuracy_knn)\n",
    "print(knn_model.score(X_test,y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "7f2c2134-76de-4727-8f77-84ffc7e9109d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.200045Z",
     "iopub.status.busy": "2026-04-09T19:52:14.199925Z",
     "iopub.status.idle": "2026-04-09T19:52:14.220539Z",
     "shell.execute_reply": "2026-04-09T19:52:14.219675Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.200034Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "precision:  [0.81119714 0.56612529]\n",
      "recall:  [0.87927695 0.43493761]\n"
     ]
    }
   ],
   "source": [
    "# Alternativ kann man direkt mit dem Modell auf den X_test (Testdatensatz) vorhersagen und diese Vorhersagen gegen die wahren Werte des Testdatensatzes mit sklearn evaluieren\n",
    "\n",
    "y_pred = knn_model.predict(X_test)\n",
    "prec = precision_score(y_test, y_pred, average=None)\n",
    "recall = recall_score(y_test, y_pred, average=None)\n",
    "print(\"precision: \", prec)\n",
    "print(\"recall: \", recall)"
   ]
  },
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     "iopub.status.idle": "2026-04-09T19:52:14.226601Z",
     "shell.execute_reply": "2026-04-09T19:52:14.226106Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.221171Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.81      0.88      0.84      1549\n",
      "           1       0.57      0.43      0.49       561\n",
      "\n",
      "    accuracy                           0.76      2110\n",
      "   macro avg       0.69      0.66      0.67      2110\n",
      "weighted avg       0.75      0.76      0.75      2110\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Zudem gibt es den \"Classification Report\", der direkt mehrere Metriken Resultate ausgibt\n",
    "\n",
    "print(classification_report(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "b2274273-574c-4a2a-b96c-08af2769ae34",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.227262Z",
     "iopub.status.busy": "2026-04-09T19:52:14.227181Z",
     "iopub.status.idle": "2026-04-09T19:52:14.245319Z",
     "shell.execute_reply": "2026-04-09T19:52:14.244595Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.227255Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 0 ... 0 0 0]\n"
     ]
    }
   ],
   "source": [
    "# Predict directly with the trained model\n",
    "\n",
    "y_pred = knn_model.predict(X_test)\n",
    "print(y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "069d41b0-7428-4550-b584-66649b94cb0d",
   "metadata": {},
   "source": [
    "### Logistic Regression Classifier\n",
    "\n",
    "Der Logistic Regression Classifier basiert auf Linear Regression, nur gibt sie am Ende eine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "ac8f8724-20a1-4d5b-901b-453ea35d8cfd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.246452Z",
     "iopub.status.busy": "2026-04-09T19:52:14.246297Z",
     "iopub.status.idle": "2026-04-09T19:52:14.256246Z",
     "shell.execute_reply": "2026-04-09T19:52:14.255835Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.246441Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logistic Regression accuracy is : 0.776303317535545\n"
     ]
    }
   ],
   "source": [
    "lr_model = LogisticRegression()\n",
    "lr_model.fit(X_train,y_train)\n",
    "accuracy_lr = lr_model.score(X_test,y_test)\n",
    "print(\"Logistic Regression accuracy is :\",accuracy_lr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "7deda99d-1526-4eaa-b3ec-e7b8c0d4f31e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.256733Z",
     "iopub.status.busy": "2026-04-09T19:52:14.256659Z",
     "iopub.status.idle": "2026-04-09T19:52:14.263601Z",
     "shell.execute_reply": "2026-04-09T19:52:14.262266Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.256725Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.81      0.90      0.86      1549\n",
      "           1       0.61      0.42      0.50       561\n",
      "\n",
      "    accuracy                           0.78      2110\n",
      "   macro avg       0.71      0.66      0.68      2110\n",
      "weighted avg       0.76      0.78      0.76      2110\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Make predictions\n",
    "lr_pred= lr_model.predict(X_test)\n",
    "report = classification_report(y_test,lr_pred)\n",
    "print(report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "51f483f4-da43-4314-8e77-cc7fb247b329",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.264440Z",
     "iopub.status.busy": "2026-04-09T19:52:14.264298Z",
     "iopub.status.idle": "2026-04-09T19:52:14.310968Z",
     "shell.execute_reply": "2026-04-09T19:52:14.310513Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.264431Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4,3))\n",
    "sns.heatmap(confusion_matrix(y_test, lr_pred),\n",
    "                annot=True,fmt = \"d\",linecolor=\"k\",linewidths=3)\n",
    "    \n",
    "plt.title(\"LOGISTIC REGRESSION CONFUSION MATRIX\",fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3d82006-b536-4ac6-9031-88856a2cff24",
   "metadata": {},
   "source": [
    "### Decision Tree Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "b984849b-5817-459e-893e-95ee262b098c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.311350Z",
     "iopub.status.busy": "2026-04-09T19:52:14.311267Z",
     "iopub.status.idle": "2026-04-09T19:52:14.328056Z",
     "shell.execute_reply": "2026-04-09T19:52:14.327478Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.311343Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree accuracy is : 0.7018957345971564\n"
     ]
    }
   ],
   "source": [
    "dt_model = DecisionTreeClassifier()\n",
    "dt_model.fit(X_train,y_train)\n",
    "predictdt_y = dt_model.predict(X_test)\n",
    "accuracy_dt = dt_model.score(X_test,y_test)\n",
    "print(\"Decision Tree accuracy is :\",accuracy_dt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "7e68f5a1-5f03-44f3-8b61-3e0ac7c5dd78",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.328510Z",
     "iopub.status.busy": "2026-04-09T19:52:14.328435Z",
     "iopub.status.idle": "2026-04-09T19:52:14.334222Z",
     "shell.execute_reply": "2026-04-09T19:52:14.333627Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.328503Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.80      0.79      0.80      1549\n",
      "           1       0.44      0.45      0.45       561\n",
      "\n",
      "    accuracy                           0.70      2110\n",
      "   macro avg       0.62      0.62      0.62      2110\n",
      "weighted avg       0.70      0.70      0.70      2110\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, predictdt_y))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57133593-2f9f-4423-a495-7346a1a779d7",
   "metadata": {},
   "source": [
    "### AdaBoost Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "a7d0fad2-bc33-4c2b-8e30-6778640e5b4b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.334550Z",
     "iopub.status.busy": "2026-04-09T19:52:14.334484Z",
     "iopub.status.idle": "2026-04-09T19:52:14.438929Z",
     "shell.execute_reply": "2026-04-09T19:52:14.438533Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.334544Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AdaBoost Classifier accuracy\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.7838862559241706"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_model = AdaBoostClassifier()\n",
    "a_model.fit(X_train,y_train)\n",
    "a_preds = a_model.predict(X_test)\n",
    "print(\"AdaBoost Classifier accuracy\")\n",
    "metrics.accuracy_score(y_test, a_preds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "169efc97-29ef-4ddd-960f-f9e913ae70a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.439801Z",
     "iopub.status.busy": "2026-04-09T19:52:14.439613Z",
     "iopub.status.idle": "2026-04-09T19:52:14.445117Z",
     "shell.execute_reply": "2026-04-09T19:52:14.444709Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.439793Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.82      0.90      0.86      1549\n",
      "           1       0.63      0.47      0.53       561\n",
      "\n",
      "    accuracy                           0.78      2110\n",
      "   macro avg       0.72      0.68      0.70      2110\n",
      "weighted avg       0.77      0.78      0.77      2110\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, a_preds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "7bb2a523-487e-4d4d-a116-f02a0302540e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.445488Z",
     "iopub.status.busy": "2026-04-09T19:52:14.445409Z",
     "iopub.status.idle": "2026-04-09T19:52:14.485914Z",
     "shell.execute_reply": "2026-04-09T19:52:14.485277Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.445481Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4,3))\n",
    "sns.heatmap(confusion_matrix(y_test, a_preds),\n",
    "                annot=True,fmt = \"d\",linecolor=\"k\",linewidths=3)\n",
    "    \n",
    "plt.title(\"AdaBoost Classifier Confusion Matrix\",fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b59d9beb-fdc8-4051-b319-4863612c0b3c",
   "metadata": {},
   "source": [
    "### Gradient Boosting Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "a2e8910d-b6f1-44d7-940c-752c0d762ff5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.486469Z",
     "iopub.status.busy": "2026-04-09T19:52:14.486343Z",
     "iopub.status.idle": "2026-04-09T19:52:14.812688Z",
     "shell.execute_reply": "2026-04-09T19:52:14.812068Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.486449Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gradient Boosting Classifier 0.7781990521327015\n"
     ]
    }
   ],
   "source": [
    "gb = GradientBoostingClassifier()\n",
    "gb.fit(X_train, y_train)\n",
    "gb_pred = gb.predict(X_test)\n",
    "print(\"Gradient Boosting Classifier\", accuracy_score(y_test, gb_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "520bc7a9-82e9-429c-b8fa-2e0b86f360ce",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.813252Z",
     "iopub.status.busy": "2026-04-09T19:52:14.813084Z",
     "iopub.status.idle": "2026-04-09T19:52:14.819049Z",
     "shell.execute_reply": "2026-04-09T19:52:14.818543Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.813179Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.82      0.90      0.86      1549\n",
      "           1       0.62      0.44      0.51       561\n",
      "\n",
      "    accuracy                           0.78      2110\n",
      "   macro avg       0.72      0.67      0.68      2110\n",
      "weighted avg       0.76      0.78      0.76      2110\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, gb_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "c80a6983-cd60-48a3-a15b-d319a8e65e99",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.819703Z",
     "iopub.status.busy": "2026-04-09T19:52:14.819631Z",
     "iopub.status.idle": "2026-04-09T19:52:14.867705Z",
     "shell.execute_reply": "2026-04-09T19:52:14.867112Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.819696Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4,3))\n",
    "sns.heatmap(confusion_matrix(y_test, gb_pred),\n",
    "                annot=True,fmt = \"d\",linecolor=\"k\",linewidths=3)\n",
    "    \n",
    "plt.title(\"Gradient Boosting Classifier Confusion Matrix\",fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e63783eb-8ba5-4e1d-a08f-d5a81118a1d8",
   "metadata": {},
   "source": [
    "### Voting Classifier\n",
    "\n",
    "Der Voting Classifier ist ein Mixture Modell, der mehrere Modelle vereint, die alle ihre Predictions machen und dann über Majority voting entschieden wird, welche Prediction Output rausgegeben wird."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "0e83a4da-50b9-4600-8b89-a2dd377f5c6b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:14.868158Z",
     "iopub.status.busy": "2026-04-09T19:52:14.868048Z",
     "iopub.status.idle": "2026-04-09T19:52:15.301023Z",
     "shell.execute_reply": "2026-04-09T19:52:15.300279Z",
     "shell.execute_reply.started": "2026-04-09T19:52:14.868149Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final Accuracy Score \n",
      "0.7834123222748816\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import VotingClassifier\n",
    "clf1 = GradientBoostingClassifier()\n",
    "clf2 = LogisticRegression()\n",
    "clf3 = AdaBoostClassifier()\n",
    "eclf1 = VotingClassifier(estimators=[(\"gbc\", clf1), (\"lr\", clf2), (\"abc\", clf3)], voting=\"soft\")\n",
    "eclf1.fit(X_train, y_train)\n",
    "predictions = eclf1.predict(X_test)\n",
    "print(\"Final Accuracy Score \")\n",
    "print(accuracy_score(y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "625e01ae-4164-4d6f-92fe-b623af867b15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:15.301504Z",
     "iopub.status.busy": "2026-04-09T19:52:15.301398Z",
     "iopub.status.idle": "2026-04-09T19:52:15.307406Z",
     "shell.execute_reply": "2026-04-09T19:52:15.306957Z",
     "shell.execute_reply.started": "2026-04-09T19:52:15.301496Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.82      0.91      0.86      1549\n",
      "           1       0.63      0.44      0.52       561\n",
      "\n",
      "    accuracy                           0.78      2110\n",
      "   macro avg       0.73      0.67      0.69      2110\n",
      "weighted avg       0.77      0.78      0.77      2110\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "f6bc6e7c-7a6a-41f8-b557-60b8828ac760",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-04-09T19:52:15.307830Z",
     "iopub.status.busy": "2026-04-09T19:52:15.307747Z",
     "iopub.status.idle": "2026-04-09T19:52:15.357559Z",
     "shell.execute_reply": "2026-04-09T19:52:15.356916Z",
     "shell.execute_reply.started": "2026-04-09T19:52:15.307821Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4,3))\n",
    "sns.heatmap(confusion_matrix(y_test, predictions),\n",
    "                annot=True,fmt = \"d\",linecolor=\"k\",linewidths=3)\n",
    "    \n",
    "plt.title(\"FINAL CONFUSION MATRIX\",fontsize=14)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.0"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}