{ "cells": [ { "cell_type": "markdown", "id": "f417dc67-8099-4e04-bfdb-3cd8602a72c4", "metadata": {}, "source": [ "# Praxisbeispiel - Telko Vertragskundenabgang-Vorhersage MIT simulierten Kunden-Service-Daten\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. \n" ] }, { "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.\n" ] }, { "cell_type": "markdown", "id": "00f525a4-b2bf-4ee8-9d0f-17f952de0eed", "metadata": {}, "source": [ "## Datensatz \n", "\n", "1. Wir nutzen den Kaggle-Datensatz als die Baseline der Kundeninformationen: \n", "https://www.kaggle.com/datasets/blastchar/telco-customer-churn\n", "2. Wir nutzen einen selbst simulierten Datensatz bzgl. Kunden-Service, das vorher in diesem Folder abgespeichert wurde: kunden_service.csv" ] }, { "cell_type": "code", "execution_count": 1, "id": "8ee77e59-bc5e-49ce-9b96-a735aa3822e3", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:54:57.904804Z", "iopub.status.busy": "2026-03-24T17:54:57.904701Z", "iopub.status.idle": "2026-03-24T17:54:57.909137Z", "shell.execute_reply": "2026-03-24T17:54:57.908375Z", "shell.execute_reply.started": "2026-03-24T17:54:57.904794Z" } }, "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": "2026-03-24T17:54:57.909576Z", "iopub.status.busy": "2026-03-24T17:54:57.909509Z", "iopub.status.idle": "2026-03-24T17:54:58.081006Z", "shell.execute_reply": "2026-03-24T17:54:58.080416Z", "shell.execute_reply.started": "2026-03-24T17:54:57.909568Z" } }, "outputs": [], "source": [ "import kagglehub" ] }, { "cell_type": "code", "execution_count": 3, "id": "b58bd575-3ead-42fc-89fd-7f2fa8f86e09", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:54:58.081511Z", "iopub.status.busy": "2026-03-24T17:54:58.081364Z", "iopub.status.idle": "2026-03-24T17:54:59.342076Z", "shell.execute_reply": "2026-03-24T17:54:59.341687Z", "shell.execute_reply.started": "2026-03-24T17:54:58.081502Z" } }, "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": "2026-03-24T17:54:59.342672Z", "iopub.status.busy": "2026-03-24T17:54:59.342507Z", "iopub.status.idle": "2026-03-24T17:54:59.649928Z", "shell.execute_reply": "2026-03-24T17:54:59.648946Z", "shell.execute_reply.started": "2026-03-24T17:54:59.342664Z" }, "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": "2fb461fa-d474-4e2b-a6a6-136cd9e17081", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:54:59.650425Z", "iopub.status.busy": "2026-03-24T17:54:59.650240Z", "iopub.status.idle": "2026-03-24T17:55:00.046314Z", "shell.execute_reply": "2026-03-24T17:55:00.045442Z", "shell.execute_reply.started": "2026-03-24T17:54:59.650415Z" } }, "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": "2026-03-24T17:55:00.047210Z", "iopub.status.busy": "2026-03-24T17:55:00.047019Z", "iopub.status.idle": "2026-03-24T17:55:00.050311Z", "shell.execute_reply": "2026-03-24T17:55:00.049331Z", "shell.execute_reply.started": "2026-03-24T17:55:00.047193Z" }, "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": [ "## Daten laden" ] }, { "cell_type": "code", "execution_count": 7, "id": "ee8380c5-4ae6-4e3c-babc-bd8c77ee0cb4", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.050980Z", "iopub.status.busy": "2026-03-24T17:55:00.050828Z", "iopub.status.idle": "2026-03-24T17:55:00.091618Z", "shell.execute_reply": "2026-03-24T17:55:00.091062Z", "shell.execute_reply.started": "2026-03-24T17:55:00.050965Z" }, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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customerIDgenderSeniorCitizenPartnerDependentstenurePhoneServiceMultipleLinesInternetServiceOnlineSecurityOnlineBackupDeviceProtectionTechSupportStreamingTVStreamingMoviesContractPaperlessBillingPaymentMethodMonthlyChargesTotalChargesChurn
07590-VHVEGFemale0YesNo1NoNo phone serviceDSLNoYesNoNoNoNoMonth-to-monthYesElectronic check29.8529.85No
15575-GNVDEMale0NoNo34YesNoDSLYesNoYesNoNoNoOne yearNoMailed check56.951889.5No
23668-QPYBKMale0NoNo2YesNoDSLYesYesNoNoNoNoMonth-to-monthYesMailed check53.85108.15Yes
37795-CFOCWMale0NoNo45NoNo phone serviceDSLYesNoYesYesNoNoOne yearNoBank transfer (automatic)42.301840.75No
49237-HQITUFemale0NoNo2YesNoFiber opticNoNoNoNoNoNoMonth-to-monthYesElectronic check70.70151.65Yes
..................................................................
70386840-RESVBMale0YesYes24YesYesDSLYesNoYesYesYesYesOne yearYesMailed check84.801990.5No
70392234-XADUHFemale0YesYes72YesYesFiber opticNoYesYesNoYesYesOne yearYesCredit card (automatic)103.207362.9No
70404801-JZAZLFemale0YesYes11NoNo phone serviceDSLYesNoNoNoNoNoMonth-to-monthYesElectronic check29.60346.45No
70418361-LTMKDMale1YesNo4YesYesFiber opticNoNoNoNoNoNoMonth-to-monthYesMailed check74.40306.6Yes
70423186-AJIEKMale0NoNo66YesNoFiber opticYesNoYesYesYesYesTwo yearYesBank transfer (automatic)105.656844.5No
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7043 rows × 21 columns

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" ], "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_ori = pd.read_csv(path_file)\n", "df_ori" ] }, { "cell_type": "code", "execution_count": 8, "id": "2f2a4b3b-9de0-43a9-82ed-30c5df74dc46", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.092199Z", "iopub.status.busy": "2026-03-24T17:55:00.092105Z", "iopub.status.idle": "2026-03-24T17:55:00.145059Z", "shell.execute_reply": "2026-03-24T17:55:00.144418Z", "shell.execute_reply.started": "2026-03-24T17:55:00.092190Z" } }, "outputs": [ { "data": { "text/html": [ "
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ticket_idcustomer_idtime_requesttime_replychannelrequestreplysolvedoriginal_requestoriginal_ticket_id
07590-VHVEG_T17590-VHVEG2024-12-23 00:00:002024-12-23 14:28:40On-siteInternet funktioniert nichtTicket geschlossenTrueTrueNaN
17590-VHVEG_T17590-VHVEG2024-12-23 14:28:402024-12-23 20:20:22HotlineInternet funktioniert nichtAnfrage wird bearbeitetFalseFalse7590-VHVEG_T1
25575-GNVDE_T15575-GNVDE2023-09-03 00:00:002023-09-03 12:48:24EmailInternet funktioniert nichtProblem gelöstTrueTrueNaN
35575-GNVDE_T15575-GNVDE2023-09-04 12:48:242023-09-05 08:04:13Social MediaFrage zum VertragWeitere Informationen benötigtFalseFalse5575-GNVDE_T1
45575-GNVDE_T25575-GNVDE2024-12-16 00:00:002024-12-17 20:29:09On-siteInternet funktioniert nichtWeitere Informationen benötigtFalseTrueNaN
.................................
281536840-RESVB_T16840-RESVB2024-03-18 20:03:202024-03-18 23:24:42EmailBeschwerde über KundenserviceTicket geschlossenTrueFalse6840-RESVB_T1
281544801-JZAZL_T14801-JZAZL2024-08-11 00:00:002024-08-11 11:26:24HotlineProblem mit RechnungTicket geschlossenTrueTrueNaN
281554801-JZAZL_T14801-JZAZL2024-08-11 11:26:242024-08-12 13:54:33EmailProblem mit RechnungAnfrage wird bearbeitetFalseFalse4801-JZAZL_T1
281568361-LTMKD_T18361-LTMKD2024-10-16 00:00:002024-10-16 17:35:16On-siteProblem mit RechnungProblem gelöstTrueTrueNaN
281578361-LTMKD_T18361-LTMKD2024-10-16 17:35:162024-10-16 20:38:36HotlineBeschwerde über KundenserviceWeitere Informationen benötigtFalseFalse8361-LTMKD_T1
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28158 rows × 10 columns

\n", "
" ], "text/plain": [ " ticket_id customer_id time_request time_reply \\\n", "0 7590-VHVEG_T1 7590-VHVEG 2024-12-23 00:00:00 2024-12-23 14:28:40 \n", "1 7590-VHVEG_T1 7590-VHVEG 2024-12-23 14:28:40 2024-12-23 20:20:22 \n", "2 5575-GNVDE_T1 5575-GNVDE 2023-09-03 00:00:00 2023-09-03 12:48:24 \n", "3 5575-GNVDE_T1 5575-GNVDE 2023-09-04 12:48:24 2023-09-05 08:04:13 \n", "4 5575-GNVDE_T2 5575-GNVDE 2024-12-16 00:00:00 2024-12-17 20:29:09 \n", "... ... ... ... ... \n", "28153 6840-RESVB_T1 6840-RESVB 2024-03-18 20:03:20 2024-03-18 23:24:42 \n", "28154 4801-JZAZL_T1 4801-JZAZL 2024-08-11 00:00:00 2024-08-11 11:26:24 \n", "28155 4801-JZAZL_T1 4801-JZAZL 2024-08-11 11:26:24 2024-08-12 13:54:33 \n", "28156 8361-LTMKD_T1 8361-LTMKD 2024-10-16 00:00:00 2024-10-16 17:35:16 \n", "28157 8361-LTMKD_T1 8361-LTMKD 2024-10-16 17:35:16 2024-10-16 20:38:36 \n", "\n", " channel request \\\n", "0 On-site Internet funktioniert nicht \n", "1 Hotline Internet funktioniert nicht \n", "2 Email Internet funktioniert nicht \n", "3 Social Media Frage zum Vertrag \n", "4 On-site Internet funktioniert nicht \n", "... ... ... \n", "28153 Email Beschwerde über Kundenservice \n", "28154 Hotline Problem mit Rechnung \n", "28155 Email Problem mit Rechnung \n", "28156 On-site Problem mit Rechnung \n", "28157 Hotline Beschwerde über Kundenservice \n", "\n", " reply solved original_request \\\n", "0 Ticket geschlossen True True \n", "1 Anfrage wird bearbeitet False False \n", "2 Problem gelöst True True \n", "3 Weitere Informationen benötigt False False \n", "4 Weitere Informationen benötigt False True \n", "... ... ... ... \n", "28153 Ticket geschlossen True False \n", "28154 Ticket geschlossen True True \n", "28155 Anfrage wird bearbeitet False False \n", "28156 Problem gelöst True True \n", "28157 Weitere Informationen benötigt False False \n", "\n", " original_ticket_id \n", "0 NaN \n", "1 7590-VHVEG_T1 \n", "2 NaN \n", "3 5575-GNVDE_T1 \n", "4 NaN \n", "... ... \n", "28153 6840-RESVB_T1 \n", "28154 NaN \n", "28155 4801-JZAZL_T1 \n", "28156 NaN \n", "28157 8361-LTMKD_T1 \n", "\n", "[28158 rows x 10 columns]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "path_kunden_service_log = \"kunden_service.csv\"\n", "df_service = pd.read_csv(path_kunden_service_log)\n", "df_service" ] }, { "cell_type": "markdown", "id": "d8662ad7-2893-4301-8c27-2cdf9e156190", "metadata": {}, "source": [ "## Daten Manipulation / Bereinigung" ] }, { "cell_type": "markdown", "id": "bdbf4cd5-0ae5-4668-a3f2-79a6ff57742c", "metadata": {}, "source": [ "### Original Kunden-Datensatz" ] }, { "cell_type": "code", "execution_count": 9, "id": "3f2fb452-45e3-4f11-9983-4b66da22d973", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.145646Z", "iopub.status.busy": "2026-03-24T17:55:00.145546Z", "iopub.status.idle": "2026-03-24T17:55:00.150204Z", "shell.execute_reply": "2026-03-24T17:55:00.149563Z", "shell.execute_reply.started": "2026-03-24T17:55:00.145638Z" } }, "outputs": [], "source": [ "df_ori[\"TotalCharges\"] = pd.to_numeric(df_ori.TotalCharges, errors=\"coerce\")" ] }, { "cell_type": "code", "execution_count": 10, "id": "224c58a4-af6c-4566-9d44-7fff26035870", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.150649Z", "iopub.status.busy": "2026-03-24T17:55:00.150570Z", "iopub.status.idle": "2026-03-24T17:55:00.159700Z", "shell.execute_reply": "2026-03-24T17:55:00.159252Z", "shell.execute_reply.started": "2026-03-24T17:55:00.150641Z" } }, "outputs": [ { "data": { "text/html": [ "
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customerIDgenderSeniorCitizenPartnerDependentstenurePhoneServiceMultipleLinesInternetServiceOnlineSecurityOnlineBackupDeviceProtectionTechSupportStreamingTVStreamingMoviesContractPaperlessBillingPaymentMethodMonthlyChargesTotalChargesChurn
07590-VHVEGFemale0YesNo1NoNo phone serviceDSLNoYesNoNoNoNoMonth-to-monthYesElectronic check29.8529.85No
15575-GNVDEMale0NoNo34YesNoDSLYesNoYesNoNoNoOne yearNoMailed check56.951889.50No
23668-QPYBKMale0NoNo2YesNoDSLYesYesNoNoNoNoMonth-to-monthYesMailed check53.85108.15Yes
37795-CFOCWMale0NoNo45NoNo phone serviceDSLYesNoYesYesNoNoOne yearNoBank transfer (automatic)42.301840.75No
49237-HQITUFemale0NoNo2YesNoFiber opticNoNoNoNoNoNoMonth-to-monthYesElectronic check70.70151.65Yes
\n", "
" ], "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 No \n", "1 No \n", "2 Yes \n", "3 No \n", "4 Yes " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_ori.drop(labels=df_ori[df_ori[\"tenure\"] == 0].index, axis=0, inplace=True)\n", "df_ori.head()" ] }, { "cell_type": "code", "execution_count": 11, "id": "58da506e-cff0-40dc-937e-f54e8d56b420", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.160108Z", "iopub.status.busy": "2026-03-24T17:55:00.160025Z", "iopub.status.idle": "2026-03-24T17:55:00.167385Z", "shell.execute_reply": "2026-03-24T17:55:00.166831Z", "shell.execute_reply.started": "2026-03-24T17:55:00.160101Z" } }, "outputs": [ { "data": { "text/html": [ "
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indexcustomerIDgenderSeniorCitizenPartnerDependentstenurePhoneServiceMultipleLinesInternetServiceOnlineSecurityOnlineBackupDeviceProtectionTechSupportStreamingTVStreamingMoviesContractPaperlessBillingPaymentMethodMonthlyChargesTotalChargesChurn
007590-VHVEGFemale0YesNo1NoNo phone serviceDSLNoYesNoNoNoNoMonth-to-monthYesElectronic check29.8529.85No
115575-GNVDEMale0NoNo34YesNoDSLYesNoYesNoNoNoOne yearNoMailed check56.951889.50No
223668-QPYBKMale0NoNo2YesNoDSLYesYesNoNoNoNoMonth-to-monthYesMailed check53.85108.15Yes
337795-CFOCWMale0NoNo45NoNo phone serviceDSLYesNoYesYesNoNoOne yearNoBank transfer (automatic)42.301840.75No
449237-HQITUFemale0NoNo2YesNoFiber opticNoNoNoNoNoNoMonth-to-monthYesElectronic check70.70151.65Yes
\n", "
" ], "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", " PhoneService MultipleLines InternetService OnlineSecurity OnlineBackup \\\n", "0 No No phone service DSL No Yes \n", "1 Yes No DSL Yes No \n", "2 Yes No DSL Yes Yes \n", "3 No No phone service DSL Yes No \n", "4 Yes 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 No \n", "1 No \n", "2 Yes \n", "3 No \n", "4 Yes " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_ori.reset_index(inplace=True) \n", "df_ori.head()" ] }, { "cell_type": "code", "execution_count": 12, "id": "d41dd2c6-8af6-4122-be89-4d693c928c0d", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.168025Z", "iopub.status.busy": "2026-03-24T17:55:00.167883Z", "iopub.status.idle": "2026-03-24T17:55:00.175582Z", "shell.execute_reply": "2026-03-24T17:55:00.175143Z", "shell.execute_reply.started": "2026-03-24T17:55:00.168013Z" } }, "outputs": [ { "data": { "text/html": [ "
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customerIDgenderSeniorCitizenPartnerDependentstenurePhoneServiceMultipleLinesInternetServiceOnlineSecurityOnlineBackupDeviceProtectionTechSupportStreamingTVStreamingMoviesContractPaperlessBillingPaymentMethodMonthlyChargesTotalChargesChurn
07590-VHVEGFemale0YesNo1NoNo phone serviceDSLNoYesNoNoNoNoMonth-to-monthYesElectronic check29.8529.85No
15575-GNVDEMale0NoNo34YesNoDSLYesNoYesNoNoNoOne yearNoMailed check56.951889.50No
23668-QPYBKMale0NoNo2YesNoDSLYesYesNoNoNoNoMonth-to-monthYesMailed check53.85108.15Yes
37795-CFOCWMale0NoNo45NoNo phone serviceDSLYesNoYesYesNoNoOne yearNoBank transfer (automatic)42.301840.75No
49237-HQITUFemale0NoNo2YesNoFiber opticNoNoNoNoNoNoMonth-to-monthYesElectronic check70.70151.65Yes
\n", "
" ], "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 No \n", "1 No \n", "2 Yes \n", "3 No \n", "4 Yes " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "if \"index\" in df_ori:\n", " df_ori.drop(\"index\", axis=1, inplace=True) \n", "df_ori.head()" ] }, { "cell_type": "markdown", "id": "2bcb9f9f-6afc-44d3-9eec-0b46c387e97e", "metadata": { "scrolled": true }, "source": [ "### Kunden-IDs? \n", "\n", "\n", "**Achtung!**\n", "Die customerIDs können jetzt nicht so schnell verworfen werden! Die brauchen wir, um die beiden Tabellen miteinander zu verknüpfen! " ] }, { "cell_type": "markdown", "id": "e24c36be-f44f-4e69-b454-79a5af6adfa9", "metadata": {}, "source": [ "#### Kategorische Spalten umwandeln\n", "Um die kategorischen Spalten richtig in numerische Spalten umzuwandeln, lass uns sie genauer anschauen und identifizieren, was sich hinter den Strings wirklich verbirgt. " ] }, { "cell_type": "markdown", "id": "9b1e7349-5dae-4796-8627-8a5c8a997f0d", "metadata": {}, "source": [ "### DatenAnalyse:\n" ] }, { "cell_type": "markdown", "id": "72796faa-19ee-4c59-9c1b-2eb6be5b988e", "metadata": {}, "source": [ "binary: \n", "gender, \n", "\n", "boolean: \n", "SeniorCitizen, Partner, Dependents, PhoneService, OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport, StreamingTV, StreamingMovies, PaperlessBilling\n", "\n", "categorical:\n", "MultipleLines, InternetService, Contract, PaymentMethod\n", "\n", "numeric:\n", "tenure, MonthlyCharges, TotalCharges" ] }, { "cell_type": "markdown", "id": "0cec4a64-4e8c-4923-90d6-42e9fa0927cd", "metadata": {}, "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" ] }, { "cell_type": "code", "execution_count": 13, "id": "eb317987-b060-4785-ae6a-000eb553096c", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.176096Z", "iopub.status.busy": "2026-03-24T17:55:00.176021Z", "iopub.status.idle": "2026-03-24T17:55:00.178015Z", "shell.execute_reply": "2026-03-24T17:55:00.177619Z", "shell.execute_reply.started": "2026-03-24T17:55:00.176088Z" } }, "outputs": [], "source": [ "cols_ori_binary = [\"gender\"]\n", "cols_ori_boolean = [\"SeniorCitizen\", \"Partner\", \"Dependents\", \"PhoneService\", \"OnlineSecurity\", \"OnlineBackup\", \n", " \"DeviceProtection\", \"TechSupport\", \"StreamingTV\", \"StreamingMovies\", \"PaperlessBilling\"]\n", "cols_ori_cat = [\"MultipleLines\", \"InternetService\", \"Contract\", \"PaymentMethod\"]\n", "cols_ori_numeric = [\"tenure\", \"MonthlyCharges\", \"TotalCharges\"]" ] }, { "cell_type": "code", "execution_count": 14, "id": "94c3ce3c-d99e-4582-8746-6f437d836360", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.178347Z", "iopub.status.busy": "2026-03-24T17:55:00.178275Z", "iopub.status.idle": "2026-03-24T17:55:00.182989Z", "shell.execute_reply": "2026-03-24T17:55:00.181854Z", "shell.execute_reply.started": "2026-03-24T17:55:00.178340Z" } }, "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": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Mapping von \"Female\" zu 1 und \"Male\" zu 0\n", "\n", "df_ori[\"gender\"] = df_ori[\"gender\"].map({\"Female\": 1, \"Male\": 0})\n", "df_ori[\"gender\"]" ] }, { "cell_type": "code", "execution_count": 15, "id": "10d5bda8-22f8-4bba-8767-8c77ddbae614", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.183388Z", "iopub.status.busy": "2026-03-24T17:55:00.183309Z", "iopub.status.idle": "2026-03-24T17:55:00.190273Z", "shell.execute_reply": "2026-03-24T17:55:00.189796Z", "shell.execute_reply.started": "2026-03-24T17:55:00.183381Z" } }, "outputs": [ { "data": { "text/html": [ "
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customerIDgenderSeniorCitizenPartnerDependentstenurePhoneServiceOnlineSecurityOnlineBackupDeviceProtectionTechSupportStreamingTVStreamingMoviesPaperlessBillingMonthlyChargesTotalChargesChurnMultipleLines_NoMultipleLines_No phone serviceMultipleLines_YesInternetService_DSLInternetService_Fiber opticInternetService_NoContract_Month-to-monthContract_One yearContract_Two yearPaymentMethod_Bank transfer (automatic)PaymentMethod_Credit card (automatic)PaymentMethod_Electronic checkPaymentMethod_Mailed check
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15575-GNVDE0000341101000056.951889.50NoTrueFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseTrue
23668-QPYBK000021110000153.85108.15YesTrueFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrue
37795-CFOCW0000450101100042.301840.75NoFalseTrueFalseTrueFalseFalseFalseTrueFalseTrueFalseFalseFalse
49237-HQITU100021000000170.70151.65YesTrueFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalse
.............................................................................................
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" ], "text/plain": [ " customerID gender SeniorCitizen Partner Dependents tenure \\\n", "0 7590-VHVEG 1 0 1 0 1 \n", "1 5575-GNVDE 0 0 0 0 34 \n", "2 3668-QPYBK 0 0 0 0 2 \n", "3 7795-CFOCW 0 0 0 0 45 \n", "4 9237-HQITU 1 0 0 0 2 \n", "... ... ... ... ... ... ... \n", "7027 6840-RESVB 0 0 1 1 24 \n", "7028 2234-XADUH 1 0 1 1 72 \n", "7029 4801-JZAZL 1 0 1 1 11 \n", "7030 8361-LTMKD 0 0 1 0 4 \n", "7031 3186-AJIEK 0 0 0 0 66 \n", "\n", " PhoneService OnlineSecurity OnlineBackup DeviceProtection \\\n", "0 0 0 1 0 \n", "1 1 1 0 1 \n", "2 1 1 1 0 \n", "3 0 1 0 1 \n", "4 1 0 0 0 \n", "... ... ... ... ... \n", "7027 1 1 0 1 \n", "7028 1 0 1 1 \n", "7029 0 1 0 0 \n", "7030 1 0 0 0 \n", "7031 1 1 0 1 \n", "\n", " TechSupport StreamingTV StreamingMovies PaperlessBilling \\\n", "0 0 0 0 1 \n", "1 0 0 0 0 \n", "2 0 0 0 1 \n", "3 1 0 0 0 \n", "4 0 0 0 1 \n", "... ... ... ... ... \n", "7027 1 1 1 1 \n", "7028 0 1 1 1 \n", "7029 0 0 0 1 \n", "7030 0 0 0 1 \n", "7031 1 1 1 1 \n", "\n", " MonthlyCharges TotalCharges Churn MultipleLines_No \\\n", "0 29.85 29.85 No False \n", "1 56.95 1889.50 No True \n", "2 53.85 108.15 Yes True \n", "3 42.30 1840.75 No False \n", "4 70.70 151.65 Yes True \n", "... ... ... ... ... \n", "7027 84.80 1990.50 No False \n", "7028 103.20 7362.90 No False \n", "7029 29.60 346.45 No False \n", "7030 74.40 306.60 Yes False \n", "7031 105.65 6844.50 No True \n", "\n", " MultipleLines_No phone service MultipleLines_Yes InternetService_DSL \\\n", "0 True False True \n", "1 False False True \n", "2 False False True \n", "3 True False True \n", "4 False False False \n", "... ... ... ... \n", "7027 False True True \n", "7028 False True False \n", "7029 True False True \n", "7030 False True False \n", "7031 False False False \n", "\n", " InternetService_Fiber optic InternetService_No \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 True False \n", "... ... ... \n", "7027 False False \n", "7028 True False \n", "7029 False False \n", "7030 True False \n", "7031 True False \n", "\n", " Contract_Month-to-month Contract_One year Contract_Two year \\\n", "0 True False False \n", "1 False True False \n", "2 True False False \n", "3 False True False \n", "4 True False False \n", "... ... ... ... \n", "7027 False True False \n", "7028 False True False \n", "7029 True False False \n", "7030 True False False \n", "7031 False False True \n", "\n", " PaymentMethod_Bank transfer (automatic) \\\n", "0 False \n", "1 False \n", "2 False \n", "3 True \n", "4 False \n", "... ... \n", "7027 False \n", "7028 False \n", "7029 False \n", "7030 False \n", "7031 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 30 columns]" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# One-Hot-Encoding für die drei kategorischen Spalten\n", "df_onehot_encoded = pd.get_dummies(df_ori, columns=cols_ori_cat) # dtype=int\n", "\n", "print(df_onehot_encoded.shape)\n", "df_onehot_encoded" ] }, { "cell_type": "code", "execution_count": 17, "id": "1b125ae7-0688-49ff-a17f-0ba75392a275", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.202711Z", "iopub.status.busy": "2026-03-24T17:55:00.202636Z", "iopub.status.idle": "2026-03-24T17:55:00.205040Z", "shell.execute_reply": "2026-03-24T17:55:00.204634Z", "shell.execute_reply.started": "2026-03-24T17:55:00.202704Z" } }, "outputs": [ { "data": { "text/plain": [ "['customerID',\n", " '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": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_onehot_encoded.columns.tolist()" ] }, { "cell_type": "code", "execution_count": 18, "id": "cd8ef306-4f02-4f3d-ae2c-228e42dea370", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.205552Z", "iopub.status.busy": "2026-03-24T17:55:00.205474Z", "iopub.status.idle": "2026-03-24T17:55:00.208479Z", "shell.execute_reply": "2026-03-24T17:55:00.208055Z", "shell.execute_reply.started": "2026-03-24T17:55:00.205545Z" } }, "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": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "index_label = df_onehot_encoded.columns.tolist().index(\"Churn\")\n", "print(df_ori.columns.tolist()[index_label])\n", "\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": 19, "id": "b96f4cd6-5c29-4c0b-9bd1-2908eb966ef4", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.208951Z", "iopub.status.busy": "2026-03-24T17:55:00.208878Z", "iopub.status.idle": "2026-03-24T17:55:00.212706Z", "shell.execute_reply": "2026-03-24T17:55:00.212312Z", "shell.execute_reply.started": "2026-03-24T17:55:00.208944Z" } }, "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": 20, "id": "8ab24cd8-c2b2-47b0-9e65-c442832ce4f9", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.213109Z", "iopub.status.busy": "2026-03-24T17:55:00.213033Z", "iopub.status.idle": "2026-03-24T17:55:00.222154Z", "shell.execute_reply": "2026-03-24T17:55:00.221413Z", "shell.execute_reply.started": "2026-03-24T17:55:00.213102Z" }, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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07590-VHVEG101010010000129.8529.85No0000000000000
15575-GNVDE0000341101000056.951889.50No0000000000000
23668-QPYBK000021110000153.85108.15Yes0000000000000
37795-CFOCW0000450101100042.301840.75No0000000000000
49237-HQITU100021000000170.70151.65Yes0000000000000
.............................................................................................
70276840-RESVB0011241101111184.801990.50No0000000000000
70282234-XADUH10117210110111103.207362.90No0000000000000
70294801-JZAZL1011110100000129.60346.45No0000000000000
70308361-LTMKD001041000000174.40306.60Yes0000000000000
70313186-AJIEK00006611011111105.656844.50No0000000000000
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7032 rows × 30 columns

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" ], "text/plain": [ " customerID gender SeniorCitizen Partner Dependents tenure \\\n", "0 7590-VHVEG 1 0 1 0 1 \n", "1 5575-GNVDE 0 0 0 0 34 \n", "2 3668-QPYBK 0 0 0 0 2 \n", "3 7795-CFOCW 0 0 0 0 45 \n", "4 9237-HQITU 1 0 0 0 2 \n", "... ... ... ... ... ... ... \n", "7027 6840-RESVB 0 0 1 1 24 \n", "7028 2234-XADUH 1 0 1 1 72 \n", "7029 4801-JZAZL 1 0 1 1 11 \n", "7030 8361-LTMKD 0 0 1 0 4 \n", "7031 3186-AJIEK 0 0 0 0 66 \n", "\n", " PhoneService OnlineSecurity OnlineBackup DeviceProtection \\\n", "0 0 0 1 0 \n", "1 1 1 0 1 \n", "2 1 1 1 0 \n", "3 0 1 0 1 \n", "4 1 0 0 0 \n", "... ... ... ... ... \n", "7027 1 1 0 1 \n", "7028 1 0 1 1 \n", "7029 0 1 0 0 \n", "7030 1 0 0 0 \n", "7031 1 1 0 1 \n", "\n", " TechSupport StreamingTV StreamingMovies PaperlessBilling \\\n", "0 0 0 0 1 \n", "1 0 0 0 0 \n", "2 0 0 0 1 \n", "3 1 0 0 0 \n", "4 0 0 0 1 \n", "... ... ... ... ... \n", "7027 1 1 1 1 \n", "7028 0 1 1 1 \n", "7029 0 0 0 1 \n", "7030 0 0 0 1 \n", "7031 1 1 1 1 \n", "\n", " MonthlyCharges TotalCharges Churn MultipleLines_No \\\n", "0 29.85 29.85 No 0 \n", "1 56.95 1889.50 No 0 \n", "2 53.85 108.15 Yes 0 \n", "3 42.30 1840.75 No 0 \n", "4 70.70 151.65 Yes 0 \n", "... ... ... ... ... \n", "7027 84.80 1990.50 No 0 \n", "7028 103.20 7362.90 No 0 \n", "7029 29.60 346.45 No 0 \n", "7030 74.40 306.60 Yes 0 \n", "7031 105.65 6844.50 No 0 \n", "\n", " MultipleLines_No phone service MultipleLines_Yes InternetService_DSL \\\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_Fiber optic InternetService_No \\\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", " Contract_Month-to-month Contract_One year Contract_Two 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", " PaymentMethod_Bank transfer (automatic) \\\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", " 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 30 columns]" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_onehot_encoded" ] }, { "cell_type": "markdown", "id": "082414a0-5bad-49c4-956e-246361fcdf0c", "metadata": {}, "source": [ "## Kunden-Service Datensatz\n", "\n", "Würden wir einen echten Kunden-Service Datensatz erhalten, müssten wir ihn genau so aufmerksam kontrollieren und checken, ob es missing fields gibt, etc. \n" ] }, { "cell_type": "code", "execution_count": 21, "id": "cf7acfe4-b348-4b72-9808-9b621813acff", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.222640Z", "iopub.status.busy": "2026-03-24T17:55:00.222546Z", "iopub.status.idle": "2026-03-24T17:55:00.228397Z", "shell.execute_reply": "2026-03-24T17:55:00.227887Z", "shell.execute_reply.started": "2026-03-24T17:55:00.222632Z" } }, "outputs": [ { "data": { "text/html": [ "
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ticket_idcustomer_idtime_requesttime_replychannelrequestreplysolvedoriginal_requestoriginal_ticket_id
07590-VHVEG_T17590-VHVEG2024-12-23 00:00:002024-12-23 14:28:40On-siteInternet funktioniert nichtTicket geschlossenTrueTrueNaN
17590-VHVEG_T17590-VHVEG2024-12-23 14:28:402024-12-23 20:20:22HotlineInternet funktioniert nichtAnfrage wird bearbeitetFalseFalse7590-VHVEG_T1
25575-GNVDE_T15575-GNVDE2023-09-03 00:00:002023-09-03 12:48:24EmailInternet funktioniert nichtProblem gelöstTrueTrueNaN
35575-GNVDE_T15575-GNVDE2023-09-04 12:48:242023-09-05 08:04:13Social MediaFrage zum VertragWeitere Informationen benötigtFalseFalse5575-GNVDE_T1
45575-GNVDE_T25575-GNVDE2024-12-16 00:00:002024-12-17 20:29:09On-siteInternet funktioniert nichtWeitere Informationen benötigtFalseTrueNaN
\n", "
" ], "text/plain": [ " ticket_id customer_id time_request time_reply \\\n", "0 7590-VHVEG_T1 7590-VHVEG 2024-12-23 00:00:00 2024-12-23 14:28:40 \n", "1 7590-VHVEG_T1 7590-VHVEG 2024-12-23 14:28:40 2024-12-23 20:20:22 \n", "2 5575-GNVDE_T1 5575-GNVDE 2023-09-03 00:00:00 2023-09-03 12:48:24 \n", "3 5575-GNVDE_T1 5575-GNVDE 2023-09-04 12:48:24 2023-09-05 08:04:13 \n", "4 5575-GNVDE_T2 5575-GNVDE 2024-12-16 00:00:00 2024-12-17 20:29:09 \n", "\n", " channel request reply \\\n", "0 On-site Internet funktioniert nicht Ticket geschlossen \n", "1 Hotline Internet funktioniert nicht Anfrage wird bearbeitet \n", "2 Email Internet funktioniert nicht Problem gelöst \n", "3 Social Media Frage zum Vertrag Weitere Informationen benötigt \n", "4 On-site Internet funktioniert nicht Weitere Informationen benötigt \n", "\n", " solved original_request original_ticket_id \n", "0 True True NaN \n", "1 False False 7590-VHVEG_T1 \n", "2 True True NaN \n", "3 False False 5575-GNVDE_T1 \n", "4 False True NaN " ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service.head()" ] }, { "cell_type": "markdown", "id": "e4340a25-40d7-4212-9b59-1d32323f750a", "metadata": {}, "source": [ "#### Datentyp Check" ] }, { "cell_type": "code", "execution_count": 22, "id": "ba0c0578-db2f-46b4-a86d-16196ea9bb11", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.228821Z", "iopub.status.busy": "2026-03-24T17:55:00.228739Z", "iopub.status.idle": "2026-03-24T17:55:00.231370Z", "shell.execute_reply": "2026-03-24T17:55:00.230978Z", "shell.execute_reply.started": "2026-03-24T17:55:00.228814Z" } }, "outputs": [ { "data": { "text/plain": [ "ticket_id str\n", "customer_id str\n", "time_request str\n", "time_reply str\n", "channel str\n", "request str\n", "reply str\n", "solved bool\n", "original_request bool\n", "original_ticket_id str\n", "dtype: object" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service.dtypes" ] }, { "cell_type": "code", "execution_count": 23, "id": "7e390567-9fd4-41b3-b6ed-3c3897168638", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.232314Z", "iopub.status.busy": "2026-03-24T17:55:00.232226Z", "iopub.status.idle": "2026-03-24T17:55:00.246067Z", "shell.execute_reply": "2026-03-24T17:55:00.245583Z", "shell.execute_reply.started": "2026-03-24T17:55:00.232307Z" } }, "outputs": [ { "data": { "text/plain": [ "ticket_id str\n", "customer_id str\n", "time_request datetime64[us]\n", "time_reply datetime64[us]\n", "channel str\n", "request str\n", "reply str\n", "solved bool\n", "original_request bool\n", "original_ticket_id str\n", "dtype: object" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Die datetime-Spalten müssen in deren Typ angepasst werden, alles andere kann in deren Original-Form bleiben (string)\n", "\n", "df_service[\"time_request\"] = pd.to_datetime(df_service[\"time_request\"], errors=\"coerce\")\n", "df_service[\"time_reply\"] = pd.to_datetime(df_service[\"time_reply\"], errors=\"coerce\")\n", "df_service.dtypes" ] }, { "cell_type": "code", "execution_count": 24, "id": "1636df43-1809-486b-a8d5-e11b6a814de3", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.246461Z", "iopub.status.busy": "2026-03-24T17:55:00.246348Z", "iopub.status.idle": "2026-03-24T17:55:00.250456Z", "shell.execute_reply": "2026-03-24T17:55:00.250035Z", "shell.execute_reply.started": "2026-03-24T17:55:00.246451Z" } }, "outputs": [ { "data": { "text/plain": [ "ticket_id 0\n", "customer_id 0\n", "time_request 0\n", "time_reply 0\n", "channel 0\n", "request 0\n", "reply 0\n", "solved 0\n", "original_request 0\n", "original_ticket_id 14140\n", "dtype: int64" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service.isnull().sum()" ] }, { "cell_type": "markdown", "id": "b91b0122-1fcf-49ed-afe7-73884013416a", "metadata": {}, "source": [ "Die große Anzahl an null-Werten in der original_ticket_id-Spalte sind in diesem Datensatz kein Fehler, sondern einleuchtend in der Logik (das wissen wir - haben wir selbst kreiert). \n", "\n", "Daher werden hier keine Daten gelöscht, sondern wir würden die leeren Datenfelder extrapolieren. \n", "\n", "Da es sich in dieser Spalte um alphanumerischen IDs handelt, ist die naheliegendste Lösung einen leeren String zu machen. Es ist keine Option, sie bei null zu belassen, da die Funktionen in den follow-up Schritten eine vollständig gefüllte Spalte benötigen." ] }, { "cell_type": "code", "execution_count": 25, "id": "d6f03c55-a853-4005-9b06-eadc0c769adb", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.250932Z", "iopub.status.busy": "2026-03-24T17:55:00.250740Z", "iopub.status.idle": "2026-03-24T17:55:00.254408Z", "shell.execute_reply": "2026-03-24T17:55:00.253978Z", "shell.execute_reply.started": "2026-03-24T17:55:00.250913Z" } }, "outputs": [ { "data": { "text/plain": [ "0 \n", "1 7590-VHVEG_T1\n", "2 \n", "3 5575-GNVDE_T1\n", "4 \n", " ... \n", "28153 6840-RESVB_T1\n", "28154 \n", "28155 4801-JZAZL_T1\n", "28156 \n", "28157 8361-LTMKD_T1\n", "Name: original_ticket_id, Length: 28158, dtype: str" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service[\"original_ticket_id\"].fillna(\"\", inplace=True)" ] }, { "cell_type": "code", "execution_count": 26, "id": "dbdff234-d327-4286-a9ac-df805a536a5a", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.254824Z", "iopub.status.busy": "2026-03-24T17:55:00.254745Z", "iopub.status.idle": "2026-03-24T17:55:00.258158Z", "shell.execute_reply": "2026-03-24T17:55:00.257730Z", "shell.execute_reply.started": "2026-03-24T17:55:00.254817Z" } }, "outputs": [ { "data": { "text/plain": [ "ticket_id 0\n", "customer_id 0\n", "time_request 0\n", "time_reply 0\n", "channel 0\n", "request 0\n", "reply 0\n", "solved 0\n", "original_request 0\n", "original_ticket_id 14140\n", "dtype: int64" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 27, "id": "656920f0-e23e-4851-ad21-a9885f41de7a", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.258510Z", "iopub.status.busy": "2026-03-24T17:55:00.258439Z", "iopub.status.idle": "2026-03-24T17:55:00.260905Z", "shell.execute_reply": "2026-03-24T17:55:00.260592Z", "shell.execute_reply.started": "2026-03-24T17:55:00.258503Z" } }, "outputs": [ { "data": { "text/plain": [ "Timestamp('2024-12-31 23:58:29')" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Dann wollen wir checken, ob es irgendein Datum gibt, das nach dem Stichtag ist \n", "df_service[\"time_request\"].max()" ] }, { "cell_type": "code", "execution_count": 28, "id": "21abe929-8ac9-4844-9ec2-f13523f311fb", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.261166Z", "iopub.status.busy": "2026-03-24T17:55:00.261101Z", "iopub.status.idle": "2026-03-24T17:55:00.263470Z", "shell.execute_reply": "2026-03-24T17:55:00.263016Z", "shell.execute_reply.started": "2026-03-24T17:55:00.261160Z" } }, "outputs": [ { "data": { "text/plain": [ "Timestamp('2024-12-31 23:59:39')" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service[\"time_reply\"].max()" ] }, { "cell_type": "markdown", "id": "d3247be3-c7e7-4093-8af9-2661028a4ed4", "metadata": {}, "source": [ "#### Logische Fehler Check" ] }, { "cell_type": "code", "execution_count": 29, "id": "b2831a52-dc31-474e-ba3e-13d81f981020", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.263878Z", "iopub.status.busy": "2026-03-24T17:55:00.263767Z", "iopub.status.idle": "2026-03-24T17:55:00.268838Z", "shell.execute_reply": "2026-03-24T17:55:00.268223Z", "shell.execute_reply.started": "2026-03-24T17:55:00.263866Z" } }, "outputs": [ { "data": { "text/html": [ "
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ticket_idcustomer_idtime_requesttime_replychannelrequestreplysolvedoriginal_requestoriginal_ticket_id
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [ticket_id, customer_id, time_request, time_reply, channel, request, reply, solved, original_request, original_ticket_id]\n", "Index: []" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Zudem wollen wir kontrollieren, ob es Fehler in der Logik gibt, z.b. time_reply vor time_request\n", "\n", "df_service[df_service[\"time_reply\"]\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ticket_idcustomer_idtime_requesttime_replychannelrequestreplysolvedoriginal_requestoriginal_ticket_id
07590-VHVEG_T17590-VHVEG2024-12-23 00:00:002024-12-23 14:28:40On-siteInternet funktioniert nichtTicket geschlossenTrueTrueNaN
17590-VHVEG_T17590-VHVEG2024-12-23 14:28:402024-12-23 20:20:22HotlineInternet funktioniert nichtAnfrage wird bearbeitetFalseFalse7590-VHVEG_T1
25575-GNVDE_T15575-GNVDE2023-09-03 00:00:002023-09-03 12:48:24EmailInternet funktioniert nichtProblem gelöstTrueTrueNaN
35575-GNVDE_T15575-GNVDE2023-09-04 12:48:242023-09-05 08:04:13Social MediaFrage zum VertragWeitere Informationen benötigtFalseFalse5575-GNVDE_T1
45575-GNVDE_T25575-GNVDE2024-12-16 00:00:002024-12-17 20:29:09On-siteInternet funktioniert nichtWeitere Informationen benötigtFalseTrueNaN
\n", "" ], "text/plain": [ " ticket_id customer_id time_request time_reply \\\n", "0 7590-VHVEG_T1 7590-VHVEG 2024-12-23 00:00:00 2024-12-23 14:28:40 \n", "1 7590-VHVEG_T1 7590-VHVEG 2024-12-23 14:28:40 2024-12-23 20:20:22 \n", "2 5575-GNVDE_T1 5575-GNVDE 2023-09-03 00:00:00 2023-09-03 12:48:24 \n", "3 5575-GNVDE_T1 5575-GNVDE 2023-09-04 12:48:24 2023-09-05 08:04:13 \n", "4 5575-GNVDE_T2 5575-GNVDE 2024-12-16 00:00:00 2024-12-17 20:29:09 \n", "\n", " channel request reply \\\n", "0 On-site Internet funktioniert nicht Ticket geschlossen \n", "1 Hotline Internet funktioniert nicht Anfrage wird bearbeitet \n", "2 Email Internet funktioniert nicht Problem gelöst \n", "3 Social Media Frage zum Vertrag Weitere Informationen benötigt \n", "4 On-site Internet funktioniert nicht Weitere Informationen benötigt \n", "\n", " solved original_request original_ticket_id \n", "0 True True NaN \n", "1 False False 7590-VHVEG_T1 \n", "2 True True NaN \n", "3 False False 5575-GNVDE_T1 \n", "4 False True NaN " ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service.head()" ] }, { "cell_type": "markdown", "id": "4e06cfdf-0f87-4187-8384-f6aa8e2ee73d", "metadata": {}, "source": [ "## EDA - Explorative Data Analysis (Daten Exploration)" ] }, { "cell_type": "markdown", "id": "dff0b75a-3862-4662-8384-2f45b4b143cb", "metadata": {}, "source": [ "Die EDA (Explorative Daten Analysis) des df_ori lassen wir in diesem Notebook aus, da wir es im letzten Notebook ausgiebig besprochen haben" ] }, { "cell_type": "markdown", "id": "9eaee5e0-0c6b-4b8a-9897-036f3d28747c", "metadata": {}, "source": [ "#### EDA df_service" ] }, { "cell_type": "code", "execution_count": 31, "id": "df3c9670-0a67-4280-b04f-1c978ee037c8", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.275315Z", "iopub.status.busy": "2026-03-24T17:55:00.275242Z", "iopub.status.idle": "2026-03-24T17:55:00.278521Z", "shell.execute_reply": "2026-03-24T17:55:00.278048Z", "shell.execute_reply.started": "2026-03-24T17:55:00.275308Z" } }, "outputs": [ { "data": { "text/plain": [ "channel\n", "On-site 5744\n", "Chat 5645\n", "Social Media 5625\n", "Hotline 5593\n", "Email 5551\n", "Name: count, dtype: int64" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service.value_counts(\"channel\", ascending=False)" ] }, { "cell_type": "code", "execution_count": 32, "id": "cbf3ba1b-58f8-477a-9b2c-c1285a12a463", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.278856Z", "iopub.status.busy": "2026-03-24T17:55:00.278788Z", "iopub.status.idle": "2026-03-24T17:55:00.282221Z", "shell.execute_reply": "2026-03-24T17:55:00.281418Z", "shell.execute_reply.started": "2026-03-24T17:55:00.278849Z" } }, "outputs": [ { "data": { "text/plain": [ "request\n", "Internet funktioniert nicht 5769\n", "Problem mit Rechnung 5675\n", "Frage zum Vertrag 5597\n", "Beschwerde über Kundenservice 5560\n", "Technische Störung 5557\n", "Name: count, dtype: int64" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service.value_counts(\"request\")" ] }, { "cell_type": "code", "execution_count": 33, "id": "d840cd77-95d4-496d-aa15-a43aa8fb646f", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.282810Z", "iopub.status.busy": "2026-03-24T17:55:00.282722Z", "iopub.status.idle": "2026-03-24T17:55:00.289893Z", "shell.execute_reply": "2026-03-24T17:55:00.289423Z", "shell.execute_reply.started": "2026-03-24T17:55:00.282802Z" } }, "outputs": [ { "data": { "text/plain": [ "request reply \n", "Beschwerde über Kundenservice Weitere Informationen benötigt 1401\n", " Anfrage wird bearbeitet 1390\n", " Ticket geschlossen 1387\n", " Problem gelöst 1382\n", "Frage zum Vertrag Ticket geschlossen 1429\n", " Weitere Informationen benötigt 1420\n", " Anfrage wird bearbeitet 1407\n", " Problem gelöst 1341\n", "Internet funktioniert nicht Problem gelöst 1477\n", " Anfrage wird bearbeitet 1476\n", " Ticket geschlossen 1417\n", " Weitere Informationen benötigt 1399\n", "Problem mit Rechnung Ticket geschlossen 1464\n", " Weitere Informationen benötigt 1450\n", " Problem gelöst 1401\n", " Anfrage wird bearbeitet 1360\n", "Technische Störung Weitere Informationen benötigt 1411\n", " Anfrage wird bearbeitet 1409\n", " Problem gelöst 1409\n", " Ticket geschlossen 1328\n", "Name: count, dtype: int64" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service[[\"request\", \"reply\"]].groupby([\"request\"]).value_counts(ascending=False)" ] }, { "cell_type": "code", "execution_count": 34, "id": "c6b6a447-0099-493b-921b-523ea2a9d146", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.290344Z", "iopub.status.busy": "2026-03-24T17:55:00.290257Z", "iopub.status.idle": "2026-03-24T17:55:00.293105Z", "shell.execute_reply": "2026-03-24T17:55:00.292727Z", "shell.execute_reply.started": "2026-03-24T17:55:00.290337Z" } }, "outputs": [ { "data": { "text/plain": [ "solved\n", "False 14123\n", "True 14035\n", "Name: count, dtype: int64" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service.value_counts(\"solved\", ascending=False)" ] }, { "cell_type": "code", "execution_count": 35, "id": "9d95ad30-64e5-4234-881a-a506f67112a5", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.293428Z", "iopub.status.busy": "2026-03-24T17:55:00.293358Z", "iopub.status.idle": "2026-03-24T17:55:00.300365Z", "shell.execute_reply": "2026-03-24T17:55:00.299793Z", "shell.execute_reply.started": "2026-03-24T17:55:00.293421Z" } }, "outputs": [ { "data": { "text/plain": [ "request solved\n", "Beschwerde über Kundenservice False 2791\n", " True 2769\n", "Frage zum Vertrag False 2827\n", " True 2770\n", "Internet funktioniert nicht True 2894\n", " False 2875\n", "Problem mit Rechnung True 2865\n", " False 2810\n", "Technische Störung False 2820\n", " True 2737\n", "Name: count, dtype: int64" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service[[\"request\",\"solved\"]].groupby([\"request\"]).value_counts(ascending=False)" ] }, { "cell_type": "code", "execution_count": 36, "id": "2f32b2de-6622-4414-994d-73791bb89cec", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.301003Z", "iopub.status.busy": "2026-03-24T17:55:00.300870Z", "iopub.status.idle": "2026-03-24T17:55:00.437304Z", "shell.execute_reply": "2026-03-24T17:55:00.436794Z", "shell.execute_reply.started": "2026-03-24T17:55:00.300994Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df_service.groupby(df_service[\"time_request\"].dt.month).count().plot(kind=\"bar\")" ] }, { "cell_type": "code", "execution_count": 37, "id": "7cc17757-a0d9-4a6c-afee-8c353d595df2", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.437729Z", "iopub.status.busy": "2026-03-24T17:55:00.437642Z", "iopub.status.idle": "2026-03-24T17:55:00.545157Z", "shell.execute_reply": "2026-03-24T17:55:00.544579Z", "shell.execute_reply.started": "2026-03-24T17:55:00.437722Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df_service.groupby(df_service[\"time_reply\"].dt.month).count().plot(kind=\"bar\")" ] }, { "cell_type": "markdown", "id": "50e5611f-2a6d-4b97-8b1e-3d69c8861374", "metadata": {}, "source": [ "## Feature Engineering" ] }, { "cell_type": "code", "execution_count": 38, "id": "2245369d-854a-471c-b361-ca914c6dd5a8", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.545587Z", "iopub.status.busy": "2026-03-24T17:55:00.545497Z", "iopub.status.idle": "2026-03-24T17:55:00.548942Z", "shell.execute_reply": "2026-03-24T17:55:00.547698Z", "shell.execute_reply.started": "2026-03-24T17:55:00.545579Z" } }, "outputs": [], "source": [ "# Definiere den Stichtag für die Features\n", "stichtag = pd.to_datetime(\"2024-12-31\")\n", "\n", "# Wir werden viele verschiedene Features erstellen, diese werden erst gesammelt und später zum DataFrame umgewandelt\n", "dict_features = {}" ] }, { "cell_type": "markdown", "id": "031d025c-bb60-4ec3-9973-c9ae64cc342a", "metadata": {}, "source": [ "### Feature-Gruppe 1: Anzahl der Requests im letzten Monat" ] }, { "cell_type": "code", "execution_count": 39, "id": "8d174937-9b0a-44e3-8f1b-677d71f2bcc3", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.549402Z", "iopub.status.busy": "2026-03-24T17:55:00.549297Z", "iopub.status.idle": "2026-03-24T17:55:00.554479Z", "shell.execute_reply": "2026-03-24T17:55:00.553820Z", "shell.execute_reply.started": "2026-03-24T17:55:00.549393Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "customer_id\n", "0013-EXCHZ 6\n", "0015-UOCOJ 1\n", "0021-IKXGC 13\n", "0023-HGHWL 3\n", "0030-FNXPP 3\n", "Name: num_request_last_1_month, dtype: int64\n" ] } ], "source": [ "# Definiere den Cutoff für die letzten 1 Monat\n", "cutoff_1m = stichtag - pd.DateOffset(months=1)\n", "\n", "# Filtere die Anfragen, die ab dem Cutoff bis zum Stichtag erfolgen\n", "recent_requests = df_service[df_service[\"time_request\"] >= cutoff_1m]\n", "\n", "# Zähle pro Kunde die Anzahl der Requests\n", "num_request_last_1m = recent_requests.groupby(\"customer_id\").size().rename(\"num_request_last_1_month\")\n", "\n", "# Ausgabe: Beispieldatensatz\n", "print(num_request_last_1m.head())" ] }, { "cell_type": "code", "execution_count": 40, "id": "ccb5abab-38e7-43a5-8c8a-797dacfd2683", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.554936Z", "iopub.status.busy": "2026-03-24T17:55:00.554843Z", "iopub.status.idle": "2026-03-24T17:55:00.568363Z", "shell.execute_reply": "2026-03-24T17:55:00.567783Z", "shell.execute_reply.started": "2026-03-24T17:55:00.554928Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dict_keys(['num_request_last_1_months', 'num_request_last_3_months', 'num_request_last_6_months', 'num_request_last_12_months'])\n" ] }, { "data": { "text/plain": [ "{'num_request_last_1_months': customer_id\n", " 0013-EXCHZ 6\n", " 0015-UOCOJ 1\n", " 0021-IKXGC 13\n", " 0023-HGHWL 3\n", " 0030-FNXPP 3\n", " ..\n", " 9972-NKTFD 1\n", " 9975-SKRNR 3\n", " 9985-MWVIX 3\n", " 9986-BONCE 3\n", " 9992-UJOEL 1\n", " Name: num_request_last_1_months, Length: 1365, dtype: int64,\n", " 'num_request_last_3_months': customer_id\n", " 0003-MKNFE 3\n", " 0004-TLHLJ 3\n", " 0013-EXCHZ 9\n", " 0015-UOCOJ 1\n", " 0018-NYROU 1\n", " ..\n", " 9986-BONCE 9\n", " 9987-LUTYD 3\n", " 9992-RRAMN 3\n", " 9992-UJOEL 1\n", " 9995-HOTOH 2\n", " Name: num_request_last_3_months, Length: 2338, dtype: int64,\n", " 'num_request_last_6_months': customer_id\n", " 0002-ORFBO 1\n", " 0003-MKNFE 4\n", " 0004-TLHLJ 3\n", " 0013-EXCHZ 9\n", " 0013-MHZWF 4\n", " ..\n", " 9986-BONCE 11\n", " 9987-LUTYD 8\n", " 9992-RRAMN 6\n", " 9992-UJOEL 1\n", " 9995-HOTOH 2\n", " Name: num_request_last_6_months, Length: 3191, dtype: int64,\n", " 'num_request_last_12_months': customer_id\n", " 0002-ORFBO 3\n", " 0003-MKNFE 4\n", " 0004-TLHLJ 3\n", " 0011-IGKFF 1\n", " 0013-EXCHZ 9\n", " ..\n", " 9986-BONCE 11\n", " 9987-LUTYD 8\n", " 9992-RRAMN 6\n", " 9992-UJOEL 1\n", " 9995-HOTOH 2\n", " Name: num_request_last_12_months, Length: 4198, dtype: int64}" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Anzahl Requests in den letzten 6, 9 etc Monaten\n", "\n", "months_interest = [1, 3, 6, 12]\n", "\n", "for mon in months_interest:\n", " # Definiere den Cutoff für die letzten 3 Monate\n", " cutoff = stichtag - pd.DateOffset(months=mon)\n", " \n", " # Filtere die Anfragen, die ab dem Cutoff bis zum Stichtag erfolgen\n", " recent_requests = df_service[df_service[\"time_request\"] >= cutoff]\n", " \n", " # Zähle pro Kunde die Anzahl der Requests\n", " col_new = \"num_request_last_\"+str(mon)+\"_months\"\n", " num_request_period = recent_requests.groupby(\"customer_id\").size().rename(col_new)\n", " \n", " # Füge das Ergebnis dem features_df hinzu. Da die customer_ids als Index genutzt werden, eignet sich join()\n", " # df_features = df_features.join(num_request_period, how='left')\n", " dict_features[col_new] = num_request_period\n", "\n", "print(dict_features.keys())\n", "dict_features" ] }, { "cell_type": "markdown", "id": "51a924d7-b03e-4251-b601-92b580d3db5f", "metadata": {}, "source": [ "## Feature-Gruppe 2 & 3: Zeit bis Lösung und Anzahl der Thread-Iterationen pro Ticket\n", "\n", "Hierfür müssen wir zuerst nach Ticket-ID gruppieren, um pro Ticket den Zeitraum von der ursprünglichen Anfrage bis zur ersten als gelöst markierten Antwort zu bestimmen.\n", "\n", "Falls ein Ticket nie als gelöst markiert wurde, ignorieren wir es in der Berechnung." ] }, { "cell_type": "code", "execution_count": 41, "id": "2f2fb5da-8b54-442b-9365-73eca3667cf6", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.568817Z", "iopub.status.busy": "2026-03-24T17:55:00.568731Z", "iopub.status.idle": "2026-03-24T17:55:00.571330Z", "shell.execute_reply": "2026-03-24T17:55:00.570771Z", "shell.execute_reply.started": "2026-03-24T17:55:00.568810Z" } }, "outputs": [], "source": [ "def compute_ticket_metrics(ticket):\n", " \"\"\"\n", " Für ein Ticket (alle Interaktionen mit gleicher ticket_id):\n", " - Ermittle die Zeitdifferenz (in Tagen) zwischen der ersten Anfrage und der ersten Antwort, die das Ticket als gelöst markiert.\n", " - Bestimme die Anzahl der Interaktionen (Thread-Iterationen) bis zur Lösung.\n", " \"\"\"\n", " ticket_sorted = ticket.sort_values(\"time_request\")\n", " \n", " # Die erste Anfrage (wir gehen davon aus, dass die erste Zeile die originale Anfrage ist)\n", " orig_time = ticket_sorted.iloc[0][\"time_request\"]\n", " \n", " # Finde die erste Interaktion, bei der solved True ist\n", " solved_interactions = ticket_sorted[ticket_sorted[\"solved\"] == True]\n", "\n", " if len(solved_interactions) > 0:\n", " solved_time = solved_interactions.iloc[0][\"time_reply\"]\n", " days_to_solution = (solved_time - orig_time).days\n", " # Ermittle die Position (Index im sortierten Ticket), beginnend bei 1\n", " thread_count = ticket_sorted.reset_index().index[ticket_sorted.reset_index()[\"solved\"] == True][0] + 1\n", " else:\n", " days_to_solution = np.nan\n", " thread_count = np.nan\n", " return pd.Series({\"days_to_solution\": days_to_solution, \"thread_count\": thread_count})" ] }, { "cell_type": "code", "execution_count": 42, "id": "1cfefc50-2ed9-4077-8e4e-06b524df25d7", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:00.571744Z", "iopub.status.busy": "2026-03-24T17:55:00.571647Z", "iopub.status.idle": "2026-03-24T17:55:10.191960Z", "shell.execute_reply": "2026-03-24T17:55:10.191474Z", "shell.execute_reply.started": "2026-03-24T17:55:00.571736Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " days_to_solution thread_count\n", "ticket_id \n", "0002-ORFBO_T1 0.0 1.0\n", "0003-MKNFE_T1 NaN NaN\n", "0003-MKNFE_T2 0.0 1.0\n", "0004-TLHLJ_T1 0.0 1.0\n", "0011-IGKFF_T1 NaN NaN" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Berechne Ticket-Metriken pro Ticket\n", "ticket_metrics = df_service.groupby(\"ticket_id\").apply(compute_ticket_metrics)\n", "ticket_metrics.head()" ] }, { "cell_type": "code", "execution_count": 43, "id": "e4170f6f-13eb-466b-9355-412a6bc1295b", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.192657Z", "iopub.status.busy": "2026-03-24T17:55:10.192378Z", "iopub.status.idle": "2026-03-24T17:55:10.198234Z", "shell.execute_reply": "2026-03-24T17:55:10.197742Z", "shell.execute_reply.started": "2026-03-24T17:55:10.192645Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " ticket_id customer_id time_request time_reply channel \\\n", "13706 0003-MKNFE_T1 0003-MKNFE 2024-08-08 2024-08-09 11:28:34 On-site \n", "\n", " request reply solved \\\n", "13706 Beschwerde über Kundenservice Anfrage wird bearbeitet False \n", "\n", " original_request original_ticket_id \n", "13706 True NaN " ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service[df_service[\"ticket_id\"]==\"0003-MKNFE_T1\"]" ] }, { "cell_type": "code", "execution_count": 44, "id": "ad418a4c-2b43-4e25-b91e-d7783b976a35", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.198832Z", "iopub.status.busy": "2026-03-24T17:55:10.198759Z", "iopub.status.idle": "2026-03-24T17:55:10.212784Z", "shell.execute_reply": "2026-03-24T17:55:10.212279Z", "shell.execute_reply.started": "2026-03-24T17:55:10.198824Z" } }, "outputs": [ { "data": { "text/html": [ "
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days_to_solutionthread_countcustomer_id
ticket_id
0002-ORFBO_T10.01.00002-ORFBO
0003-MKNFE_T1NaNNaN0003-MKNFE
0003-MKNFE_T20.01.00003-MKNFE
0004-TLHLJ_T10.01.00004-TLHLJ
0011-IGKFF_T1NaNNaN0011-IGKFF
............
9992-RRAMN_T31.01.09992-RRAMN
9992-UJOEL_T1NaNNaN9992-UJOEL
9993-LHIEB_T11.01.09993-LHIEB
9995-HOTOH_T11.02.09995-HOTOH
9995-HOTOH_T21.01.09995-HOTOH
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14140 rows × 3 columns

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" ], "text/plain": [ " days_to_solution thread_count customer_id\n", "ticket_id \n", "0002-ORFBO_T1 0.0 1.0 0002-ORFBO\n", "0003-MKNFE_T1 NaN NaN 0003-MKNFE\n", "0003-MKNFE_T2 0.0 1.0 0003-MKNFE\n", "0004-TLHLJ_T1 0.0 1.0 0004-TLHLJ\n", "0011-IGKFF_T1 NaN NaN 0011-IGKFF\n", "... ... ... ...\n", "9992-RRAMN_T3 1.0 1.0 9992-RRAMN\n", "9992-UJOEL_T1 NaN NaN 9992-UJOEL\n", "9993-LHIEB_T1 1.0 1.0 9993-LHIEB\n", "9995-HOTOH_T1 1.0 2.0 9995-HOTOH\n", "9995-HOTOH_T2 1.0 1.0 9995-HOTOH\n", "\n", "[14140 rows x 3 columns]" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Füge die customer_id (die für alle Interaktionen in einem Ticket gleich ist) hinzu\n", "ticket_customer = df_service.groupby(\"ticket_id\")[\"customer_id\"].first().to_frame()\n", "ticket_metrics = ticket_metrics.merge(ticket_customer, left_index=True, right_index=True)\n", "ticket_metrics" ] }, { "cell_type": "code", "execution_count": 45, "id": "77cbc935-37fe-4d25-a977-5a7ca3c49d56", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.213185Z", "iopub.status.busy": "2026-03-24T17:55:10.213107Z", "iopub.status.idle": "2026-03-24T17:55:10.218999Z", "shell.execute_reply": "2026-03-24T17:55:10.218555Z", "shell.execute_reply.started": "2026-03-24T17:55:10.213177Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "customer_id\n", "0002-ORFBO 0.0\n", "0003-MKNFE 0.0\n", "0004-TLHLJ 0.0\n", "0011-IGKFF NaN\n", "0013-EXCHZ 1.0\n", "Name: avg_days_till_solution, dtype: float64\n", "customer_id\n", "0002-ORFBO 1.00\n", "0003-MKNFE 1.00\n", "0004-TLHLJ 1.00\n", "0011-IGKFF NaN\n", "0013-EXCHZ 1.25\n", "Name: avg_thread_till_solution, dtype: float64\n" ] } ], "source": [ "# Aggregiere pro Kunde (nur Tickets, die gelöst wurden)\n", "avg_days_till_solution = ticket_metrics.groupby(\"customer_id\")[\"days_to_solution\"].mean().rename(\"avg_days_till_solution\")\n", "avg_thread_till_solution = ticket_metrics.groupby(\"customer_id\")[\"thread_count\"].mean().rename(\"avg_thread_till_solution\")\n", "\n", "print(avg_days_till_solution.head())\n", "print(avg_thread_till_solution.head())" ] }, { "cell_type": "code", "execution_count": 46, "id": "accdd06c-4c8b-4248-b5c8-cec1ba2c1e07", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.219388Z", "iopub.status.busy": "2026-03-24T17:55:10.219311Z", "iopub.status.idle": "2026-03-24T17:55:10.220920Z", "shell.execute_reply": "2026-03-24T17:55:10.220608Z", "shell.execute_reply.started": "2026-03-24T17:55:10.219380Z" } }, "outputs": [], "source": [ "dict_features[\"avg_num_days_till_solution\"] = avg_days_till_solution\n", "dict_features[\"avg_num_thread_till_solution\"] = avg_thread_till_solution" ] }, { "cell_type": "code", "execution_count": 47, "id": "bab627c7-d7c1-487c-bfd8-7ed7bddf8e1f", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.221230Z", "iopub.status.busy": "2026-03-24T17:55:10.221170Z", "iopub.status.idle": "2026-03-24T17:55:10.223882Z", "shell.execute_reply": "2026-03-24T17:55:10.223401Z", "shell.execute_reply.started": "2026-03-24T17:55:10.221223Z" } }, "outputs": [ { "data": { "text/plain": [ "dict_keys(['num_request_last_1_months', 'num_request_last_3_months', 'num_request_last_6_months', 'num_request_last_12_months', 'avg_num_days_till_solution', 'avg_num_thread_till_solution'])" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dict_features.keys()" ] }, { "cell_type": "markdown", "id": "7f52a380-9d2e-4799-8fb0-af7b1ad85d73", "metadata": {}, "source": [ "### Feature-Gruppe 4 & 5: Zuletzt benutzter Kanal und am häufigsten genutzter Kanal in den letzten 6 Monaten" ] }, { "cell_type": "code", "execution_count": 48, "id": "35d4ba8b-80e4-48e4-815e-3cf468ae2460", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.224363Z", "iopub.status.busy": "2026-03-24T17:55:10.224300Z", "iopub.status.idle": "2026-03-24T17:55:10.518606Z", "shell.execute_reply": "2026-03-24T17:55:10.517919Z", "shell.execute_reply.started": "2026-03-24T17:55:10.224356Z" }, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "customer_id\n", "0002-ORFBO Hotline\n", "0003-MKNFE Social Media\n", "0004-TLHLJ Social Media\n", "0011-IGKFF Social Media\n", "0013-EXCHZ Email\n", "Name: last_channel_used, dtype: str\n", "customer_id\n", "0002-ORFBO Hotline\n", "0003-MKNFE Email\n", "0004-TLHLJ Chat\n", "0013-EXCHZ Chat\n", "0013-MHZWF On-site\n", "Name: channel_used_most_last_6_months, dtype: str\n" ] } ], "source": [ "# Last channel used: Finde pro Kunde die letzte Interaktion (Sortierung nach time_request)\n", "last_channel = df_service.sort_values(\"time_request\").groupby(\"customer_id\").last()[\"channel\"].rename(\"last_channel_used\")\n", "\n", "# den meist genutzten Channel in letzten 6 Monaten\n", "# zuerst den Zeitraum auf die letzten 6 Monate eingrenzen\n", "cutoff_6m = stichtag - pd.DateOffset(months=6)\n", "channels_last_6m = df_service[df_service[\"time_request\"] >= cutoff_6m]\n", "\n", "# Bestimme pro Kunde den am häufigsten auftretenden Kanal in diesem Zeitraum. Falls es mehrere Modi gibt, nimm den ersten.\n", "channel_most_used_last6mo = channels_last_6m.groupby(\"customer_id\")[\"channel\"].agg(lambda x: x.mode().iloc[0] if not x.mode().empty else np.nan)\\\n", " .rename(\"channel_used_most_last_6_months\")\n", "\n", "print(last_channel.head())\n", "print(channel_most_used_last6mo.head())" ] }, { "cell_type": "code", "execution_count": 49, "id": "007c74bc-74f8-4af4-9409-7d89e8603009", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.519229Z", "iopub.status.busy": "2026-03-24T17:55:10.519136Z", "iopub.status.idle": "2026-03-24T17:55:10.521153Z", "shell.execute_reply": "2026-03-24T17:55:10.520761Z", "shell.execute_reply.started": "2026-03-24T17:55:10.519220Z" } }, "outputs": [], "source": [ "dict_features[\"last_channel\"] = last_channel\n", "dict_features[\"channel_most_used_last6mo\"] = channel_most_used_last6mo" ] }, { "cell_type": "code", "execution_count": 50, "id": "40980105-4d4a-4068-a8db-1983b9996d66", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.521571Z", "iopub.status.busy": "2026-03-24T17:55:10.521493Z", "iopub.status.idle": "2026-03-24T17:55:10.524324Z", "shell.execute_reply": "2026-03-24T17:55:10.523462Z", "shell.execute_reply.started": "2026-03-24T17:55:10.521554Z" } }, "outputs": [ { "data": { "text/plain": [ "dict_keys(['num_request_last_1_months', 'num_request_last_3_months', 'num_request_last_6_months', 'num_request_last_12_months', 'avg_num_days_till_solution', 'avg_num_thread_till_solution', 'last_channel', 'channel_most_used_last6mo'])" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dict_features.keys()" ] }, { "cell_type": "markdown", "id": "4de7e1f5-7e36-4c7c-a9b8-59a58e50b709", "metadata": {}, "source": [ "### Feature-Gruppe 5: Weitere Features – Gesamtzahl Tickets, Interaktionen, durchschnittliche Reply-Zeit und textbasierte Features" ] }, { "cell_type": "code", "execution_count": 51, "id": "b4df1fa1-6a10-478d-8b2a-e2a5ca9ab228", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.524686Z", "iopub.status.busy": "2026-03-24T17:55:10.524618Z", "iopub.status.idle": "2026-03-24T17:55:10.542037Z", "shell.execute_reply": "2026-03-24T17:55:10.541166Z", "shell.execute_reply.started": "2026-03-24T17:55:10.524679Z" }, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "customer_id\n", "0002-ORFBO 1\n", "0003-MKNFE 2\n", "0004-TLHLJ 1\n", "0011-IGKFF 2\n", "0013-EXCHZ 5\n", "Name: total_tickets, dtype: int64\n", "customer_id\n", "0002-ORFBO 3\n", "0003-MKNFE 4\n", "0004-TLHLJ 3\n", "0011-IGKFF 3\n", "0013-EXCHZ 9\n", "Name: total_interactions, dtype: int64\n", "customer_id\n", "0002-ORFBO 19.058148\n", "0003-MKNFE 22.865833\n", "0004-TLHLJ 7.966481\n", "0011-IGKFF 11.924352\n", "0013-EXCHZ 23.818210\n", "Name: avg_reply_delay_hours, dtype: float64\n", "customer_id\n", "0002-ORFBO 1\n", "0003-MKNFE 3\n", "0004-TLHLJ 1\n", "0011-IGKFF 2\n", "0013-EXCHZ 1\n", "Name: num_complaint_requests, dtype: int64\n" ] } ], "source": [ "# Gesamtzahl der Tickets pro Kunde\n", "total_tickets = df_service.groupby(\"customer_id\")[\"ticket_id\"].nunique().rename(\"total_tickets\")\n", "\n", "# Gesamtzahl der Interaktionen pro Kunde\n", "total_interactions = df_service.groupby(\"customer_id\").size().rename(\"total_interactions\")\n", "\n", "# Durchschnittliche Reply-Verzögerung (in Stunden) pro Interaktion\n", "df_service[\"reply_delay_hours\"] = (df_service[\"time_reply\"] - df_service[\"time_request\"]).dt.total_seconds() / 3600\n", "avg_reply_delay = df_service.groupby(\"customer_id\")[\"reply_delay_hours\"].mean().rename(\"avg_reply_delay_hours\")\n", "\n", "# Textbasierte Features:\n", "# Zähle, wie oft im Request-Text Begriffe wie \"Problem\" oder \"Beschwerde\" auftauchen\n", "df_service[\"is_complaint\"] = df_service[\"request\"].str.contains(\"Problem|Beschwerde\", case=False, regex=True)\n", "num_complaint_requests = df_service.groupby(\"customer_id\")[\"is_complaint\"].sum().rename(\"num_complaint_requests\")\n", "\n", "print(total_tickets.head())\n", "print(total_interactions.head())\n", "print(avg_reply_delay.head())\n", "print(num_complaint_requests.head())" ] }, { "cell_type": "code", "execution_count": 52, "id": "1ff24345-e2cd-4c31-9b66-278587a93938", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.542686Z", "iopub.status.busy": "2026-03-24T17:55:10.542408Z", "iopub.status.idle": "2026-03-24T17:55:10.546156Z", "shell.execute_reply": "2026-03-24T17:55:10.545728Z", "shell.execute_reply.started": "2026-03-24T17:55:10.542674Z" } }, "outputs": [], "source": [ "dict_features[\"total_tickets\"] = total_tickets\n", "dict_features[\"total_interactions\"] = total_interactions\n", "dict_features[\"avg_reply_delay\"] = avg_reply_delay\n", "dict_features[\"num_complaint_requests\"] = num_complaint_requests" ] }, { "cell_type": "code", "execution_count": 53, "id": "940d27f4-6f2f-41af-aae6-11372db4dd47", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.546656Z", "iopub.status.busy": "2026-03-24T17:55:10.546559Z", "iopub.status.idle": "2026-03-24T17:55:10.549426Z", "shell.execute_reply": "2026-03-24T17:55:10.549100Z", "shell.execute_reply.started": "2026-03-24T17:55:10.546649Z" } }, "outputs": [ { "data": { "text/plain": [ "dict_keys(['num_request_last_1_months', 'num_request_last_3_months', 'num_request_last_6_months', 'num_request_last_12_months', 'avg_num_days_till_solution', 'avg_num_thread_till_solution', 'last_channel', 'channel_most_used_last6mo', 'total_tickets', 'total_interactions', 'avg_reply_delay', 'num_complaint_requests'])" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dict_features.keys()" ] }, { "cell_type": "markdown", "id": "d31b19ba-8488-4f14-b455-b822a963847e", "metadata": {}, "source": [ "### Zusammenführen aller Features " ] }, { "cell_type": "code", "execution_count": 54, "id": "f90c55e2-93fb-4d52-aecd-a6a99a1d303b", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.549834Z", "iopub.status.busy": "2026-03-24T17:55:10.549766Z", "iopub.status.idle": "2026-03-24T17:55:10.570244Z", "shell.execute_reply": "2026-03-24T17:55:10.569902Z", "shell.execute_reply.started": "2026-03-24T17:55:10.549827Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(6096, 13)\n" ] }, { "data": { "text/html": [ "
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customer_idnum_request_last_1_monthsnum_request_last_3_monthsnum_request_last_6_monthsnum_request_last_12_monthsavg_num_days_till_solutionavg_num_thread_till_solutionlast_channelchannel_most_used_last6mototal_ticketstotal_interactionsavg_reply_delaynum_complaint_requests
00002-ORFBONaNNaN1.03.00.01.00HotlineHotline1319.0581481
10003-MKNFENaN3.04.04.00.01.00Social MediaEmail2422.8658333
20004-TLHLJNaN3.03.03.00.01.00Social MediaChat137.9664811
30011-IGKFFNaNNaNNaN1.0NaNNaNSocial MediaNaN2311.9243522
40013-EXCHZ6.09.09.09.01.01.25EmailChat5923.8182101
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" ], "text/plain": [ " customer_id num_request_last_1_months num_request_last_3_months \\\n", "0 0002-ORFBO NaN NaN \n", "1 0003-MKNFE NaN 3.0 \n", "2 0004-TLHLJ NaN 3.0 \n", "3 0011-IGKFF NaN NaN \n", "4 0013-EXCHZ 6.0 9.0 \n", "\n", " num_request_last_6_months num_request_last_12_months \\\n", "0 1.0 3.0 \n", "1 4.0 4.0 \n", "2 3.0 3.0 \n", "3 NaN 1.0 \n", "4 9.0 9.0 \n", "\n", " avg_num_days_till_solution avg_num_thread_till_solution last_channel \\\n", "0 0.0 1.00 Hotline \n", "1 0.0 1.00 Social Media \n", "2 0.0 1.00 Social Media \n", "3 NaN NaN Social Media \n", "4 1.0 1.25 Email \n", "\n", " channel_most_used_last6mo total_tickets total_interactions \\\n", "0 Hotline 1 3 \n", "1 Email 2 4 \n", "2 Chat 1 3 \n", "3 NaN 2 3 \n", "4 Chat 5 9 \n", "\n", " avg_reply_delay num_complaint_requests \n", "0 19.058148 1 \n", "1 22.865833 3 \n", "2 7.966481 1 \n", "3 11.924352 2 \n", "4 23.818210 1 " ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Fasse alle aggregierten Features in einem DataFrame zusammen\n", "df_features = pd.DataFrame(dict_features).reset_index()\n", "\n", "print(df_features.shape)\n", "df_features.head()" ] }, { "cell_type": "code", "execution_count": 55, "id": "7a30883e-b015-44b2-ae08-d5ad4a906e31", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.570796Z", "iopub.status.busy": "2026-03-24T17:55:10.570723Z", "iopub.status.idle": "2026-03-24T17:55:10.576202Z", "shell.execute_reply": "2026-03-24T17:55:10.575750Z", "shell.execute_reply.started": "2026-03-24T17:55:10.570788Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 6096 entries, 0 to 6095\n", "Data columns (total 13 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 customer_id 6096 non-null str \n", " 1 num_request_last_1_months 1365 non-null float64\n", " 2 num_request_last_3_months 2338 non-null float64\n", " 3 num_request_last_6_months 3191 non-null float64\n", " 4 num_request_last_12_months 4198 non-null float64\n", " 5 avg_num_days_till_solution 5384 non-null float64\n", " 6 avg_num_thread_till_solution 5384 non-null float64\n", " 7 last_channel 6096 non-null str \n", " 8 channel_most_used_last6mo 3191 non-null str \n", " 9 total_tickets 6096 non-null int64 \n", " 10 total_interactions 6096 non-null int64 \n", " 11 avg_reply_delay 6096 non-null float64\n", " 12 num_complaint_requests 6096 non-null int64 \n", "dtypes: float64(7), int64(3), str(3)\n", "memory usage: 741.0 KB\n" ] } ], "source": [ "df_features.info()" ] }, { "cell_type": "code", "execution_count": 56, "id": "546f46bd-106a-4dde-9ea6-31d00b140970", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.576647Z", "iopub.status.busy": "2026-03-24T17:55:10.576568Z", "iopub.status.idle": "2026-03-24T17:55:10.579566Z", "shell.execute_reply": "2026-03-24T17:55:10.579115Z", "shell.execute_reply.started": "2026-03-24T17:55:10.576640Z" } }, "outputs": [ { "data": { "text/plain": [ "customer_id 0\n", "num_request_last_1_months 4731\n", "num_request_last_3_months 3758\n", "num_request_last_6_months 2905\n", "num_request_last_12_months 1898\n", "avg_num_days_till_solution 712\n", "avg_num_thread_till_solution 712\n", "last_channel 0\n", "channel_most_used_last6mo 2905\n", "total_tickets 0\n", "total_interactions 0\n", "avg_reply_delay 0\n", "num_complaint_requests 0\n", "dtype: int64" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_features.isnull().sum()" ] }, { "cell_type": "markdown", "id": "34419bf3-8cc8-425e-8f13-d3f21ac62319", "metadata": {}, "source": [ "### Null-Werte\n", "Leere Werte auffüllen - hierbei darauf achten, dass zwischen verschiedenen Datentypen wieder unterschieden werden muss.\n", "\n", "In diesem Fall muss man nicht manuell durch alle Spalten durchgehen, sondern kann sich direkt die dtypes zu Nutze machen. " ] }, { "cell_type": "markdown", "id": "fe1c1c5f-2f83-4e0a-8efd-f92b2a09c7f1", "metadata": {}, "source": [ "### Lösung durch Schleife (ineffizient) vs. pythonic Lösung mit select_dtypes (effizient) \n", "Straight-forward way kann eine Schleife die Lösung liefern: \n", "\n" ] }, { "cell_type": "raw", "id": "bc39468d-f250-4fc0-ba4f-c2d51d04c9cd", "metadata": {}, "source": [ "for col in df_features.columns:\n", " if df_features[col].dtype == 'object':\n", " df_features[col].fillna(\"\", inplace=True)\n", " else:\n", " df_features[col].fillna(0, inplace=True)" ] }, { "cell_type": "markdown", "id": "a07a6e13-870c-4118-95ed-645007ee4cbf", "metadata": {}, "source": [ "#### Aber effizienter (und \"Pythonic\"-way) würde man select_dtypes nutzen\n", "\n", "select_dtypes basiert auf Vektoroperationen, ist somit meist schneller und übersichtlicher als eine explizite Schleife über alle Spalten\n" ] }, { "cell_type": "code", "execution_count": 57, "id": "d216426e-4eb3-4cb2-b0e0-2ef04704c3d1", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.579943Z", "iopub.status.busy": "2026-03-24T17:55:10.579882Z", "iopub.status.idle": "2026-03-24T17:55:10.587318Z", "shell.execute_reply": "2026-03-24T17:55:10.586948Z", "shell.execute_reply.started": "2026-03-24T17:55:10.579936Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " customer_id num_request_last_1_months num_request_last_3_months \\\n", "0 0002-ORFBO 0.0 0.0 \n", "1 0003-MKNFE 0.0 3.0 \n", "2 0004-TLHLJ 0.0 3.0 \n", "3 0011-IGKFF 0.0 0.0 \n", "4 0013-EXCHZ 6.0 9.0 \n", "\n", " num_request_last_6_months num_request_last_12_months \\\n", "0 1.0 3.0 \n", "1 4.0 4.0 \n", "2 3.0 3.0 \n", "3 0.0 1.0 \n", "4 9.0 9.0 \n", "\n", " avg_num_days_till_solution avg_num_thread_till_solution last_channel \\\n", "0 0.0 1.00 Hotline \n", "1 0.0 1.00 Social Media \n", "2 0.0 1.00 Social Media \n", "3 0.0 0.00 Social Media \n", "4 1.0 1.25 Email \n", "\n", " channel_most_used_last6mo total_tickets total_interactions \\\n", "0 Hotline 1 3 \n", "1 Email 2 4 \n", "2 Chat 1 3 \n", "3 2 3 \n", "4 Chat 5 9 \n", "\n", " avg_reply_delay num_complaint_requests \n", "0 19.058148 1 \n", "1 22.865833 3 \n", "2 7.966481 1 \n", "3 11.924352 2 \n", "4 23.818210 1 " ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Für numerische Spalten\n", "cols_feature_numeric = df_features.select_dtypes(include=[np.number]).columns\n", "df_features[cols_feature_numeric] = df_features[cols_feature_numeric].fillna(0)\n", "\n", "# Für string-Spalten\n", "cols_feature_object = df_features.select_dtypes(include=[\"object\"]).columns\n", "df_features[cols_feature_object] = df_features[cols_feature_object].fillna(\"\")\n", "\n", "# Ausgabe des Feature-DataFrames\n", "df_features.head()" ] }, { "cell_type": "markdown", "id": "ff5569fe-2060-4866-80c3-e792fc601d39", "metadata": {}, "source": [ "## Merge die Features mit der originalen Kunden-Tabelle\n", "\n", "Beim Merge achten wir darauf, dass der Schlüssel in der Kunden-Tabelle \"customerID\" heißt und in features_df \"customer_id\"\n", "\n", "Zudem wollen wir hier einen left-merge, sodass die Originale Kunden-Tabelle auf jeden Fall bestehen bleibt und die Feature-Tabelle \"rangemergt\" wird.\n" ] }, { "cell_type": "code", "execution_count": 58, "id": "e9582c1e-8e88-4ba3-84ba-df86ff3823bd", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.587637Z", "iopub.status.busy": "2026-03-24T17:55:10.587578Z", "iopub.status.idle": "2026-03-24T17:55:10.605035Z", "shell.execute_reply": "2026-03-24T17:55:10.604681Z", "shell.execute_reply.started": "2026-03-24T17:55:10.587631Z" } }, "outputs": [ { "data": { "text/html": [ "
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7032 rows × 43 columns

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" ], "text/plain": [ " customerID gender SeniorCitizen Partner Dependents tenure \\\n", "0 7590-VHVEG 1 0 1 0 1 \n", "1 5575-GNVDE 0 0 0 0 34 \n", "2 3668-QPYBK 0 0 0 0 2 \n", "3 7795-CFOCW 0 0 0 0 45 \n", "4 9237-HQITU 1 0 0 0 2 \n", "... ... ... ... ... ... ... \n", "7027 6840-RESVB 0 0 1 1 24 \n", "7028 2234-XADUH 1 0 1 1 72 \n", "7029 4801-JZAZL 1 0 1 1 11 \n", "7030 8361-LTMKD 0 0 1 0 4 \n", "7031 3186-AJIEK 0 0 0 0 66 \n", "\n", " PhoneService OnlineSecurity OnlineBackup DeviceProtection \\\n", "0 0 0 1 0 \n", "1 1 1 0 1 \n", "2 1 1 1 0 \n", "3 0 1 0 1 \n", "4 1 0 0 0 \n", "... ... ... ... ... \n", "7027 1 1 0 1 \n", "7028 1 0 1 1 \n", "7029 0 1 0 0 \n", "7030 1 0 0 0 \n", "7031 1 1 0 1 \n", "\n", " TechSupport StreamingTV StreamingMovies PaperlessBilling \\\n", "0 0 0 0 1 \n", "1 0 0 0 0 \n", "2 0 0 0 1 \n", "3 1 0 0 0 \n", "4 0 0 0 1 \n", "... ... ... ... ... \n", "7027 1 1 1 1 \n", "7028 0 1 1 1 \n", "7029 0 0 0 1 \n", "7030 0 0 0 1 \n", "7031 1 1 1 1 \n", "\n", " MonthlyCharges TotalCharges Churn MultipleLines_No \\\n", "0 29.85 29.85 No 0 \n", "1 56.95 1889.50 No 0 \n", "2 53.85 108.15 Yes 0 \n", "3 42.30 1840.75 No 0 \n", "4 70.70 151.65 Yes 0 \n", "... ... ... ... ... \n", "7027 84.80 1990.50 No 0 \n", "7028 103.20 7362.90 No 0 \n", "7029 29.60 346.45 No 0 \n", "7030 74.40 306.60 Yes 0 \n", "7031 105.65 6844.50 No 0 \n", "\n", " MultipleLines_No phone service MultipleLines_Yes InternetService_DSL \\\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_Fiber optic InternetService_No \\\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", " Contract_Month-to-month Contract_One year Contract_Two 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", " PaymentMethod_Bank transfer (automatic) \\\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", " 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 customer_id num_request_last_1_months \\\n", "0 0 7590-VHVEG 2.0 \n", "1 0 5575-GNVDE 3.0 \n", "2 0 3668-QPYBK 3.0 \n", "3 0 7795-CFOCW 0.0 \n", "4 0 9237-HQITU 2.0 \n", "... ... ... ... \n", "7027 0 6840-RESVB 0.0 \n", "7028 0 NaN NaN \n", "7029 0 4801-JZAZL 0.0 \n", "7030 0 8361-LTMKD 0.0 \n", "7031 0 NaN NaN \n", "\n", " num_request_last_3_months num_request_last_6_months \\\n", "0 2.0 2.0 \n", "1 3.0 3.0 \n", "2 6.0 6.0 \n", "3 0.0 0.0 \n", "4 5.0 5.0 \n", "... ... ... \n", "7027 0.0 0.0 \n", "7028 NaN NaN \n", "7029 0.0 2.0 \n", "7030 2.0 2.0 \n", "7031 NaN NaN \n", "\n", " num_request_last_12_months avg_num_days_till_solution \\\n", "0 2.0 0.0 \n", "1 3.0 0.5 \n", "2 6.0 1.5 \n", "3 0.0 0.0 \n", "4 5.0 2.0 \n", "... ... ... \n", "7027 3.0 1.0 \n", "7028 NaN NaN \n", "7029 2.0 0.0 \n", "7030 2.0 0.0 \n", "7031 NaN NaN \n", "\n", " avg_num_thread_till_solution last_channel channel_most_used_last6mo \\\n", "0 1.0 Hotline Hotline \n", "1 1.0 Hotline Hotline \n", "2 1.5 Chat Hotline \n", "3 1.0 Email \n", "4 2.0 Hotline Email \n", "... ... ... ... \n", "7027 1.0 Email \n", "7028 NaN NaN NaN \n", "7029 1.0 Email Email \n", "7030 1.0 Hotline Hotline \n", "7031 NaN NaN NaN \n", "\n", " total_tickets total_interactions avg_reply_delay \\\n", "0 1.0 2.0 10.169722 \n", "1 3.0 8.0 21.380208 \n", "2 3.0 6.0 19.322130 \n", "3 1.0 2.0 11.750556 \n", "4 2.0 5.0 28.044167 \n", "... ... ... ... \n", "7027 1.0 3.0 23.803889 \n", "7028 NaN NaN NaN \n", "7029 1.0 2.0 18.954583 \n", "7030 1.0 2.0 10.321667 \n", "7031 NaN NaN NaN \n", "\n", " num_complaint_requests \n", "0 0.0 \n", "1 1.0 \n", "2 1.0 \n", "3 1.0 \n", "4 3.0 \n", "... ... \n", "7027 2.0 \n", "7028 NaN \n", "7029 2.0 \n", "7030 2.0 \n", "7031 NaN \n", "\n", "[7032 rows x 43 columns]" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_merge = df_onehot_encoded.merge(df_features, left_on=\"customerID\", right_on=\"customer_id\", how=\"left\")\n", "df_merge" ] }, { "cell_type": "code", "execution_count": 59, "id": "8b2540c6-1c84-4ceb-a298-5e1b3de8e235", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.605599Z", "iopub.status.busy": "2026-03-24T17:55:10.605526Z", "iopub.status.idle": "2026-03-24T17:55:10.616807Z", "shell.execute_reply": "2026-03-24T17:55:10.616181Z", "shell.execute_reply.started": "2026-03-24T17:55:10.605591Z" } }, "outputs": [ { "data": { "text/html": [ "
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customerIDgenderSeniorCitizenPartnerDependentstenurePhoneServiceOnlineSecurityOnlineBackupDeviceProtectionTechSupportStreamingTVStreamingMoviesPaperlessBillingMonthlyChargesTotalChargesChurnMultipleLines_NoMultipleLines_No phone serviceMultipleLines_YesInternetService_DSLInternetService_Fiber opticInternetService_NoContract_Month-to-monthContract_One yearContract_Two yearPaymentMethod_Bank transfer (automatic)PaymentMethod_Credit card (automatic)PaymentMethod_Electronic checkPaymentMethod_Mailed checknum_request_last_1_monthsnum_request_last_3_monthsnum_request_last_6_monthsnum_request_last_12_monthsavg_num_days_till_solutionavg_num_thread_till_solutionlast_channelchannel_most_used_last6mototal_ticketstotal_interactionsavg_reply_delaynum_complaint_requests
07590-VHVEG101010010000129.8529.85No00000000000002.02.02.02.00.01.0HotlineHotline1.02.010.1697220.0
15575-GNVDE0000341101000056.951889.50No00000000000003.03.03.03.00.51.0HotlineHotline3.08.021.3802081.0
23668-QPYBK000021110000153.85108.15Yes00000000000003.06.06.06.01.51.5ChatHotline3.06.019.3221301.0
37795-CFOCW0000450101100042.301840.75No00000000000000.00.00.00.00.01.0Email1.02.011.7505561.0
49237-HQITU100021000000170.70151.65Yes00000000000002.05.05.05.02.02.0HotlineEmail2.05.028.0441673.0
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" ], "text/plain": [ " customerID gender SeniorCitizen Partner Dependents tenure \\\n", "0 7590-VHVEG 1 0 1 0 1 \n", "1 5575-GNVDE 0 0 0 0 34 \n", "2 3668-QPYBK 0 0 0 0 2 \n", "3 7795-CFOCW 0 0 0 0 45 \n", "4 9237-HQITU 1 0 0 0 2 \n", "\n", " PhoneService OnlineSecurity OnlineBackup DeviceProtection TechSupport \\\n", "0 0 0 1 0 0 \n", "1 1 1 0 1 0 \n", "2 1 1 1 0 0 \n", "3 0 1 0 1 1 \n", "4 1 0 0 0 0 \n", "\n", " StreamingTV StreamingMovies PaperlessBilling MonthlyCharges \\\n", "0 0 0 1 29.85 \n", "1 0 0 0 56.95 \n", "2 0 0 1 53.85 \n", "3 0 0 0 42.30 \n", "4 0 0 1 70.70 \n", "\n", " TotalCharges Churn MultipleLines_No MultipleLines_No phone service \\\n", "0 29.85 No 0 0 \n", "1 1889.50 No 0 0 \n", "2 108.15 Yes 0 0 \n", "3 1840.75 No 0 0 \n", "4 151.65 Yes 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", " 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", " 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", " 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", " PaymentMethod_Mailed check num_request_last_1_months \\\n", "0 0 2.0 \n", "1 0 3.0 \n", "2 0 3.0 \n", "3 0 0.0 \n", "4 0 2.0 \n", "\n", " num_request_last_3_months num_request_last_6_months \\\n", "0 2.0 2.0 \n", "1 3.0 3.0 \n", "2 6.0 6.0 \n", "3 0.0 0.0 \n", "4 5.0 5.0 \n", "\n", " num_request_last_12_months avg_num_days_till_solution \\\n", "0 2.0 0.0 \n", "1 3.0 0.5 \n", "2 6.0 1.5 \n", "3 0.0 0.0 \n", "4 5.0 2.0 \n", "\n", " avg_num_thread_till_solution last_channel channel_most_used_last6mo \\\n", "0 1.0 Hotline Hotline \n", "1 1.0 Hotline Hotline \n", "2 1.5 Chat Hotline \n", "3 1.0 Email \n", "4 2.0 Hotline Email \n", "\n", " total_tickets total_interactions avg_reply_delay num_complaint_requests \n", "0 1.0 2.0 10.169722 0.0 \n", "1 3.0 8.0 21.380208 1.0 \n", "2 3.0 6.0 19.322130 1.0 \n", "3 1.0 2.0 11.750556 1.0 \n", "4 2.0 5.0 28.044167 3.0 " ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Entferne den doppelten Spaltennamen (customer_id) oder ordne die Spalten neu\n", "df_merge.drop(columns=\"customer_id\", inplace=True)\n", "\n", "# Ausgabe der erweiterten Kunden-Tabelle\n", "df_merge.head()" ] }, { "cell_type": "code", "execution_count": 60, "id": "82206be8-eb6c-4590-9aed-e02789b16dde", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.617186Z", "iopub.status.busy": "2026-03-24T17:55:10.617102Z", "iopub.status.idle": "2026-03-24T17:55:10.622902Z", "shell.execute_reply": "2026-03-24T17:55:10.622409Z", "shell.execute_reply.started": "2026-03-24T17:55:10.617177Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 7032 entries, 0 to 7031\n", "Data columns (total 42 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 customerID 7032 non-null str \n", " 1 gender 7032 non-null int64 \n", " 2 SeniorCitizen 7032 non-null int64 \n", " 3 Partner 7032 non-null int64 \n", " 4 Dependents 7032 non-null int64 \n", " 5 tenure 7032 non-null int64 \n", " 6 PhoneService 7032 non-null int64 \n", " 7 OnlineSecurity 7032 non-null int64 \n", " 8 OnlineBackup 7032 non-null int64 \n", " 9 DeviceProtection 7032 non-null int64 \n", " 10 TechSupport 7032 non-null int64 \n", " 11 StreamingTV 7032 non-null int64 \n", " 12 StreamingMovies 7032 non-null int64 \n", " 13 PaperlessBilling 7032 non-null int64 \n", " 14 MonthlyCharges 7032 non-null float64\n", " 15 TotalCharges 7032 non-null float64\n", " 16 Churn 7032 non-null str \n", " 17 MultipleLines_No 7032 non-null int64 \n", " 18 MultipleLines_No phone service 7032 non-null int64 \n", " 19 MultipleLines_Yes 7032 non-null int64 \n", " 20 InternetService_DSL 7032 non-null int64 \n", " 21 InternetService_Fiber optic 7032 non-null int64 \n", " 22 InternetService_No 7032 non-null int64 \n", " 23 Contract_Month-to-month 7032 non-null int64 \n", " 24 Contract_One year 7032 non-null int64 \n", " 25 Contract_Two year 7032 non-null int64 \n", " 26 PaymentMethod_Bank transfer (automatic) 7032 non-null int64 \n", " 27 PaymentMethod_Credit card (automatic) 7032 non-null int64 \n", " 28 PaymentMethod_Electronic check 7032 non-null int64 \n", " 29 PaymentMethod_Mailed check 7032 non-null int64 \n", " 30 num_request_last_1_months 6087 non-null float64\n", " 31 num_request_last_3_months 6087 non-null float64\n", " 32 num_request_last_6_months 6087 non-null float64\n", " 33 num_request_last_12_months 6087 non-null float64\n", " 34 avg_num_days_till_solution 6087 non-null float64\n", " 35 avg_num_thread_till_solution 6087 non-null float64\n", " 36 last_channel 6087 non-null str \n", " 37 channel_most_used_last6mo 6087 non-null str \n", " 38 total_tickets 6087 non-null float64\n", " 39 total_interactions 6087 non-null float64\n", " 40 avg_reply_delay 6087 non-null float64\n", " 41 num_complaint_requests 6087 non-null float64\n", "dtypes: float64(12), int64(26), str(4)\n", "memory usage: 2.4 MB\n" ] } ], "source": [ "df_merge.info()" ] }, { "cell_type": "code", "execution_count": 61, "id": "d4f4de3b-1db9-4de4-8acf-2dc5724a1f3e", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.623313Z", "iopub.status.busy": "2026-03-24T17:55:10.623242Z", "iopub.status.idle": "2026-03-24T17:55:10.627938Z", "shell.execute_reply": "2026-03-24T17:55:10.627405Z", "shell.execute_reply.started": "2026-03-24T17:55:10.623305Z" } }, "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", "OnlineSecurity 0\n", "OnlineBackup 0\n", "DeviceProtection 0\n", "TechSupport 0\n", "StreamingTV 0\n", "StreamingMovies 0\n", "PaperlessBilling 0\n", "MonthlyCharges 0\n", "TotalCharges 0\n", "Churn 0\n", "MultipleLines_No 0\n", "MultipleLines_No phone service 0\n", "MultipleLines_Yes 0\n", "InternetService_DSL 0\n", "InternetService_Fiber optic 0\n", "InternetService_No 0\n", "Contract_Month-to-month 0\n", "Contract_One year 0\n", "Contract_Two year 0\n", "PaymentMethod_Bank transfer (automatic) 0\n", "PaymentMethod_Credit card (automatic) 0\n", "PaymentMethod_Electronic check 0\n", "PaymentMethod_Mailed check 0\n", "num_request_last_1_months 945\n", "num_request_last_3_months 945\n", "num_request_last_6_months 945\n", "num_request_last_12_months 945\n", "avg_num_days_till_solution 945\n", "avg_num_thread_till_solution 945\n", "last_channel 945\n", "channel_most_used_last6mo 945\n", "total_tickets 945\n", "total_interactions 945\n", "avg_reply_delay 945\n", "num_complaint_requests 945\n", "dtype: int64" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_merge.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 62, "id": "0d81307e-56f0-4807-9c67-8925e73073ed", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.628325Z", "iopub.status.busy": "2026-03-24T17:55:10.628249Z", "iopub.status.idle": "2026-03-24T17:55:10.641098Z", "shell.execute_reply": "2026-03-24T17:55:10.640344Z", "shell.execute_reply.started": "2026-03-24T17:55:10.628318Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " customerID gender SeniorCitizen Partner Dependents tenure \\\n", "10 9763-GRSKD 0 0 1 1 13 \n", "30 3841-NFECX 1 0 1 0 71 \n", "31 4929-XIHVW 0 0 1 0 2 \n", "38 5380-WJKOV 0 0 0 0 34 \n", "42 9867-JCZSP 1 0 1 1 17 \n", "... ... ... ... ... ... ... \n", "7018 2235-DWLJU 1 0 0 0 6 \n", "7019 0871-OPBXW 1 0 0 0 2 \n", "7025 7750-EYXWZ 1 0 0 0 12 \n", "7028 2234-XADUH 1 0 1 1 72 \n", "7031 3186-AJIEK 0 0 0 0 66 \n", "\n", " PhoneService OnlineSecurity OnlineBackup DeviceProtection \\\n", "10 1 1 0 0 \n", "30 1 1 1 1 \n", "31 1 0 0 1 \n", "38 1 0 1 1 \n", "42 1 0 0 0 \n", "... ... ... ... ... \n", "7018 0 0 0 0 \n", "7019 1 0 0 0 \n", "7025 0 0 1 1 \n", "7028 1 0 1 1 \n", "7031 1 1 0 1 \n", "\n", " TechSupport StreamingTV StreamingMovies PaperlessBilling \\\n", "10 0 0 0 1 \n", "30 1 0 0 1 \n", "31 0 1 1 1 \n", "38 0 1 1 1 \n", "42 0 0 0 0 \n", "... ... ... ... ... \n", "7018 0 1 1 1 \n", "7019 0 0 0 1 \n", "7025 1 1 1 0 \n", "7028 0 1 1 1 \n", "7031 1 1 1 1 \n", "\n", " MonthlyCharges TotalCharges Churn MultipleLines_No \\\n", "10 49.95 587.45 No 0 \n", "30 96.35 6766.95 No 0 \n", "31 95.50 181.65 No 0 \n", "38 106.35 3549.25 Yes 0 \n", "42 20.75 418.25 No 0 \n", "... ... ... ... ... \n", "7018 44.40 263.05 No 0 \n", "7019 20.05 39.25 No 0 \n", "7025 60.65 743.30 No 0 \n", "7028 103.20 7362.90 No 0 \n", "7031 105.65 6844.50 No 0 \n", "\n", " MultipleLines_No phone service MultipleLines_Yes InternetService_DSL \\\n", "10 0 0 0 \n", "30 0 0 0 \n", "31 0 0 0 \n", "38 0 0 0 \n", "42 0 0 0 \n", "... ... ... ... \n", "7018 0 0 0 \n", "7019 0 0 0 \n", "7025 0 0 0 \n", "7028 0 0 0 \n", "7031 0 0 0 \n", "\n", " InternetService_Fiber optic InternetService_No \\\n", "10 0 0 \n", "30 0 0 \n", "31 0 0 \n", "38 0 0 \n", "42 0 0 \n", "... ... ... \n", "7018 0 0 \n", "7019 0 0 \n", "7025 0 0 \n", "7028 0 0 \n", "7031 0 0 \n", "\n", " Contract_Month-to-month Contract_One year Contract_Two year \\\n", "10 0 0 0 \n", "30 0 0 0 \n", "31 0 0 0 \n", "38 0 0 0 \n", "42 0 0 0 \n", "... ... ... ... \n", "7018 0 0 0 \n", "7019 0 0 0 \n", "7025 0 0 0 \n", "7028 0 0 0 \n", "7031 0 0 0 \n", "\n", " PaymentMethod_Bank transfer (automatic) \\\n", "10 0 \n", "30 0 \n", "31 0 \n", "38 0 \n", "42 0 \n", "... ... \n", "7018 0 \n", "7019 0 \n", "7025 0 \n", "7028 0 \n", "7031 0 \n", "\n", " PaymentMethod_Credit card (automatic) PaymentMethod_Electronic check \\\n", "10 0 0 \n", "30 0 0 \n", "31 0 0 \n", "38 0 0 \n", "42 0 0 \n", "... ... ... \n", "7018 0 0 \n", "7019 0 0 \n", "7025 0 0 \n", "7028 0 0 \n", "7031 0 0 \n", "\n", " PaymentMethod_Mailed check num_request_last_1_months \\\n", "10 0 NaN \n", "30 0 NaN \n", "31 0 NaN \n", "38 0 NaN \n", "42 0 NaN \n", "... ... ... \n", "7018 0 NaN \n", "7019 0 NaN \n", "7025 0 NaN \n", "7028 0 NaN \n", "7031 0 NaN \n", "\n", " num_request_last_3_months num_request_last_6_months \\\n", "10 NaN NaN \n", "30 NaN NaN \n", "31 NaN NaN \n", "38 NaN NaN \n", "42 NaN NaN \n", "... ... ... \n", "7018 NaN NaN \n", "7019 NaN NaN \n", "7025 NaN NaN \n", "7028 NaN NaN \n", "7031 NaN NaN \n", "\n", " num_request_last_12_months avg_num_days_till_solution \\\n", "10 NaN NaN \n", "30 NaN NaN \n", "31 NaN NaN \n", "38 NaN NaN \n", "42 NaN NaN \n", "... ... ... \n", "7018 NaN NaN \n", "7019 NaN NaN \n", "7025 NaN NaN \n", "7028 NaN NaN \n", "7031 NaN NaN \n", "\n", " avg_num_thread_till_solution last_channel channel_most_used_last6mo \\\n", "10 NaN NaN NaN \n", "30 NaN NaN NaN \n", "31 NaN NaN NaN \n", "38 NaN NaN NaN \n", "42 NaN NaN NaN \n", "... ... ... ... \n", "7018 NaN NaN NaN \n", "7019 NaN NaN NaN \n", "7025 NaN NaN NaN \n", "7028 NaN NaN NaN \n", "7031 NaN NaN NaN \n", "\n", " total_tickets total_interactions avg_reply_delay \\\n", "10 NaN NaN NaN \n", "30 NaN NaN NaN \n", "31 NaN NaN NaN \n", "38 NaN NaN NaN \n", "42 NaN NaN NaN \n", "... ... ... ... \n", "7018 NaN NaN NaN \n", "7019 NaN NaN NaN \n", "7025 NaN NaN NaN \n", "7028 NaN NaN NaN \n", "7031 NaN NaN NaN \n", "\n", " num_complaint_requests \n", "10 NaN \n", "30 NaN \n", "31 NaN \n", "38 NaN \n", "42 NaN \n", "... ... \n", "7018 NaN \n", "7019 NaN \n", "7025 NaN \n", "7028 NaN \n", "7031 NaN \n", "\n", "[945 rows x 42 columns]" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_merge[df_merge[\"num_request_last_6_months\"].isnull()]" ] }, { "cell_type": "code", "execution_count": 63, "id": "959346f7-1f8c-450f-80cf-b3527fe033a9", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.641973Z", "iopub.status.busy": "2026-03-24T17:55:10.641843Z", "iopub.status.idle": "2026-03-24T17:55:10.646322Z", "shell.execute_reply": "2026-03-24T17:55:10.645982Z", "shell.execute_reply.started": "2026-03-24T17:55:10.641965Z" } }, "outputs": [ { "data": { "text/html": [ "
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ticket_idcustomer_idtime_requesttime_replychannelrequestreplysolvedoriginal_requestoriginal_ticket_idreply_delay_hoursis_complaint
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" ], "text/plain": [ "Empty DataFrame\n", "Columns: [ticket_id, customer_id, time_request, time_reply, channel, request, reply, solved, original_request, original_ticket_id, reply_delay_hours, is_complaint]\n", "Index: []" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_service[df_service[\"customer_id\"]==\"9763-GRSKD\"]" ] }, { "cell_type": "markdown", "id": "65342c18-d159-44ec-9e8d-e13962306936", "metadata": {}, "source": [ "### Den finalen DataFrame auffüllen" ] }, { "cell_type": "code", "execution_count": 64, "id": "db7db6c0-812b-40c6-8a75-3e3e4cdfb129", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.646787Z", "iopub.status.busy": "2026-03-24T17:55:10.646723Z", "iopub.status.idle": "2026-03-24T17:55:10.652137Z", "shell.execute_reply": "2026-03-24T17:55:10.651677Z", "shell.execute_reply.started": "2026-03-24T17:55:10.646781Z" } }, "outputs": [], "source": [ "# Für numerische Spalten\n", "numeric_cols = df_merge.select_dtypes(include=[np.number]).columns\n", "df_merge[numeric_cols] = df_merge[numeric_cols].fillna(0)\n", "\n", "# Für string-Spalten\n", "object_cols = df_merge.select_dtypes(include=[\"object\"]).columns\n", "df_merge[object_cols] = df_merge[object_cols].fillna(\"\")" ] }, { "cell_type": "code", "execution_count": 65, "id": "744fb7ad-c50f-4e29-8d1a-a82cf6e8a0a5", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.652535Z", "iopub.status.busy": "2026-03-24T17:55:10.652474Z", "iopub.status.idle": "2026-03-24T17:55:10.656760Z", "shell.execute_reply": "2026-03-24T17:55:10.655655Z", "shell.execute_reply.started": "2026-03-24T17:55:10.652528Z" } }, "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", "OnlineSecurity 0\n", "OnlineBackup 0\n", "DeviceProtection 0\n", "TechSupport 0\n", "StreamingTV 0\n", "StreamingMovies 0\n", "PaperlessBilling 0\n", "MonthlyCharges 0\n", "TotalCharges 0\n", "Churn 0\n", "MultipleLines_No 0\n", "MultipleLines_No phone service 0\n", "MultipleLines_Yes 0\n", "InternetService_DSL 0\n", "InternetService_Fiber optic 0\n", "InternetService_No 0\n", "Contract_Month-to-month 0\n", "Contract_One year 0\n", "Contract_Two year 0\n", "PaymentMethod_Bank transfer (automatic) 0\n", "PaymentMethod_Credit card (automatic) 0\n", "PaymentMethod_Electronic check 0\n", "PaymentMethod_Mailed check 0\n", "num_request_last_1_months 0\n", "num_request_last_3_months 0\n", "num_request_last_6_months 0\n", "num_request_last_12_months 0\n", "avg_num_days_till_solution 0\n", "avg_num_thread_till_solution 0\n", "last_channel 0\n", "channel_most_used_last6mo 0\n", "total_tickets 0\n", "total_interactions 0\n", "avg_reply_delay 0\n", "num_complaint_requests 0\n", "dtype: int64" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_merge.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 66, "id": "c7e45a7a-82dc-45f6-a379-14584d946bb3", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.657143Z", "iopub.status.busy": "2026-03-24T17:55:10.657077Z", "iopub.status.idle": "2026-03-24T17:55:10.667563Z", "shell.execute_reply": "2026-03-24T17:55:10.667070Z", "shell.execute_reply.started": "2026-03-24T17:55:10.657136Z" } }, "outputs": [ { "data": { "text/html": [ "
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49237-HQITU100021000000170.70151.65Yes00000000000002.05.05.05.02.02.0HotlineEmail2.05.028.0441673.0
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" ], "text/plain": [ " customerID gender SeniorCitizen Partner Dependents tenure \\\n", "0 7590-VHVEG 1 0 1 0 1 \n", "1 5575-GNVDE 0 0 0 0 34 \n", "2 3668-QPYBK 0 0 0 0 2 \n", "3 7795-CFOCW 0 0 0 0 45 \n", "4 9237-HQITU 1 0 0 0 2 \n", "\n", " PhoneService OnlineSecurity OnlineBackup DeviceProtection TechSupport \\\n", "0 0 0 1 0 0 \n", "1 1 1 0 1 0 \n", "2 1 1 1 0 0 \n", "3 0 1 0 1 1 \n", "4 1 0 0 0 0 \n", "\n", " StreamingTV StreamingMovies PaperlessBilling MonthlyCharges \\\n", "0 0 0 1 29.85 \n", "1 0 0 0 56.95 \n", "2 0 0 1 53.85 \n", "3 0 0 0 42.30 \n", "4 0 0 1 70.70 \n", "\n", " TotalCharges Churn MultipleLines_No MultipleLines_No phone service \\\n", "0 29.85 No 0 0 \n", "1 1889.50 No 0 0 \n", "2 108.15 Yes 0 0 \n", "3 1840.75 No 0 0 \n", "4 151.65 Yes 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", " 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", " 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", " 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", " PaymentMethod_Mailed check num_request_last_1_months \\\n", "0 0 2.0 \n", "1 0 3.0 \n", "2 0 3.0 \n", "3 0 0.0 \n", "4 0 2.0 \n", "\n", " num_request_last_3_months num_request_last_6_months \\\n", "0 2.0 2.0 \n", "1 3.0 3.0 \n", "2 6.0 6.0 \n", "3 0.0 0.0 \n", "4 5.0 5.0 \n", "\n", " num_request_last_12_months avg_num_days_till_solution \\\n", "0 2.0 0.0 \n", "1 3.0 0.5 \n", "2 6.0 1.5 \n", "3 0.0 0.0 \n", "4 5.0 2.0 \n", "\n", " avg_num_thread_till_solution last_channel channel_most_used_last6mo \\\n", "0 1.0 Hotline Hotline \n", "1 1.0 Hotline Hotline \n", "2 1.5 Chat Hotline \n", "3 1.0 Email \n", "4 2.0 Hotline Email \n", "\n", " total_tickets total_interactions avg_reply_delay num_complaint_requests \n", "0 1.0 2.0 10.169722 0.0 \n", "1 3.0 8.0 21.380208 1.0 \n", "2 3.0 6.0 19.322130 1.0 \n", "3 1.0 2.0 11.750556 1.0 \n", "4 2.0 5.0 28.044167 3.0 " ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_merge.head()" ] }, { "cell_type": "code", "execution_count": 67, "id": "fe913ccd-f0e2-4188-805c-8763914fd4bd", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.668056Z", "iopub.status.busy": "2026-03-24T17:55:10.667972Z", "iopub.status.idle": "2026-03-24T17:55:10.670889Z", "shell.execute_reply": "2026-03-24T17:55:10.670484Z", "shell.execute_reply.started": "2026-03-24T17:55:10.668049Z" } }, "outputs": [ { "data": { "text/plain": [ "customerID str\n", "gender int64\n", "SeniorCitizen int64\n", "Partner int64\n", "Dependents int64\n", "tenure int64\n", "PhoneService int64\n", "OnlineSecurity int64\n", "OnlineBackup int64\n", "DeviceProtection int64\n", "TechSupport int64\n", "StreamingTV int64\n", "StreamingMovies int64\n", "PaperlessBilling int64\n", "MonthlyCharges float64\n", "TotalCharges float64\n", "Churn str\n", "MultipleLines_No int64\n", "MultipleLines_No phone service int64\n", "MultipleLines_Yes int64\n", "InternetService_DSL int64\n", "InternetService_Fiber optic int64\n", "InternetService_No int64\n", "Contract_Month-to-month int64\n", "Contract_One year int64\n", "Contract_Two year int64\n", "PaymentMethod_Bank transfer (automatic) int64\n", "PaymentMethod_Credit card (automatic) int64\n", "PaymentMethod_Electronic check int64\n", "PaymentMethod_Mailed check int64\n", "num_request_last_1_months float64\n", "num_request_last_3_months float64\n", "num_request_last_6_months float64\n", "num_request_last_12_months float64\n", "avg_num_days_till_solution float64\n", "avg_num_thread_till_solution float64\n", "last_channel str\n", "channel_most_used_last6mo str\n", "total_tickets float64\n", "total_interactions float64\n", "avg_reply_delay float64\n", "num_complaint_requests float64\n", "dtype: object" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_merge.dtypes" ] }, { "cell_type": "markdown", "id": "04199cdd-a47b-4e58-9e93-32048ef4bac7", "metadata": {}, "source": [ "### Transform categorical columns" ] }, { "cell_type": "code", "execution_count": 68, "id": "6f90b413-4aa7-43a7-85ba-0bff36d764f8", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.671221Z", "iopub.status.busy": "2026-03-24T17:55:10.671166Z", "iopub.status.idle": "2026-03-24T17:55:10.686913Z", "shell.execute_reply": "2026-03-24T17:55:10.686429Z", "shell.execute_reply.started": "2026-03-24T17:55:10.671215Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(7032, 52)\n" ] }, { "data": { "text/html": [ "
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23668-QPYBK000021110000153.85108.15Yes00000000000003.06.06.06.01.51.53.06.019.3221301.0010000000100
37795-CFOCW0000450101100042.301840.75No00000000000000.00.00.00.00.01.01.02.011.7505561.0001000100000
49237-HQITU100021000000170.70151.65Yes00000000000002.05.05.05.02.02.02.05.028.0441673.0000100001000
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70276840-RESVB0011241101111184.801990.50No00000000000000.00.00.03.01.01.01.03.023.8038892.0001000100000
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70308361-LTMKD001041000000174.40306.60Yes00000000000000.02.02.02.00.01.01.02.010.3216672.0000100000100
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7032 rows × 52 columns

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" ], "text/plain": [ " customerID gender SeniorCitizen Partner Dependents tenure \\\n", "0 7590-VHVEG 1 0 1 0 1 \n", "1 5575-GNVDE 0 0 0 0 34 \n", "2 3668-QPYBK 0 0 0 0 2 \n", "3 7795-CFOCW 0 0 0 0 45 \n", "4 9237-HQITU 1 0 0 0 2 \n", "... ... ... ... ... ... ... \n", "7027 6840-RESVB 0 0 1 1 24 \n", "7028 2234-XADUH 1 0 1 1 72 \n", "7029 4801-JZAZL 1 0 1 1 11 \n", "7030 8361-LTMKD 0 0 1 0 4 \n", "7031 3186-AJIEK 0 0 0 0 66 \n", "\n", " PhoneService OnlineSecurity OnlineBackup DeviceProtection \\\n", "0 0 0 1 0 \n", "1 1 1 0 1 \n", "2 1 1 1 0 \n", "3 0 1 0 1 \n", "4 1 0 0 0 \n", "... ... ... ... ... \n", "7027 1 1 0 1 \n", "7028 1 0 1 1 \n", "7029 0 1 0 0 \n", "7030 1 0 0 0 \n", "7031 1 1 0 1 \n", "\n", " TechSupport StreamingTV StreamingMovies PaperlessBilling \\\n", "0 0 0 0 1 \n", "1 0 0 0 0 \n", "2 0 0 0 1 \n", "3 1 0 0 0 \n", "4 0 0 0 1 \n", "... ... ... ... ... \n", "7027 1 1 1 1 \n", "7028 0 1 1 1 \n", "7029 0 0 0 1 \n", "7030 0 0 0 1 \n", "7031 1 1 1 1 \n", "\n", " MonthlyCharges TotalCharges Churn MultipleLines_No \\\n", "0 29.85 29.85 No 0 \n", "1 56.95 1889.50 No 0 \n", "2 53.85 108.15 Yes 0 \n", "3 42.30 1840.75 No 0 \n", "4 70.70 151.65 Yes 0 \n", "... ... ... ... ... \n", "7027 84.80 1990.50 No 0 \n", "7028 103.20 7362.90 No 0 \n", "7029 29.60 346.45 No 0 \n", "7030 74.40 306.60 Yes 0 \n", "7031 105.65 6844.50 No 0 \n", "\n", " MultipleLines_No phone service MultipleLines_Yes InternetService_DSL \\\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_Fiber optic InternetService_No \\\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", " Contract_Month-to-month Contract_One year Contract_Two 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", " PaymentMethod_Bank transfer (automatic) \\\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", " 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 num_request_last_1_months \\\n", "0 0 2.0 \n", "1 0 3.0 \n", "2 0 3.0 \n", "3 0 0.0 \n", "4 0 2.0 \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", " num_request_last_3_months num_request_last_6_months \\\n", "0 2.0 2.0 \n", "1 3.0 3.0 \n", "2 6.0 6.0 \n", "3 0.0 0.0 \n", "4 5.0 5.0 \n", "... ... ... \n", "7027 0.0 0.0 \n", "7028 0.0 0.0 \n", "7029 0.0 2.0 \n", "7030 2.0 2.0 \n", "7031 0.0 0.0 \n", "\n", " num_request_last_12_months avg_num_days_till_solution \\\n", "0 2.0 0.0 \n", "1 3.0 0.5 \n", "2 6.0 1.5 \n", "3 0.0 0.0 \n", "4 5.0 2.0 \n", "... ... ... \n", "7027 3.0 1.0 \n", "7028 0.0 0.0 \n", "7029 2.0 0.0 \n", "7030 2.0 0.0 \n", "7031 0.0 0.0 \n", "\n", " avg_num_thread_till_solution total_tickets total_interactions \\\n", "0 1.0 1.0 2.0 \n", "1 1.0 3.0 8.0 \n", "2 1.5 3.0 6.0 \n", "3 1.0 1.0 2.0 \n", "4 2.0 2.0 5.0 \n", "... ... ... ... \n", "7027 1.0 1.0 3.0 \n", "7028 0.0 0.0 0.0 \n", "7029 1.0 1.0 2.0 \n", "7030 1.0 1.0 2.0 \n", "7031 0.0 0.0 0.0 \n", "\n", " avg_reply_delay num_complaint_requests last_channel_ \\\n", "0 10.169722 0.0 0 \n", "1 21.380208 1.0 0 \n", "2 19.322130 1.0 0 \n", "3 11.750556 1.0 0 \n", "4 28.044167 3.0 0 \n", "... ... ... ... \n", "7027 23.803889 2.0 0 \n", "7028 0.000000 0.0 1 \n", "7029 18.954583 2.0 0 \n", "7030 10.321667 2.0 0 \n", "7031 0.000000 0.0 1 \n", "\n", " last_channel_Chat last_channel_Email last_channel_Hotline \\\n", "0 0 0 1 \n", "1 0 0 1 \n", "2 1 0 0 \n", "3 0 1 0 \n", "4 0 0 1 \n", "... ... ... ... \n", "7027 0 1 0 \n", "7028 0 0 0 \n", "7029 0 1 0 \n", "7030 0 0 1 \n", "7031 0 0 0 \n", "\n", " last_channel_On-site last_channel_Social Media \\\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", " channel_most_used_last6mo_ channel_most_used_last6mo_Chat \\\n", "0 0 0 \n", "1 0 0 \n", "2 0 0 \n", "3 1 0 \n", "4 0 0 \n", "... ... ... \n", "7027 1 0 \n", "7028 1 0 \n", "7029 0 0 \n", "7030 0 0 \n", "7031 1 0 \n", "\n", " channel_most_used_last6mo_Email channel_most_used_last6mo_Hotline \\\n", "0 0 1 \n", "1 0 1 \n", "2 0 1 \n", "3 0 0 \n", "4 1 0 \n", "... ... ... \n", "7027 0 0 \n", "7028 0 0 \n", "7029 1 0 \n", "7030 0 1 \n", "7031 0 0 \n", "\n", " channel_most_used_last6mo_On-site \\\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", " channel_most_used_last6mo_Social Media \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 52 columns]" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cols_merge_object = [\"last_channel\", \"channel_most_used_last6mo\"]\n", "df_final = pd.get_dummies(df_merge, columns=cols_merge_object, dtype=int) \n", "\n", "print(df_final.shape)\n", "df_final" ] }, { "cell_type": "markdown", "id": "1b5bcc4c-6ad5-49ac-8028-5788e5e6da1c", "metadata": {}, "source": [ "### Don't forget the Target Variable!" ] }, { "cell_type": "code", "execution_count": 69, "id": "092428c3-dd9f-45ce-8764-157f34b6310f", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.687365Z", "iopub.status.busy": "2026-03-24T17:55:10.687283Z", "iopub.status.idle": "2026-03-24T17:55:10.698739Z", "shell.execute_reply": "2026-03-24T17:55:10.698330Z", "shell.execute_reply.started": "2026-03-24T17:55:10.687357Z" } }, "outputs": [ { "data": { "text/html": [ "
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customerIDgenderSeniorCitizenPartnerDependentstenurePhoneServiceOnlineSecurityOnlineBackupDeviceProtectionTechSupportStreamingTVStreamingMoviesPaperlessBillingMonthlyChargesTotalChargesChurnMultipleLines_NoMultipleLines_No phone serviceMultipleLines_YesInternetService_DSLInternetService_Fiber opticInternetService_NoContract_Month-to-monthContract_One yearContract_Two yearPaymentMethod_Bank transfer (automatic)PaymentMethod_Credit card (automatic)PaymentMethod_Electronic checkPaymentMethod_Mailed checknum_request_last_1_monthsnum_request_last_3_monthsnum_request_last_6_monthsnum_request_last_12_monthsavg_num_days_till_solutionavg_num_thread_till_solutiontotal_ticketstotal_interactionsavg_reply_delaynum_complaint_requestslast_channel_last_channel_Chatlast_channel_Emaillast_channel_Hotlinelast_channel_On-sitelast_channel_Social Mediachannel_most_used_last6mo_channel_most_used_last6mo_Chatchannel_most_used_last6mo_Emailchannel_most_used_last6mo_Hotlinechannel_most_used_last6mo_On-sitechannel_most_used_last6mo_Social Media
07590-VHVEG101010010000129.8529.85000000000000002.02.02.02.00.01.01.02.010.1697220.0000100000100
15575-GNVDE0000341101000056.951889.50000000000000003.03.03.03.00.51.03.08.021.3802081.0000100000100
23668-QPYBK000021110000153.85108.15100000000000003.06.06.06.01.51.53.06.019.3221301.0010000000100
37795-CFOCW0000450101100042.301840.75000000000000000.00.00.00.00.01.01.02.011.7505561.0001000100000
49237-HQITU100021000000170.70151.65100000000000002.05.05.05.02.02.02.05.028.0441673.0000100001000
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" ], "text/plain": [ " customerID gender SeniorCitizen Partner Dependents tenure \\\n", "0 7590-VHVEG 1 0 1 0 1 \n", "1 5575-GNVDE 0 0 0 0 34 \n", "2 3668-QPYBK 0 0 0 0 2 \n", "3 7795-CFOCW 0 0 0 0 45 \n", "4 9237-HQITU 1 0 0 0 2 \n", "\n", " PhoneService OnlineSecurity OnlineBackup DeviceProtection TechSupport \\\n", "0 0 0 1 0 0 \n", "1 1 1 0 1 0 \n", "2 1 1 1 0 0 \n", "3 0 1 0 1 1 \n", "4 1 0 0 0 0 \n", "\n", " StreamingTV StreamingMovies PaperlessBilling MonthlyCharges \\\n", "0 0 0 1 29.85 \n", "1 0 0 0 56.95 \n", "2 0 0 1 53.85 \n", "3 0 0 0 42.30 \n", "4 0 0 1 70.70 \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", " 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", " 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", " 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", " 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", " PaymentMethod_Mailed check num_request_last_1_months \\\n", "0 0 2.0 \n", "1 0 3.0 \n", "2 0 3.0 \n", "3 0 0.0 \n", "4 0 2.0 \n", "\n", " num_request_last_3_months num_request_last_6_months \\\n", "0 2.0 2.0 \n", "1 3.0 3.0 \n", "2 6.0 6.0 \n", "3 0.0 0.0 \n", "4 5.0 5.0 \n", "\n", " num_request_last_12_months avg_num_days_till_solution \\\n", "0 2.0 0.0 \n", "1 3.0 0.5 \n", "2 6.0 1.5 \n", "3 0.0 0.0 \n", "4 5.0 2.0 \n", "\n", " avg_num_thread_till_solution total_tickets total_interactions \\\n", "0 1.0 1.0 2.0 \n", "1 1.0 3.0 8.0 \n", "2 1.5 3.0 6.0 \n", "3 1.0 1.0 2.0 \n", "4 2.0 2.0 5.0 \n", "\n", " avg_reply_delay num_complaint_requests last_channel_ last_channel_Chat \\\n", "0 10.169722 0.0 0 0 \n", "1 21.380208 1.0 0 0 \n", "2 19.322130 1.0 0 1 \n", "3 11.750556 1.0 0 0 \n", "4 28.044167 3.0 0 0 \n", "\n", " last_channel_Email last_channel_Hotline last_channel_On-site \\\n", "0 0 1 0 \n", "1 0 1 0 \n", "2 0 0 0 \n", "3 1 0 0 \n", "4 0 1 0 \n", "\n", " last_channel_Social Media channel_most_used_last6mo_ \\\n", "0 0 0 \n", "1 0 0 \n", "2 0 0 \n", "3 0 1 \n", "4 0 0 \n", "\n", " channel_most_used_last6mo_Chat channel_most_used_last6mo_Email \\\n", "0 0 0 \n", "1 0 0 \n", "2 0 0 \n", "3 0 0 \n", "4 0 1 \n", "\n", " channel_most_used_last6mo_Hotline channel_most_used_last6mo_On-site \\\n", "0 1 0 \n", "1 1 0 \n", "2 1 0 \n", "3 0 0 \n", "4 0 0 \n", "\n", " channel_most_used_last6mo_Social Media \n", "0 0 \n", "1 0 \n", "2 0 \n", "3 0 \n", "4 0 " ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_final['Churn'] = df_final['Churn'].map({\"Yes\": 1, \"No\": 0})\n", "df_final.head()" ] }, { "cell_type": "code", "execution_count": 70, "id": "ae97ccb4-9864-45be-90b9-1ef235abf17f", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.699137Z", "iopub.status.busy": "2026-03-24T17:55:10.699060Z", "iopub.status.idle": "2026-03-24T17:55:10.713354Z", "shell.execute_reply": "2026-03-24T17:55:10.712715Z", "shell.execute_reply.started": "2026-03-24T17:55:10.699130Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " gender SeniorCitizen Partner Dependents tenure PhoneService \\\n", "0 1 0 1 0 1 0 \n", "1 0 0 0 0 34 1 \n", "2 0 0 0 0 2 1 \n", "3 0 0 0 0 45 0 \n", "4 1 0 0 0 2 1 \n", "... ... ... ... ... ... ... \n", "7027 0 0 1 1 24 1 \n", "7028 1 0 1 1 72 1 \n", "7029 1 0 1 1 11 0 \n", "7030 0 0 1 0 4 1 \n", "7031 0 0 0 0 66 1 \n", "\n", " OnlineSecurity OnlineBackup DeviceProtection TechSupport \\\n", "0 0 1 0 0 \n", "1 1 0 1 0 \n", "2 1 1 0 0 \n", "3 1 0 1 1 \n", "4 0 0 0 0 \n", "... ... ... ... ... \n", "7027 1 0 1 1 \n", "7028 0 1 1 0 \n", "7029 1 0 0 0 \n", "7030 0 0 0 0 \n", "7031 1 0 1 1 \n", "\n", " StreamingTV StreamingMovies PaperlessBilling MonthlyCharges \\\n", "0 0 0 1 29.85 \n", "1 0 0 0 56.95 \n", "2 0 0 1 53.85 \n", "3 0 0 0 42.30 \n", "4 0 0 1 70.70 \n", "... ... ... ... ... \n", "7027 1 1 1 84.80 \n", "7028 1 1 1 103.20 \n", "7029 0 0 1 29.60 \n", "7030 0 0 1 74.40 \n", "7031 1 1 1 105.65 \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", 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"7031 0.0 0.0 \n", "\n", " avg_num_thread_till_solution total_tickets total_interactions \\\n", "0 1.0 1.0 2.0 \n", "1 1.0 3.0 8.0 \n", "2 1.5 3.0 6.0 \n", "3 1.0 1.0 2.0 \n", "4 2.0 2.0 5.0 \n", "... ... ... ... \n", "7027 1.0 1.0 3.0 \n", "7028 0.0 0.0 0.0 \n", "7029 1.0 1.0 2.0 \n", "7030 1.0 1.0 2.0 \n", "7031 0.0 0.0 0.0 \n", "\n", " avg_reply_delay num_complaint_requests last_channel_ \\\n", "0 10.169722 0.0 0 \n", "1 21.380208 1.0 0 \n", "2 19.322130 1.0 0 \n", "3 11.750556 1.0 0 \n", "4 28.044167 3.0 0 \n", "... ... ... ... \n", "7027 23.803889 2.0 0 \n", "7028 0.000000 0.0 1 \n", "7029 18.954583 2.0 0 \n", "7030 10.321667 2.0 0 \n", "7031 0.000000 0.0 1 \n", "\n", " last_channel_Chat last_channel_Email last_channel_Hotline \\\n", "0 0 0 1 \n", "1 0 0 1 \n", "2 1 0 0 \n", "3 0 1 0 \n", "4 0 0 1 \n", "... ... ... ... \n", "7027 0 1 0 \n", "7028 0 0 0 \n", "7029 0 1 0 \n", "7030 0 0 1 \n", "7031 0 0 0 \n", "\n", " last_channel_On-site last_channel_Social Media \\\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", " channel_most_used_last6mo_ channel_most_used_last6mo_Chat \\\n", "0 0 0 \n", "1 0 0 \n", "2 0 0 \n", "3 1 0 \n", "4 0 0 \n", "... ... ... \n", "7027 1 0 \n", "7028 1 0 \n", "7029 0 0 \n", "7030 0 0 \n", "7031 1 0 \n", "\n", " channel_most_used_last6mo_Email channel_most_used_last6mo_Hotline \\\n", "0 0 1 \n", "1 0 1 \n", "2 0 1 \n", "3 0 0 \n", "4 1 0 \n", "... ... ... \n", "7027 0 0 \n", "7028 0 0 \n", "7029 1 0 \n", "7030 0 1 \n", "7031 0 0 \n", "\n", " channel_most_used_last6mo_On-site \\\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", " channel_most_used_last6mo_Social Media \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 51 columns]" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ "## Verwerfe ID-columns\n", "if \"customerID\" in df_final:\n", " df_final.drop(\"customerID\", axis=1, inplace=True)\n", "\n", "df_final" ] }, { "cell_type": "markdown", "id": "01aa7cb2-c71b-497c-af6c-95789e20b677", "metadata": {}, "source": [ "### Kunden-IDs:\n", "\n", "Jetzt, wo die Tabellen gemergt sind, können wir als letzten Schritt vor dem Split des Datensatzes die einzig uebrig gebliebene Kunden-ID Spalte entfernen" ] }, { "cell_type": "code", "execution_count": 71, "id": "e1170d05-3ae1-4dd6-8bfb-09a598f9bfcf", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.714691Z", "iopub.status.busy": "2026-03-24T17:55:10.714585Z", "iopub.status.idle": "2026-03-24T17:55:10.727974Z", "shell.execute_reply": "2026-03-24T17:55:10.727498Z", "shell.execute_reply.started": "2026-03-24T17:55:10.714683Z" }, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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7032 rows × 51 columns

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" ], "text/plain": [ " gender SeniorCitizen Partner Dependents tenure PhoneService \\\n", "0 1 0 1 0 1 0 \n", "1 0 0 0 0 34 1 \n", "2 0 0 0 0 2 1 \n", "3 0 0 0 0 45 0 \n", "4 1 0 0 0 2 1 \n", "... ... ... ... ... ... ... \n", "7027 0 0 1 1 24 1 \n", "7028 1 0 1 1 72 1 \n", "7029 1 0 1 1 11 0 \n", "7030 0 0 1 0 4 1 \n", "7031 0 0 0 0 66 1 \n", "\n", " OnlineSecurity OnlineBackup DeviceProtection TechSupport \\\n", "0 0 1 0 0 \n", "1 1 0 1 0 \n", "2 1 1 0 0 \n", "3 1 0 1 1 \n", "4 0 0 0 0 \n", "... ... ... ... ... \n", "7027 1 0 1 1 \n", "7028 0 1 1 0 \n", "7029 1 0 0 0 \n", "7030 0 0 0 0 \n", "7031 1 0 1 1 \n", "\n", " StreamingTV StreamingMovies PaperlessBilling MonthlyCharges \\\n", "0 0 0 1 29.85 \n", "1 0 0 0 56.95 \n", "2 0 0 1 53.85 \n", "3 0 0 0 42.30 \n", "4 0 0 1 70.70 \n", "... ... ... ... ... \n", "7027 1 1 1 84.80 \n", "7028 1 1 1 103.20 \n", "7029 0 0 1 29.60 \n", "7030 0 0 1 74.40 \n", "7031 1 1 1 105.65 \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 num_request_last_1_months \\\n", "0 0 2.0 \n", "1 0 3.0 \n", "2 0 3.0 \n", "3 0 0.0 \n", "4 0 2.0 \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", " num_request_last_3_months num_request_last_6_months \\\n", "0 2.0 2.0 \n", "1 3.0 3.0 \n", "2 6.0 6.0 \n", "3 0.0 0.0 \n", "4 5.0 5.0 \n", "... ... ... \n", "7027 0.0 0.0 \n", "7028 0.0 0.0 \n", "7029 0.0 2.0 \n", "7030 2.0 2.0 \n", "7031 0.0 0.0 \n", "\n", " num_request_last_12_months avg_num_days_till_solution \\\n", "0 2.0 0.0 \n", "1 3.0 0.5 \n", "2 6.0 1.5 \n", "3 0.0 0.0 \n", "4 5.0 2.0 \n", "... ... ... \n", "7027 3.0 1.0 \n", "7028 0.0 0.0 \n", "7029 2.0 0.0 \n", "7030 2.0 0.0 \n", "7031 0.0 0.0 \n", "\n", " avg_num_thread_till_solution total_tickets total_interactions \\\n", "0 1.0 1.0 2.0 \n", "1 1.0 3.0 8.0 \n", "2 1.5 3.0 6.0 \n", "3 1.0 1.0 2.0 \n", "4 2.0 2.0 5.0 \n", "... ... ... ... \n", "7027 1.0 1.0 3.0 \n", "7028 0.0 0.0 0.0 \n", "7029 1.0 1.0 2.0 \n", "7030 1.0 1.0 2.0 \n", "7031 0.0 0.0 0.0 \n", "\n", " avg_reply_delay num_complaint_requests last_channel_ \\\n", "0 10.169722 0.0 0 \n", "1 21.380208 1.0 0 \n", "2 19.322130 1.0 0 \n", "3 11.750556 1.0 0 \n", "4 28.044167 3.0 0 \n", "... ... ... ... \n", "7027 23.803889 2.0 0 \n", "7028 0.000000 0.0 1 \n", "7029 18.954583 2.0 0 \n", "7030 10.321667 2.0 0 \n", "7031 0.000000 0.0 1 \n", "\n", " last_channel_Chat last_channel_Email last_channel_Hotline \\\n", "0 0 0 1 \n", "1 0 0 1 \n", "2 1 0 0 \n", "3 0 1 0 \n", "4 0 0 1 \n", "... ... ... ... \n", "7027 0 1 0 \n", "7028 0 0 0 \n", "7029 0 1 0 \n", "7030 0 0 1 \n", "7031 0 0 0 \n", "\n", " last_channel_On-site last_channel_Social Media \\\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", " channel_most_used_last6mo_ channel_most_used_last6mo_Chat \\\n", "0 0 0 \n", "1 0 0 \n", "2 0 0 \n", "3 1 0 \n", "4 0 0 \n", "... ... ... \n", "7027 1 0 \n", "7028 1 0 \n", "7029 0 0 \n", "7030 0 0 \n", "7031 1 0 \n", "\n", " channel_most_used_last6mo_Email channel_most_used_last6mo_Hotline \\\n", "0 0 1 \n", "1 0 1 \n", "2 0 1 \n", "3 0 0 \n", "4 1 0 \n", "... ... ... \n", "7027 0 0 \n", "7028 0 0 \n", "7029 1 0 \n", "7030 0 1 \n", "7031 0 0 \n", "\n", " channel_most_used_last6mo_On-site \\\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", " channel_most_used_last6mo_Social Media \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 51 columns]" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "if \"customerID\" in df_final:\n", " df_final.drop(\"customerID\", axis=1, inplace=True)\n", "\n", "df_final" ] }, { "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": 72, "id": "b30f3010-ae54-40cf-bd72-0fc8b88a5d38", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.728441Z", "iopub.status.busy": "2026-03-24T17:55:10.728360Z", "iopub.status.idle": "2026-03-24T17:55:10.731124Z", "shell.execute_reply": "2026-03-24T17:55:10.730704Z", "shell.execute_reply.started": "2026-03-24T17:55:10.728433Z" } }, "outputs": [], "source": [ "# Split X and y\n", "X = df_final.drop(columns = ['Churn'])\n", "y = df_final['Churn'].values" ] }, { "cell_type": "code", "execution_count": 73, "id": "e1c15d59-37c5-4bec-a577-38f4ae248316", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.731484Z", "iopub.status.busy": "2026-03-24T17:55:10.731418Z", "iopub.status.idle": "2026-03-24T17:55:10.737544Z", "shell.execute_reply": "2026-03-24T17:55:10.737169Z", "shell.execute_reply.started": "2026-03-24T17:55:10.731477Z" } }, "outputs": [], "source": [ "# Splitting the data into train and test sets\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": "markdown", "id": "2235820d-6d46-4b0b-8465-5c681dd306bb", "metadata": {}, "source": [ "### Normalization\n", "How to scale/normalize the numerical columns?" ] }, { "cell_type": "code", "execution_count": 74, "id": "2fcbf05a-086a-475d-ad6a-2355448171c2", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.737920Z", "iopub.status.busy": "2026-03-24T17:55:10.737846Z", "iopub.status.idle": "2026-03-24T17:55:10.740351Z", "shell.execute_reply": "2026-03-24T17:55:10.739811Z", "shell.execute_reply.started": "2026-03-24T17:55:10.737912Z" } }, "outputs": [ { "data": { "text/plain": [ "['tenure', 'MonthlyCharges', 'TotalCharges']" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cols_ori_numeric" ] }, { "cell_type": "code", "execution_count": 75, "id": "491d8c7d-55d2-43f5-9ff2-1af8262fd7f1", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.741279Z", "iopub.status.busy": "2026-03-24T17:55:10.741211Z", "iopub.status.idle": "2026-03-24T17:55:10.743608Z", "shell.execute_reply": "2026-03-24T17:55:10.743040Z", "shell.execute_reply.started": "2026-03-24T17:55:10.741272Z" } }, "outputs": [ { "data": { "text/plain": [ "Index(['num_request_last_1_months', 'num_request_last_3_months',\n", " 'num_request_last_6_months', 'num_request_last_12_months',\n", " 'avg_num_days_till_solution', 'avg_num_thread_till_solution',\n", " 'total_tickets', 'total_interactions', 'avg_reply_delay',\n", " 'num_complaint_requests'],\n", " dtype='str')" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cols_feature_numeric" ] }, { "cell_type": "code", "execution_count": 76, "id": "d2ab6e1b-fb9f-4b42-8d15-7b25b6c3289f", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.743948Z", "iopub.status.busy": "2026-03-24T17:55:10.743877Z", "iopub.status.idle": "2026-03-24T17:55:10.745996Z", "shell.execute_reply": "2026-03-24T17:55:10.745644Z", "shell.execute_reply.started": "2026-03-24T17:55:10.743940Z" } }, "outputs": [ { "data": { "text/plain": [ "['tenure',\n", " 'MonthlyCharges',\n", " 'TotalCharges',\n", " 'num_request_last_1_months',\n", " 'num_request_last_3_months',\n", " 'num_request_last_6_months',\n", " 'num_request_last_12_months',\n", " 'avg_num_days_till_solution',\n", " 'avg_num_thread_till_solution',\n", " 'total_tickets',\n", " 'total_interactions',\n", " 'avg_reply_delay',\n", " 'num_complaint_requests']" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "numeric_final_cols = cols_ori_numeric + cols_feature_numeric.tolist()\n", "numeric_final_cols" ] }, { "cell_type": "code", "execution_count": 77, "id": "f0c6c033-031e-4870-aede-fb67a05fb6b4", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.746354Z", "iopub.status.busy": "2026-03-24T17:55:10.746257Z", "iopub.status.idle": "2026-03-24T17:55:10.748555Z", "shell.execute_reply": "2026-03-24T17:55:10.748054Z", "shell.execute_reply.started": "2026-03-24T17:55:10.746348Z" } }, "outputs": [], "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)" ] }, { "cell_type": "code", "execution_count": 78, "id": "7c0f563a-e438-448c-99b2-76c607beac6b", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:10.748933Z", "iopub.status.busy": "2026-03-24T17:55:10.748874Z", "iopub.status.idle": "2026-03-24T17:55:11.634488Z", "shell.execute_reply": "2026-03-24T17:55:11.634008Z", "shell.execute_reply.started": "2026-03-24T17:55:10.748927Z" } }, "outputs": [ { "data": { "image/png": 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for feat in numeric_final_cols: \n", " distplot(feat, df_final)" ] }, { "cell_type": "markdown", "id": "8e823d8f-d538-42c8-9edc-944a6e5a82de", "metadata": {}, "source": [ "### Überlegung: Welchen Scaler sollte ich nutzen? \n", "Da die numerischen Features über verschiedene Wertebereiche (value ranges) verteilt sind, nutzen wir hier den Standard Scalar, 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": 79, "id": "ee55e0a7-5331-4bc0-b41c-1fe106fe6890", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:11.634909Z", "iopub.status.busy": "2026-03-24T17:55:11.634820Z", "iopub.status.idle": "2026-03-24T17:55:12.591199Z", "shell.execute_reply": "2026-03-24T17:55:12.589917Z", "shell.execute_reply.started": "2026-03-24T17:55:11.634901Z" }, "scrolled": true }, "outputs": [ { "data": { "image/png": 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", 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", 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AAAC4NGp4AQAA4NIIeAEAAODSqOGtYN5znTlHG4PXtkE8AAAAGo521tXZFqOiosyMhJUh4C2HBrvR0dEN9fkAAACgnhw5ckTatGlT6T4EvOXQzK71Auo0pQAAAGhcdEp1TVBa47bKEPCWw1rGoMEuAS8AAEDjVZ3yUwatAQAAwKUR8AIAAMClEfACAADApRHwAgAAwKUR8AIAAMClEfACAADApRHwAgAAwKUR8AIAAMClMfEEHOLV48frfIw7oqLq5VwAAIBrI8MLAAAAl0bACwAAAJdGwAsAAACX5tCAd+3atTJ69GiJiooSNzc3WblyZaX7//DDD2a/sktCQkKp/ebPny/t27cXHx8f6d+/v2zYsKGB3wkAAAAaK4cGvFlZWRIbG2sC1JrYu3evxMfH25bw8HDbYytWrJApU6bIzJkzZfPmzeb4w4cPl8TExAZ4BwAAAGjsHNqlYcSIEWapKQ1wmzdvXu5jzz//vNx+++0yYcIEs75w4UL54osv5I033pBp06bV+ZwBAADgXJyyhrdXr17SqlUrGTZsmPz888+27fn5+bJp0yYZOnSobZu7u7tZX7duXYXHy8vLk4yMjFILAAAAXINTBbwa5GrG9sMPPzRLdHS0XHTRRaZ0QSUnJ0tRUZFERESUep6ul63ztTd79mwJDg62LXpcAAAAuAanmniic+fOZrEaOHCgHDhwQP7zn//Im2++WevjTp8+3dT9WmmGl6AXAADANThVwFuefv36yU8//WTuh4aGioeHh5w4caLUProeGRlZ4TG8vb3NAgAAANfjVCUN5dm6daspdVBeXl7Su3dvWbNmje3x4uJisz5gwAAHniUAAACaZIY3MzNT9u/fb1s/ePCgCWBDQkKkbdu2ptTg2LFjsmzZMvP4vHnzJCYmRrp16ya5ubny2muvyXfffSdff/217RhamjB+/Hjp06ePyf7qc7T9mbVrAwAAAJoWhwa8GzdulCFDhtjWrXW0GrAuWbLE9NiNi4sr1YXh/vvvN0Gwn5+f9OzZU7799ttSxxg7dqwkJSXJjBkzzEA17eiwatWq0wayAQAAoGlws1gsFkefRGOjg9a0W0N6eroEBQU5+nRc0qvHj9f5GHdERdXLuQAAANeO15y+hhcAAACoDAEvAAAAXBoBLwAAAFwaAS8AAABcGgEvAAAAXBoBLwAAAFwaAS8AAABcGgEvAAAAXBoBLwAAAFwaAS8AAABcGgEvAAAAXBoBLwAAAFwaAS8AAABcGgEvAAAAXBoBLwAAAFwaAS8AAABcGgEvAAAAXBoBLwAAAFwaAS8AAABcGgEvAAAAXBoBLwAAAFwaAS8AAABcGgEvAAAAXBoBLwAAAFwaAS8AAABcmkMD3rVr18ro0aMlKipK3NzcZOXKlZXu/9FHH8mwYcMkLCxMgoKCZMCAAbJ69epS+zz66KPmWPZLly5dGvidAAAAoLFyaMCblZUlsbGxMn/+/GoHyBrwfvnll7Jp0yYZMmSICZi3bNlSar9u3bpJfHy8bfnpp58a6B0AAACgsfN05IuPGDHCLNU1b968UutPPfWUfPLJJ/LZZ5/Jueeea9vu6ekpkZGR1T5uXl6eWawyMjKq/VwAAAA0bk5dw1tcXCynTp2SkJCQUtv37dtnyiQ6dOggN954o8TFxVV6nNmzZ0twcLBtiY6ObuAzBwAAwJni1AHvnDlzJDMzU6677jrbtv79+8uSJUtk1apVsmDBAjl48KBccMEFJjCuyPTp0yU9Pd22HDly5Ay9AwAAALh0SUNdLF++XB577DFT0hAeHm7bbl8i0bNnTxMAt2vXTt577z257bbbyj2Wt7e3WQAAAOB6nDLgfffdd2XixIny/vvvy9ChQyvdt3nz5nL22WfL/v37z9j5AQAAoPFwupKGd955RyZMmGBuR40aVeX+WvJw4MABadWq1Rk5PwAAADQuDs3wajBqn3nVetutW7eaQWht27Y1tbXHjh2TZcuW2coYxo8fLy+88IIpVUhISDDbfX19zWAz9cADD5hWZVrGcPz4cZk5c6Z4eHjIDTfc4KB3CQAAgCab4d24caNpJ2ZtKTZlyhRzf8aMGWZde+jad1h49dVXpbCwUO6++26TsbUu9957r22fo0ePmuC2c+fOZjBby5YtZf369WayCgAAADQ9bhaLxeLok2hstA+vZoy1Y4PO6Ib69+rx43U+xh1RUfVyLgAAwLXjNaer4QUAAABqgoAXAAAALo2AFwAAAC6NgBcAAAAujYAXAAAALo2AFwAAAC6NgBcAAAAujYAXAAAALo2AFwAAAC6NgBcAAAAujYAXAAAALo2AFwAAAC6NgBcAAAAujYAXAAAALo2AFwAAAC6NgBcAAAAujYAXAAAALo2AFwAAAC6NgBcAAAAujYAXAAAALo2AFwAAAC6NgBcAAAAujYAXAAAALo2AFwAAAC7NoQHv2rVrZfTo0RIVFSVubm6ycuXKKp/zww8/yHnnnSfe3t7SqVMnWbJkyWn7zJ8/X9q3by8+Pj7Sv39/2bBhQwO9AwAAADR2Dg14s7KyJDY21gSo1XHw4EEZNWqUDBkyRLZu3Sr33XefTJw4UVavXm3bZ8WKFTJlyhSZOXOmbN682Rx/+PDhkpiY2IDvBAAAAI2Vm8VisUgjoBnejz/+WK644ooK93nwwQfliy++kJ07d9q2XX/99ZKWliarVq0y65rR7du3r7z00ktmvbi4WKKjo2Xy5Mkybdq0ap1LRkaGBAcHS3p6ugQFBdX5veF0rx4/XufLckdUFJcWAIAmKqMG8ZpT1fCuW7dOhg4dWmqbZm91u8rPz5dNmzaV2sfd3d2sW/cpT15enrlo9gsAAABcg1MFvAkJCRIREVFqm65rgJqTkyPJyclSVFRU7j763IrMnj3b/IVgXTQjDAAAANfgVAFvQ5k+fbpJh1uXI0eOOPqUAAAAUE88a/OkP//8Uzp06CBnWmRkpJw4caLUNl3Xug1fX1/x8PAwS3n76HMroh0fdAEAAIDrqVWGV9uBaaeEt956S3Jzc+VMGTBggKxZs6bUtm+++cZsV15eXtK7d+9S++igNV237gMAAICmpVYBr7b76tmzp2n/pZnTO++8s1a9bjMzM017MV2sbcf0flxcnK3UYNy4cbb9//73v5vs8tSpU2XPnj3y8ssvy3vvvSf//Oc/bfvoOS1atEiWLl0qu3fvlkmTJpn2ZxMmTKjNWwUAAEBTDHh79eolL7zwghw/flzeeOMNiY+Pl/PPP1+6d+8uzz//vCQlJVXrOBs3bpRzzz3XLNZgVe/PmDHDrOtxrcGviomJMW3JNKur/XXnzp0rr732munUYDV27FiZM2eOOYaepwbQ2rKs7EA2AAAANA310odX23pptlUzstoaTEsLrrvuOnnmmWekVatW4mzow9vw6MMLAACcog+vZmjvuusuE9RqZveBBx6QAwcOmAysZn/HjBlTl8MDAAAAjunSoMHt4sWLZe/evTJy5EhZtmyZudVJHqylB0uWLJH27dvX/QwBAACAMx3wLliwQG699Va55ZZbKixZCA8Pl9dff70u5wYAAAA4JuDVkoW2bdvaMrpWWg6skzboY1rHO378+LqfIQAAAFAHtarh7dixo5nGt6yUlBRTzgAAAAA4dcBbUWMH7avr4+NT13MCAAAAHFPSoH1ylZubm+lz6+fnZ3usqKhIfv31V9P7FgAAAHDKgHfLli22DO+OHTtMna6V3tfJILQ1GQAAAOCUAe/3339vbnWaXp1praomvwAAAIBTdmnQHrwAAACASwW8V111lZlMQrO6er8yH330UX2cGwAAAHDmAl6dq1gHq1nvAwAAAC4V8NqXMVDSAAAAAJfuw5uTkyPZ2dm29cOHD8u8efPk66+/rs9zAwAAABwT8I4ZM0aWLVtm7qelpUm/fv1k7ty5ZvuCBQvqflYAAACAIwPezZs3ywUXXGDuf/DBBxIZGWmyvBoEv/jii/V1bgAAAIBjAl4tZwgMDDT3tYxBuza4u7vLX/7yFxP4AgAAAE4d8Hbq1ElWrlwpR44ckdWrV8ull15qticmJjIZBQAAAJw/4J0xY4aZQrh9+/bSv39/GTBggC3be+6559b3OQIAAABndqa1a665Rs4//3yJj4+X2NhY2/ZLLrlErrzyytqfDQAAANAYAl6lA9V0safdGgAAAACnD3izsrLk6aefljVr1pi63eLi4lKP//nnn/V1fgAAAMCZD3gnTpwoP/74o9x8883SqlUr25TDAAAAQGNTq4D3q6++ki+++EIGDRpU/2cElONYXp58m5oq8fn5klFYKJlFRfLq8eMytEULswxp0UI8+MMLAADUV5eGFi1aSEhIiNSX+fPnm44PPj4+puvDhg0bKtz3oosuMhnlssuoUaNs+9xyyy2nPX7ZZZfV2/nizAa6C48fl8cPH5ZfMjLkYG6unCwslDyLRTZlZsozR47IsO3b5byNG+X71FQ+GgAAUD8Z3ieeeMK0Jlu6dKn4+flJXaxYsUKmTJkiCxcuNMHuvHnzZPjw4bJ3714JDw8/bf+PPvpI8vPzbesnT540nSKuvfbaUvtpgLt48WLbure3d53OE2fe1sxMWRQfL4UWi2jRzHkBAdInMFCae3qKn4eHdPT1lW9SUmRlcrJsz8qSi7dtkytCQ2Xh2WdLhJcXHxkAADDcLBaLRWpIe+0eOHBA9KmamW3WrNlpUw9Xlwa5ffv2lZdeesms6wC46OhomTx5skybNq3K52uArMG3tkjz9/e3ZXjT0tLM5Bi1kZGRIcHBwZKens5EGg1EyxEq83N6urx54oTol7Orn59cGxYmUWX+aLkjKsrcJufny6OHDplMcJGItPH2lo+7dZM+QUENdfoAAMDBahKv1SrDe8UVV0h90Eztpk2bZPr06bZtOkXx0KFDZd26ddU6xuuvvy7XX3+9Ldi1+uGHH0yGWMsvLr74YnnyySelZcuW5R4jLy/PLPYXEI7zXWqqrEhKMvcHBgXJTRERldbnhnp5yUtnny1/j4qSa37/Xfbm5MgFW7fKa507y40REWfwzAEAQGNUq4B35syZ9fLiycnJUlRUJBFlghJd37NnT5XP11rfnTt3mqC3bDnDVVddJTExMSYT/dBDD8mIESNMEO3h4XHacWbPni2PPfZYPbwj1NXe7Gx5ryTYvbRFC7kqNLTaXUC6BwTIr717y427dskXKSly0+7dklxQIPe2acMHAwBAE1arQWtKSwZee+01k51NSUmxlTIcO3ZMzhQNdHv06HHahBea8b388svNY5qN/vzzz+W3334zWd/y6HvQdLh1OXLkyBl6B7Cn3Rdej483ZQya2b06LKzGLe+CPT3lkx495P6SIPe+/fvlP3yeAAA0abXK8G7fvt2UHWjdxKFDh+T22283XRt0QFlcXJwsW7asWscJDQ01GdcTJ06U2q7rZWdxK2/yi3fffVcef/zxKl+nQ4cO5rX2799vpj8uSwe0MajNsYotFlmckCDpRUXSystLri9nwGJ1afnDcx07io+7u8yKi5MpWm8uIlOio+v1nAEAgAtneLWrgg4M27dvn2klZjVy5EhZu3ZttY/j5eUlvXv3NjO2WemgNV0fMGBApc99//33Td3tTTfdVOXrHD161HRz0Eky0DitSU2VXdnZ0szNTe5o1Uq83Wv944OhmeEnYmLkkXbtzPr9Bw7IG/Hx9XS2AADAmdQqqtDygDvvvPO07a1bt5aEhIQaB8+LFi0yLc52794tkyZNMtnbCRMmmMfHjRtXalCbfTmDliuUHYiWmZkp//rXv2T9+vUm+6zB85gxY6RTp06m3Rkan/TCQvns5Elz/7pyujHUJeh9PCZGHizJ7N6xd698npxcL8cGAAAuXtKgP/+X18ngjz/+kLCwsBoda+zYsZKUlGRai2mw3KtXL1m1apVtIJuWSGjnBnvao/enn36Sr7/++rTjaYmEllxoAK11xlFRUXLppZea3sGULTROnyQnm4kkYnx85ILg4Ho//uwOHSQhP1+Wnjgh1+3aJWtiY2VAA7wOAABwoT68EydONCUC7733nqnd1QBTA03NuF544YWmN64zow/vmevDG5ebK0/FxZkaW83EdvD1rfYxrH14q6OguFiu2LlTvkxJkZaenrL+vPOkUx0nTQEAAM4Rr9WqpGHu3LmmdECzuTk5OTJ48GBTMhAYGCizZs2q7XmjidG/tbQFmQa7/QIDaxTs1lQzd3d5r1s36RsYaKYmHrljh5wsKGiw1wMAAE5e0qDR9DfffCM///yzbNu2zQS/5513nuncAFTXlsxM2ZeTYwaqXRka2uAXzt/DQz7t3l36b95sXveqnTvl69jYOg+QAwAALhbwaheFJUuWmBZkOihMBwbpBA/aRkwzdjXtm4qmSb8rWl6ghrZoISFlpqduKJHe3vJFjx4yaMsWWZueLhP37pVlXbrwvQUAwIV51jRI0QkdvvzyS4mNjTUTO+g27a6gbco0CF65cmXDnS1chrYgO5KXJ95ubibgrUsdcG1MiIyU/x47Jm+dOCGdfH1lZvv2tT4WAABwoYBXM7vaZ1dbfQ0ZMqTUY999950ZtKaTTmgrMaAyq0qyu+cHB0tAOdM9N7Su/v7yt/BweSsxUR49dEg6+vjITVVMdgIAAJxTjYoX33nnHXnooYdOC3bVxRdfLNOmTZO33367Ps8PLmh9err8kZMjGuYOq2V2tz5c0Ly5XFry+rft3Str09Icdi4AAKCRBLzafuyyyy6r8PERI0aYQWxAZZ6OizO3/YOCpMUZqt2tiA6Wuzo0VPItFrly5075IzvboecDAAAcHPCmpKTYJoQojz6WmppaH+cFF7U7K0s+OXlSdGijNbvqSO5ubvLmOedI/8BASSkslFE7dkhyfr6jTwsAADgq4C0qKhJPz4rLfnXyicLCwvo4L7iol44dM7c9/f2lVT1NIVxXvh4e8kmPHtLex0f25+SYCSpyi4ocfVoAAMBRXRq0G0NFU/Tm5eXV13nBBWUWFsqbJ06Y+0OaN5fGJMLLy7QrG7h5s/yckWFqet865xzalQEA0NQC3vHjx1e5Dx0aUJG3ExPlVFGRnOXrK50b4bS+2rnhw+7d5bLt22V5YqJpV/ZYTIyjTwsAAJzJgHfx4sV1fT00UfrrwIKScoa/R0WZ2tnG6JIWLWTh2WebCSkeP3xYOvr6yjjalQEA4NSYUxVnxPqMDNmWlSU+7u5ySyMPIG9r1Uqmt21r7mvgu7qkZzAAAHBOBLw4IxaUzIo2NizsjE0jXBdPxsTI9eHhUlDSruzn9HRHnxIAAKglAl40uJMFBfJeYqK5f1fr1k5xxbXkYmmXLnJZSIjkFBfLqO3bZeupU44+LQAAUAsEvGhwy0+ckDyLRXoFBEjfwECnueJe7u7yYbduZvrj9KIiuXT7dvk9K8vRpwUAAGqIgBcNbmlCgrmdEBnpdG2+/Dw85PMePeS8gABJKiiQi7dulV0EvQAAOBUCXjSoHZmZsikzU5q5ucnfwsOd8moHe3rKN7Gxcm5AgCQWFMgQgl4AAJwKAS/OSHb3ry1bSqiXl9NebR1o961d0HvR1q2yhZpeAACcAgEvGkxBcbG8VTKzWmNvRVaToLd3SXmDZnrp3gAAQONHwIsGo/1rTxQUSFizZjIiJMQlrrQGvWt69ZILSgayDdu2Tb46edLRpwUAACpBwIsGs6SknOGmiAhp5u46XzWt6V3Vs6cJ4rVl2egdO2yzyAEAACefWhiortSCAvmsJPM5vpGXM7xaMilGTWldcmphoZlF7q59+2R/To4827GjeDhZJwoAAFyd66Td0Kh8mJQk+RaL9PT3l9iAAHFFnm5ucktEhFzesqVZf/7oUbnm998lq6jI0acGAAAaW8A7f/58ad++vfj4+Ej//v1lw4YNFe67ZMkS08vVftHn2bNYLDJjxgxp1aqV+Pr6ytChQ2Xfvn1n4J3AannJzGp/i4hw6Yui379RLVvKbZGR4u3mJiuTk2Xwli0Sn5fn6FMDAACNJeBdsWKFTJkyRWbOnCmbN2+W2NhYGT58uCSWBEzlCQoKkvj4eNty+PDhUo8/++yz8uKLL8rChQvl119/FX9/f3PM3NzcM/COcCwvT35ISzMX4non7b1bU/2CgsxgttBmzUzf4f6bN8sm2pYBANAoODzgff755+X222+XCRMmSNeuXU2Q6ufnJ2+88UalWbXIyEjbEmGXRdTs7rx58+Thhx+WMWPGSM+ePWXZsmVy/PhxWbly5Rl6V03bisREsYiYKXnblcm+u7JBwcGy/rzzpLOvrxzJy5NBmzfL6/Hxjj4tAACaPIcGvPn5+bJp0yZTcmDl7u5u1tetW1fh8zIzM6Vdu3YSHR1tgtrff//d9tjBgwclISGh1DGDg4NNqURFx8zLy5OMjIxSC2pveUnvXWedWa0uOvr6mqB3dMuWkmexyMS9e+X2vXsll7peAACaZpeG5ORkKSoqKpWhVbq+Z8+ecp/TuXNnk/3VzG16errMmTNHBg4caILeNm3amGDXeoyyx7Q+Vtbs2bPlscceq7f31ZTtzc42P+nrgK5rw8KkKbHv9jAyJMT8NfnpyZPyWny8fJ2SIndGRZmSh6rcERXVwGcKAEDT4vCShpoaMGCAjBs3Tnr16iWDBw+Wjz76SMLCwuSVV16p9TGnT59ugmfrcuTIkXo956bknZLs7qUtWjj1VMJ15e7mJiNbtpR/tG4t/u7uEpeXJ08dPiw7s7IcfWoAADQ5Dg14Q0NDxcPDQ06UBElWuq61udXRrFkzOffcc2X//v1m3fq8mhzT29vbDISzX1BzWj/dVLozVFdXf395uF07ae/tLVnFxfLfY8fk46QkKbJolTMAAHD5gNfLy0t69+4ta9assW0rLi4265rJrQ4tidixY4dpQaZiYmJMYGt/TK3J1W4N1T0make7EuzLyRFfd3cZU9KbFv83HfED0dEyODjYXI5Vqany3JEjklxQwOUBAKAplDRoS7JFixbJ0qVLZffu3TJp0iTJysoyXRuUli9oyYHV448/Ll9//bX8+eefpo3ZTTfdZNqSTZw40dbB4b777pMnn3xSPv30UxMM6zGioqLkiiuucNj7bAqs2d0xoaES4MkkfvZ0amXNet+pvaHd3eVgbq48efiwbKZ1GQAADc7hUcnYsWMlKSnJTBShg8q0NnfVqlW2QWdxcXGmc4NVamqqaWOm+7Zo0cJkiH/55RfT0sxq6tSpJmi+4447JC0tTc4//3xzzLITVKD+6E/071rLGZpgd4bqOi8wUNr6+JiBbBr0vhIfLxdmZ5sBfl5233MAAFB/3CxaeIlStARCW5npADbqeavnu9RUuWTbNmnh6SkJAwdWGbzZdzRoqn8gfJqcbMobVJSXl9zeqpVEeXvTpQEAgHqO10gpoV5775KprB4PNze5MixM7m3dWgI9POR4fr48FRcnP6Wnm8F/AACg/hDwos7yiovlg6Qkc5/uDDXv4vBIu3Zyjp+fFFgs8uaJE3L9rl2SxoA2AADqDQEv6uyrkyclvahIWnt5yQUlnQhQfcGenqZf75WhoeZfyPeSkiR240b5KS2NywgAQD0g4EWdvV0yWO2GiAgz4QJq8S+im5tcFhIiU6OjpaOPj5moYvDWrTLz4EEpLC7mkgIAUAcEvKiT9MJC+Sw52dynO0Pdxfj6ypY+fWRcRIRomPv44cMm8D2Uk8M3FQCAWiLgRZ18mJQkeRaLdPPzk14BAVzNehDo6SlLzzlH3j7nHAny8JBfMjJMicO7ZWYPBAAA1UPAizp5qyQIuykiwkz6gfqjAwC39ukjA4OCJKOoSG7YvVvG794tpwoLucwAANQAAS9q7UhurvxQMrCK7gwNV+LwY69eMrNdO/Mv67ITJ+TcjRtlQ0ZGA70iAACuh4AXtfZOYqJox9gLg4PN7GFoGJ7u7vJoTIwJfNt6e8uB3FwZtGWLzD582ExgAQAAKkfAi3opZ0DDO795c9nWp49cFxYmhRaLPHTwoAzbtk2O5uZy+QEAqIRnZQ8CFdmemSk7srLEy81NrgkL40LVo6qmXb64eXPxcXeXFYmJ8n1amnTZsEFujoiQcwMDS+13R1QUnwsAAGR4Udfs7l9btpQWzZpxIc8gHRw4KDhY/t2unbTz9pas4mJZGB8vbyYkSC49ewEAOA0lDagxrRtdTjmDw0V4ecnUtm1leIsWov0xfsrIkCcOH5Y/srMdfWoAADQqBLyosR/T0uRYfr409/SUkS1bcgUdyNPNTa4KC5MpbdpIS09PSS4okOePHpUPkpIkt6iIzwYAAAJe1MbbJdnda8PCxNudv5kag7P9/OSRdu1kUFCQ6ZzxTWqq9Nm0SbacOuXoUwMAwOGIVlAjOUVFJnuo6M7QuPh6eMi4yEi5KypKAj085PfsbOm3ebPMOHhQ8qjtBQA0YQS8qJHPT540s35pP9jzg4O5eo1QbECAmajiqtBQ075M63p7bdwoP6enO/rUAABwCAJe1Ko7w40REeLOVMKNVqCnp3zQrZu837WrRDRrJnuys+WCLVvknj/+YGpiAECTQ8CLakvOz5cvU1JsAS8af/uya8LDZVe/fnJrZKSp7Z1//Lh0/e03+Tw52dGnBwDAGUPAi2p7NzHR/EQe6+8v3fz9uXJOIqRZM3m9Sxf5NjZWOvj4yNG8PBm9c6eM2r6dFmYAgCaBgBfVYrFYZFF8vLl/a6tWXDUndEmLFrKjb1+ZGh0tzdzcTLa++2+/yb8OHJCMwkJHnx4AAA2GgBfVsunUKdmelSXebm50Z3Bifh4e8kzHjrKzb18ZGRIiBRaLzDlyRM7+9VdZHB8vxRYtfAAAwLV4OvoE4BxeK8nuXh0WZn4iR+P36vHjlT4+JjTUlDi8n5QkJwoK5Na9e00Ls9GhoaZsRWuA74iKOmPnCwBAQyHgRZWyiopkeWKiuT+RcgaX0iMgQM7x95fvUlPli5QUOZqfLwuOH5d23t5yeWioKWXRwBcAAGdGSQOq9H5iopwqKpKOPj4yuHlzrpgLTk98aUiIPBUTIyNCQkzZyuG8PPnvsWMyaMsW+TYlxQS+AAA4q0YR8M6fP1/at28vPj4+0r9/f9mwYUOF+y5atEguuOACadGihVmGDh162v633HKLyUrZL5dddtkZeCeuyTpY7bZWrei968L8PTzkitBQmRUTI8NatDAD29ZlZMiw7dvlvE2bZEl8vOQWFTn6NAEAcL6Ad8WKFTJlyhSZOXOmbN68WWJjY2X48OGSWPITelk//PCD3HDDDfL999/LunXrJDo6Wi699FI5duxYqf00wI2Pj7ct77zzzhl6R67l96ws+SUjQzxEZHxkpKNPB2do0oprwsJM4PuP1q3F191dtmZmyoS9e6Xt+vWmzjc+L4/PAgDgNNwsDv6tUjO6ffv2lZdeesmsFxcXmyB28uTJMm3atCqfX1RUZDK9+vxx48bZMrxpaWmycuXKap1DXl6eWawyMjLMOaSnp0tQUJA0ZX/fu1deiY+XK0ND5aPu3c/YgCo0DjpoLaWgwAxafOnYMTlS8u+JZn91AOO4iAiTDfZ0d/jfzgCAJiYjI0OCg4OrFa859P9S+fn5smnTJlOWYDshd3ezrtnb6sjOzpaCggIJCQk5LRMcHh4unTt3lkmTJsnJkycrPMbs2bPNBbMuGuxCJLWgQN4smUr43jZtuCRNlHblmNq2rfzZv7+817WrDAoKMu3MdCKSkTt2SOt16+S+fftM6zpqfQEAjZFDA97k5GSToY0oM02trickJFTrGA8++KBERUWVCpq1nGHZsmWyZs0aeeaZZ+THH3+UESNGmNcqz/Tp081fB9blyJEjdXxnruGNhATJLi6Wnv7+cmFwsKNPBw6mWdxrw8Plp/POk029e8vk1q0lrFkzSSwokBeOHZM+mzZJt99+k0cOHpRfMzLo6QsAaDScui3Z008/Le+++67J5uqAN6vrr7/edr9Hjx7Ss2dP6dixo9nvkksuOe043t7eZsH/K7JYzE/Y6h9t2tCaCqWcFxholrkdO8rXqanyZkKCfHLypOzOzpYnDx82S3izZjKyZUsZFRJiukAEeTr1f24AAE7Mof8HCg0NFQ8PDzlR8rO5la5HVjFAas6cOSbg/fbbb01AW5kOHTqY19q/f3+5AS9O9/nJk3IoN1dCPD3lb+HhXCKUq5m7u4zSoLZlS0kvLJRPkpPNd2d1SorJ/C5JSDCLDnrsHRgoFwQHywXNm8v5wcHSkglMAABNIeD18vKS3r17m9KDK664wjZoTdfvueeeCp/37LPPyqxZs2T16tXSp0+fKl/n6NGjpoa3FZMmVNuLR4/aBi35emi4gqaoNoMLh7ZoIUOaN5f9OTlmOuodmZlmJrcNp06ZZW7Jd6ubn58MDA6W8wICTLa4h78/3zUAQINw+G+M2pJs/PjxJnDt16+fzJs3T7KysmTChAnmce280Lp1azOwTGlN7owZM2T58uWmd6+11jcgIMAsmZmZ8thjj8nVV19tssQHDhyQqVOnSqdOnUy7M1RtY0aGfJeWZrJyk5haFrXg4eYmnf38zHJtWJgMDwmR/0lLk/9JT5e16emyJztbfi9ZbM8RMbO+aQDc3d9fuvj5yTl+fhLj62uOBwCA0wa8Y8eOlaSkJBPEavDaq1cvWbVqlW0gW1xcnOncYLVgwQLT3eGaa64pdRzt4/voo4+aEont27fL0qVLTWsyHdCmfXqfeOIJ6nSr6am4OHP7t4gIaWtXGw3UVjsfH2kXGSk3lZQqJebny0/p6fLbqVOyWZfMTEkuKJCdWVlmsefl5iZn+/mZADjGx0fa2y16XJ0wAwCARt2H19n7urmanZmZ0mPjRtF82u99+5qMW0OgD2/ToqUxldH/DB3LyzOB75bMTNmdlWWywHtzciS3uLjS52qnCGsA3MbbWyK9vKRVyWLue3ubWnSdcREA0DTjNYdneNG4zC7J7uqkAg0V7KLpqckfONZg9eIWLUxrs5TCQjOzm9YB6yQYJ3UpLDQZ4ZziYkkqKDCLZosrojlg7RIRrIuHh/wlKMgEw6HNmpVaWpbcUrcOAK6FgBc2+7OzzWQC6t9t23Jl4HDubm62YLRHOY9nFxWVCoC1U4RZiooko+R+VnGxaAfu1MJCs6htZcomyvJzdz8tEG7u6WkWDZpt9z08Sm3TW52KmWwyADQuBLwold3VH4+1b2qvwECuDBo9Pw8Ps1Q2N2JBcbGcKiqyBcLWoFi3ZZaz6L8DOuFKXF6eWWpKp10O9PAwtcUB9rfu7qXXS263ZWaKt7u7eLu5iZe7u/i4u5u6ZbOtZNF1PW5lgXRVZSMA0JQR8MLYlZVl+qWqf7drx1WBS/UKDtGlGn1/tZZYa4ZLBcEl6zm6FBebRTPLeqvBdpo1q1xYaILlgpIyDF3qk4a61uDXPkC23l+blmaCaP8yQXZV2/xLjkFWGoArI+CFMfXAAfM/6ytDQ2UA0wijidKgT+t3dQmrxv72WVUNljUwTivJHmeVLLpNyyoy7dftbrW8Iq+42Cz5emux2Nb1fmHJuGL9pwbjubpSzjTpW6so06iM1jiXDYKtWWj7bfbZ6fK26W2QLp6e5pZAGkBjQcALWZOaKl+kpIinm5s83aEDVwRooG4jWq6gi9YFW/WrYmSxTvOtgXB+mUDYBMd2AbJO3mENsrPKBNkVbdNjmtfQ0c5a91xOIF0XWoZhHwDX9laDaTLQAOqCgLeJ0/+Z3r9/v7l/V1SU6XcKoPHwsGadq7Gv1g7XhDWYzrULqCsLrCu6b81Omwx0yTYpKe/QAYW61LWcwxoA63u01TXb1Td7VbJtV3a2+YPeo2S7p92t/aL7Wv8osS76Wjp4UlEnDTgvAt4m7s2EBPOTqo42f4TaXaBpBtP1PHlHcUkQnFMSAFtvc8tZt90vqYsuu11LrTR8NgMO6zkDXV1aI63B7/NHjphacO39HGp/W9LiTtfDmzUzvZ81UAbQeBDwNmFJ+fnyrz//tA1UC/XycvQpAXAB7vUUSGtd9M2RkabFnCm5KLm1lnhoBtl2v+RW1812u20bT50ytdCa0dbHCu1ubYtddts+2FYmi60Bd06OiC7VoPXN9u3qrG3s9P4tkZESVTJJimahATQ8At4mbPK+faZ3aU9/f7m3TRtHnw4AlKJ1u2+dOFHtq2JKE8oJsnUWvtoE2xoUl81MWwcclm1rd8ruVgNorZfOys+X4/n5px37lfh4233NDEd5eZkAuLWXl7T29jYzBtrfMlMgUHcEvE3Ux0lJsiIpyYzOfqNLF7IMAFAm2NaaXs3ABtUwUNY+ztZ2dea2pHuHbWKUku1aoKFJB122V9JlQ+uNrZOd6NKi5PbasDBbUKyzE3qSLQYqRMDbBOn0rHft22fuT23bVnozyQQA1FugbG3bpoFoZYGxZoGtwa/9kmp3XzPGmmm2TqFt772kpP9/XRFTItG6JFNsDYTtM8W6PcCT/+2jaeKb38ToYJJb9+yRhPx8OcfPT2YwUA0AHBIYa9/igCoCY61DtmaIUwsKSgXEOjDuWF6eHMvPN2UU8fn5ZtlYyetqHXF5gbB9gKxlFtbOFICrIOBtYp46fFg+OXnSjDpe1qWL+NTz6GwAQP3RNmuh1t7Nvr4VJjKsk56klpMltq5rHbLpdpGdbVq1VURLOaIqyRS3KSmhYMAdnAkBbxPy1cmTMuPQIXP/5bPPlj5VNLwHADR+mo01k3R4ekrbSvbT6bErKp1ItSuh0G4Vh3JzzVIZ7YlsrSceGBz8fwFxmYF3ek5AY8A3sYnYnZUlf9u92/Sz/HtUlNzaqpWjTwkAcAZZW8Vpn+CKaGlEehVBsS66nwbHusTl5VU46E5LNsoLhG33vbwk3MuLEgo0OALeJuCP7Gy5eNs28x+pAUFB8kKnTo4+JQBAI6St3Vo2a2aWygbclS2hKO++tnHT/fZkZ5ulItqJ2NqBQqfI1kBYl3be3qalnC56Pkwvjbog4HVxB3Jy5OKtW80gtR7+/vJZjx7UXQEAak0Dz0Cd5tnTU6Ir2U8n8TgtEC4z8E4nEtEJPlIKC83yZwVlFDqRhzX41aWd3X1dtMaZgBiVIeB1YdsyM2X0jh1mBG9XPz/5Nja20r/aAQCoL9pFIsLLyywVKaqghEJvTxYUmEUH2mkLt9+zs81SHp36OaJZM9vr/S08XM7285OzfX1pxQaDgNdFvZeYKBP27DEN0Lv4+cma2FhTJwUAQGPh4eYmIc2amaWy1mya/T1ZMknHyZL72lNeb9OKikwHisN5eWZRn508aXu+zmRnDX47l9x29fc3mWHarzUdBLwuRkfhaieGOUeOmPVLW7SQd7p2rfQ/JgAANObWbJVlijUg1kk5TuTny4mSW+0i/EdOjtmu0zvr8kNa2mlZYU0InVOyaBCst518fSn9c0EEvC7k25QUmbRvn+zPyTHrD0RHy+yYGKabBAC4dECsfYN1KSurqEgS7QJh65JQUGCywlszM81SdhCd/iKqM9eNCgmRc0oCYQ2O/ehd77QIeF3AplOnzIQSHyUn236+eemss+TKsDBHnxoAAA6jUzzH+PqapexkHVoeYZ2dTgd2x+flmft5FotZ18U+GNassQ6WM9lgzQqXBMK6tOBX1EaPgNdJ6ejXVSkp8vKxY/J1aqrtX8Z7WreWJ2NiaPYNAEAFtHZXs7i6xJZpuaYD5kwAnJ9vWqXt1pnpsrJM7bB1Qo6vUlJKHU+zwSYILgmErfe1DIPuEY1Dowh458+fL88995wkJCRIbGys/Pe//5V+/fpVuP/7778vjzzyiBw6dEjOOusseeaZZ2TkyJGlvrAzZ86URYsWSVpamgwaNEgWLFhg9nVmSSU1SBroajZXR7IqnRz4hogIeTA6WroHBDj6NAEAcEpudoPotKZX9Q4MNLenCgtLZ4RLFv1/sTUj/F2ZOmE/d3fpGRBgBsi19faWtmVuNaAmIG4iAe+KFStkypQpsnDhQunfv7/MmzdPhg8fLnv37pXw8PDT9v/ll1/khhtukNmzZ8tf//pXWb58uVxxxRWyefNm6d69u9nn2WeflRdffFGWLl0qMTExJjjWY+7atUt8fHykscsoLJTDJX9F6nzn2zMzZUtmpvkr056WLtwQHi53t2592s81AACg/lh7D2vHh7KDxe0DYGtArCUT2ilpfUaGWco9poeHCXw1QxymS7NmZtG+wuZ+yTZd1311oB0Bcu24WTQd6kAa5Pbt21deeukls15cXCzR0dEyefJkmTZt2mn7jx07VrKysuTzzz+3bfvLX/4ivXr1MkGzvp2oqCi5//775YEHHjCPp6enS0REhCxZskSuv/76Ks8pIyNDgoODzfOCgoKkoWn7MJ2FRgvrdUSpTtVYkZ7+/nJR8+ZyZWioXNC8uWnp4oxePX7c0acAAECDyS8uNoPl9P/bOv1yXG5uqVsNiGvKvWS6Zg1+za2np7nVxdfdXbzc3MwgPr31sq7b3fdydzfrumjg7FZyTL1vbkvKPdzK3C9vm3Wxsgbieh4jW7aUM6Em8ZpDM7z5+fmyadMmmT59um2bu7u7DB06VNatW1fuc3S7ZoTtafZ25cqV5v7BgwdNaYQew0ovhgbW+tzyAt68vDyzWOmFs17IM2FDfLzJ5Npr4elpplXs6Ocn3f38pFtAgPQJCJCWdm1Zsk6dEmeV48TnDgBAdYRqjKLBn/66HBxc6rHsoiI5lpcnR3JzTbIr2a7PsLmvWWKdga6gwNQVK52VTiOTMxOd1I52y9hdSVlqfbLGadXJ3To04E1OTpaioiKTfbWn63v27Cn3ORrMlre/brc+bt1W0T5laXnEY489dtp2zTQ7SmrJslVEPnTYWQAAgLq4r4ldvuOaaDzDr3nq1CmT3GzUNbyNgWaY7bPGWlaRkpIiLVu2pFamAf4a0z8kjhw5ckbKRdDw+ExdC5+n6+EzdS18nv9PM7sa7Gopa1UcGvCGhoaKh4eHnDhxotR2XY+MjCz3Obq9sv2tt7qtVatWpfbROt/yeHt7m8Ve8+bNa/muUB0a7BLwuhY+U9fC5+l6+ExdC5/n/6kqs2ulNcoO4+XlJb1795Y1a9aUyq7q+oABA8p9jm6331998803tv21K4MGvfb76F9Dv/76a4XHBAAAgOtyeEmDlhKMHz9e+vTpY3rvalsy7cIwYcIE8/i4ceOkdevWps5W3XvvvTJ48GCZO3eujBo1St59913ZuHGjvPrqq7ZRgvfdd588+eSTpu+utS2Zpru1fRkAAACaFocHvNpmLCkpSWbMmGEGlWnZwapVq2yDzuLi4kznBquBAwea3rsPP/ywPPTQQyao1Q4N1h68aurUqSZovuOOO8zEE+eff745pjP04HV1Wjqik4KULSGB8+IzdS18nq6Hz9S18Hk6aR9eAAAAoCE5tIYXAAAAaGgEvAAAAHBpBLwAAABwaQS8AAAAcGkEvHCoWbNmmc4bfn5+TPbhhObPny/t27c3HVD69+8vGzZscPQpoZbWrl0ro0ePNi0ctb2jdr+B89JWnn379pXAwEAJDw83bTn37t3r6NNCHSxYsEB69uxpm3BC5xb46quvuKbVRMALh8rPz5drr71WJk2axCfhZFasWGH6aGubuc2bN0tsbKwMHz5cEhMTHX1qqAVt5aifof4RA+f3448/yt133y3r1683kzMVFBTIpZdeaj5nOKc2bdrI008/LZs2bTLzD1x88cUyZswY+f333x19ak6BtmRoFJYsWWImDNG+yXAOmtHVDNJLL71kmyUxOjpaJk+eLNOmTXP06aEONMP78ccfM1mPC9F+95rp1UD4wgsvdPTpoJ6EhITIc889J7fddhvXtApkeAHUKjOvWYahQ4f+/39M3N3N+rp167iiQCOTnp5uC5Dg/IqKisxMs5qx19IGOMFMawCcT3JysvkPrnVGRCtd37Nnj8POC8Dp9NcX/QVt0KBBpWYlhfPZsWOHCXBzc3MlICDA/BLTtWtXR5+WUyDDi3qnP2frT6KVLQRFAHBmaC3vzp07TUYQzq1z586ydetW+fXXX83Yl/Hjx8uuXbscfVpOgQwv6t39998vt9xyS6X7dOjQgSvvxEJDQ8XDw0NOnDhRaruuR0ZGOuy8AJR2zz33yOeff266cOigJzg3Ly8v6dSpk7nfu3dv+e233+SFF16QV155xdGn1ugR8KLehYWFmQWu/R9d/Y/tmjVrbAOb9GdTXdf/wQJwLIvFYgaQ6k/eP/zwg8TExPCRuCD9725eXp6jT8MpEPDCoeLi4iQlJcXcak2o/lSj9C9YrU9C46UtyfTntD59+ki/fv1k3rx5ZgDFhAkTHH1qqIXMzEzZv3+/bf3gwYPm30cd5NS2bVuuqROWMSxfvlw++eQT04s3ISHBbA8ODhZfX19Hnx5qYfr06TJixAjz7+OpU6fM56t/zKxevZrrWQ20JYNDaenD0qVLT9v+/fffy0UXXeSQc0L1aUsybYmj/zPt1auXvPjii6ZdGZyP/o9zyJAhp23XP2q0bSCci46VKM/ixYurLDlD46Stx/RXtPj4ePOHi05C8eCDD8qwYcMcfWpOgYAXAAAALo0uDQAAAHBpBLwAAABwaQS8AAAAcGkEvAAAAHBpBLwAAABwaQS8AAAAcGkEvAAAAHBpBLwAAABwaQS8AOBkM2itXLmyRs/RmdKaN2/eYOcEAI0dAS8A1DLwrGx59NFHK3zuoUOHzD5bt26tl2uvU3GPHDlSWrZsKX5+ftK1a1e5//775dixY/VyfABwdgS8AFALOp+9dZk3b54EBQWV2vbAAw+ckev6yiuvyNChQyUyMlI+/PBD2bVrlyxcuFDS09Nl7ty5DfraBQUFDXp8AKgvBLwAUAsaYFqX4OBgk7G1roeHh8vzzz8vbdq0EW9vb+nVq5esWrXK9tyYmBhze+6555rnXXTRRWb9t99+k2HDhkloaKg55uDBg2Xz5s0VnsPRo0flH//4h1neeOMNc5z27dvLhRdeKK+99prMmDGj1P6rV6+Wc845RwICAuSyyy4zgblVdV5bz3XBggVy+eWXi7+/v8yaNctsf/LJJ817DgwMlIkTJ8q0adPMe7an56Ov7ePjI126dJGXX37Z9lh+fr7cc8890qpVK/N4u3btZPbs2XwvAdQbAl4AqGcvvPCCya7OmTNHtm/fLsOHDzdB4r59+8zjGzZsMLfffvutCTo/+ugjs37q1CkZP368/PTTT7J+/Xo566yzTKmCbi/P+++/b4LFqVOnlvu4fd1udna2OZ8333xT1q5dK3FxcaWy0NV9bS3VuPLKK2XHjh1y6623yttvv20C32eeeUY2bdokbdu2NUGxPd1Hg2/db/fu3fLUU0/JI488IkuXLjWPv/jii/Lpp5/Ke++9J3v37jX7a+AOAPXGAgCok8WLF1uCg4Nt61FRUZZZs2aV2qdv376Wu+66y9w/ePCgRf/zu2XLlkqPW1RUZAkMDLR89tlntm36vI8//tjcnzRpkiUoKKha56fP279/v23b/PnzLRERETV+7fvuu6/Ufv3797fcfffdpbYNGjTIEhsba1vv2LGjZfny5aX2eeKJJywDBgww9ydPnmy5+OKLLcXFxVW+FwCoDTK8AFCPMjIy5Pjx4zJo0KBS23Vds5uVOXHihNx+++0mu6plBVoXnJmZabKx5dEYVMsMqkMHs3Xs2NG2ruUDiYmJNX7tPn36lFrXjGy/fv1KbbNfz8rKkgMHDshtt91mSimsi5ZB6HZ1yy23mAF8nTt3NuUZX3/9dbXeEwBUl2e19wQANCgtKTh58qQpidA6Vq3/HTBggClbKM/ZZ59tBqdpWYQGsJVp1qxZqXUNlP8vaVuz19ba3ZrQoFktWrRI+vfvX+oxDw8Pc3veeefJwYMH5auvvjJlHtddd50ZiPfBBx/U6LUAoCJkeAGgHmlmNCoqSn7++edS23Vd24UpLy8vc1tUVHTaPprh1NrZbt26maAzOTm5wte65pprzLGeffbZch9PS0ur9nnX9LWtNCurA97s2a9HRESY6/Hnn39Kp06dSi3WwXvW6zZ27FgTGK9YscJ0nEhJSan2+QNAZcjwAkA9+9e//iUzZ840JQTarWDx4sXmJ3sdjKW0o4Gvr6/p3KCdHLQzgZYRaDmBDirTsgEtjdDj6H4ViY6Olv/85z+mw4HuP27cODPYS7s3LFu2zJQOVLc1WU1f22ry5MmmFEKfN3DgQBOs6kC9Dh062PZ57LHHTDCt71G7Q+Tl5cnGjRslNTVVpkyZYjpaaIZau1a4u7ubwXja7YLJMgDUFzK8AFDPNLjTQE4nf+jRo4cJbLULgQaVytPT03Qm0B66mv0cM2aM2f7666+bIFB/4r/55pvNcTQ4rsxdd91lal51kgntnqAtv7Q1mGZMa9ILuDavrW688UaZPn26eS1raYLW5GoQb6Xno23JNPDX66Etz3T2N2uGV9uZaZZag+a+ffuaiTm+/PJLE/wCQH1w05Fr9XIkAABETD9fzdBqxhgAGgNKGgAAtab9fXVmN+01rIPQ3nnnHTPw7JtvvuGqAmg0yPACAGotJydHRo8eLVu2bJHc3FwziO3hhx+Wq666iqsKoNEg4AUAAIBLY0QAAAAAXBoBLwAAAFwaAS8AAABcGgEvAAAAXBoBLwAAAFwaAS8AAABcGgEvAAAAXBoBLwAAAMSV/S8oSsaX7P/GOwAAAABJRU5ErkJggg==", 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", 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", 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", 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z6+lYLYOldVC1RUs7W2nwqK1G+g9FT7e5S9ehLRpaNkz/iWtLmbZouBNwl0RLKukoRdoBSUtzadCkpX+0VexMWmP09KG2kmmwprmDmnup+0dfQ/HOJ1VF8ye1FJmWl9LSYXbJK00dce5E5El6DOg26Qhw5557rtlmDYK0xJieNtd8UH1/lJbG0pJUGozo/tVj4MUXXzT71PnHkuZQaiknvU/fPz0+Nf/UVc1lrQ2r69M8WO2cpq21GvToDzzNMdcfIEo7mWngq58PPe60LJd+PpzL3ul9Sve1vu92J8yK0Nepx4+2cmqnJd123VYNoJ1/nGgurwbturwG8bqcBu2ab6qvq6zPpzs0BURbtfX4Ufp8TzzxhLmu75vdaq7bqmcjNGVJO1npZNN8Xk1nqi66fXb9XS0Hp6kO+qNFg0ZXtabdoe+vHqu6bn0f9MeQpnO4S3+I6Xujn0d9T7TTof5o1s/A0KFDK7RNqGEqVAMB8BMzZswwJWF69Ojh8n4tj6TllhISEkw5mwYNGpjSRM8884wpB+Rc1mjatGku1/HRRx9ZHTp0sIKDg08rk7Nlyxbr6quvturXr2/KP2kJomuvvdZasWJFuUpzKS21oyVwdD2NGjWyHnroIWv58uUuS3NpKR13SiDt3r3blF2qVauW1bBhQ+vee++1PvzwQ7NO5xJA5SnNpd58803rrLPOMvtUy0ppCaGSSnOVtF9d0eW1DFRxul5dvzMtXaXlnHQb2rZta7appNJcxddZ0raV9ppLYr+/JZUl0nVqCTctxxUeHm61bt3aGjNmjLVx48Yiy+n70r59e/P+6/G2YMECl++plpHSEmwRERFW3bp1rVtvvdX64YcfXJao0mNq1KhRpgRZSEiI1aRJE+sPf/iD9cEHHziWeeKJJ8znR8uI6XGipduefPJJx+dDacmxO++80xxDAQEB5SrT5eo1vPrqq6Y8mL5WfT7d7uLvnX6Ghg0bZsXHx5v3WC9Hjhx5Wims0j6f7pbJcjU5f+ZKWkYnVyWtynpOV59f3UeuSqS5On43b95sjqnIyEhzHFx88cXW2rVr3TouXZV303Jx+txa3sv5Nbm7Dt0efW+aN29u3tPY2FhznBU/xoGSBOgfTwfUAHyHFjzXkcC0dU5bk+G99IyCjnRV3lHJAMCXkDMLoERZWVlFbmvOrJ6S1M5yBLIAAG9AziyAEulwt1ojUjtjaOeiN99803Te0txZlP1DoKxawZpjqgNW1ESa16tD0ZZE82o90VHKU++bt+4PwBcQzAIokXbW0Y5qGrxq73Ht7KMdy7QgPUqnNU21Y19ptLOfdp6qqT+UVq9eXeL92nnKE+kRnnrfvHV/AL6AnFkAqAJa0kqHeS2rF7hd+7Wm2bRpU6mjSOmgB1qxoaa8b966PwBfQDALAAAAn0UHMAAAAPisGpczq2OOJyUlmQLZ1TmUIQAAANyjlWN1AI34+Hgzel5palwwq4FsRcaeBgAAQPXav3+/GbmvNDUumNUWWXvnVGQMagAAAFQtHd5cGx/tuK00NS6YtVMLNJAlmAUAAPBe7qSE0gEMAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD6rxg2agKLmJCW5tUtuiY9n1wEAAK9DyywAAAB8FsEsAAAAfBbBLAAAAHyWR4PZmTNnSufOnSU6OtpMvXr1ksWLF5f6mPfff1/atWsn4eHh0qlTJ/nss8+qbXsBAADgXTwazDZt2lSeeuop2bRpk2zcuFEGDBggw4YNk+3bt7tcfu3atTJy5Ei5+eabZcuWLTJ8+HAz/fDDD9W+7QAAAPC8AMuyLPEi9erVk2nTppmAtbgRI0ZIZmamfPLJJ455PXv2lK5du8qsWbPcWn9aWprExMRIamqqaQ2u6ahmAAAAvE154jWvyZnNz8+Xd955xwSrmm7gyrp162TgwIFF5g0ePNjML0l2drbZIc4TAAAA/IPHg9lt27ZJZGSkhIWFyW233SYLFy6UDh06uFw2OTlZGjVqVGSe3tb5JZk6daqJ7O2pWbNmlf4aAAAAUEOD2bZt28rWrVvlm2++kdtvv11Gjx4tP/74Y6Wtf9KkSaaJ2p72799faesGAABADR8BLDQ0VBISEsz17t27y4YNG+SFF16Q2bNnn7ZsXFycHDp0qMg8va3zS6ItvjoBAADA/3i8Zba4goICk+fqiubSrlixosi85cuXl5hjCwAAAP/m0ZZZTQEYMmSING/eXNLT02X+/PmyatUqWbp0qbl/1KhR0qRJE5P3qu666y7p16+fTJ8+XS6//HLTYUxLes2ZM8eTLwMAAAA1MZg9fPiwCVgPHjxoOmfpAAoayF566aXm/sTERAkM/F/jce/evU3A+/DDD8tDDz0kbdq0kUWLFknHjh09+CoAAADgKV5XZ7aqUWe2KOrMAgAAb+OTdWYBAACA8iKYBQAAgM8imAUAAIDPIpgFAACAzyKYBQAAgM8imAUAAIDPIpgFAACAzyKYBQAAgM8imAUAAIDPIpgFAACAzyKYBQAAgM8imAUAAIDPIpgFAACAzyKYBQAAgM8imAUAAIDPIpgFAACAzyKYBQAAgM8imAUAAIDPIpgFAACAzyKYBQAAgM8imAUAAIDPIpgFAACAzyKYBQAAgM8imAUAAIDP8mgwO3XqVDn//PMlKipKYmNjZfjw4bJjx45SHzNv3jwJCAgoMoWHh1fbNgMAAMB7eDSYXb16tUyYMEHWr18vy5cvl9zcXBk0aJBkZmaW+rjo6Gg5ePCgY9q3b1+1bTMAAAC8R7Ann3zJkiWntbpqC+2mTZukb9++JT5OW2Pj4uKqYQsBAADgzbwqZzY1NdVc1qtXr9TlMjIypEWLFtKsWTMZNmyYbN++vcRls7OzJS0trcgEAAAA/+A1wWxBQYHcfffd0qdPH+nYsWOJy7Vt21Zee+01+eijj+TNN980j+vdu7f89ttvJeblxsTEOCYNgAEAAOAfAizLssQL3H777bJ48WL56quvpGnTpm4/TvNs27dvLyNHjpTHH3/cZcusTjZtmdWAVluBNfe2ppuTlOTWcrfEx1f5tgAAANjxmjZCuhOveTRn1nbHHXfIJ598ImvWrClXIKtCQkKkW7dusnPnTpf3h4WFmQkAAAD+x6NpBtoorIHswoUL5YsvvpBWrVqVex35+fmybds2ady4cZVsIwAAALyXR1tmtSzX/PnzTf6r1ppNTk4287VZuVatWub6qFGjpEmTJib3VT322GPSs2dPSUhIkJSUFJk2bZopzTVu3DhPvhQAAADUtGB25syZ5rJ///5F5s+dO1fGjBljricmJkpg4P8akE+cOCHjx483gW/dunWle/fusnbtWunQoUM1bz0AAAA8zWs6gHljQnFNQAcwAADgy/Ga15TmAgAAAMqLYBYAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD7Lo8Hs1KlT5fzzz5eoqCiJjY2V4cOHy44dO8p83Pvvvy/t2rWT8PBw6dSpk3z22WfVsr0AAADwLh4NZlevXi0TJkyQ9evXy/LlyyU3N1cGDRokmZmZJT5m7dq1MnLkSLn55ptly5YtJgDW6YcffqjWbQcAAIDnBViWZYmXOHLkiGmh1SC3b9++LpcZMWKECXY/+eQTx7yePXtK165dZdasWactn52dbSZbWlqaNGvWTFJTUyU6OlpqujlJSW4td0t8fJVvCwAAgB2vxcTEuBWveVXOrG6wqlevXonLrFu3TgYOHFhk3uDBg838klIZdGfYkwayAAAA8A9eE8wWFBTI3XffLX369JGOHTuWuFxycrI0atSoyDy9rfNdmTRpkgmS7Wn//v2Vvu0AAADwjGDxEpo7q3mvX331VaWuNywszEwAAADwPxVqmd29e3elbsQdd9xhcmBXrlwpTZs2LXXZuLg4OXToUJF5elvnAwAAoGapUDCbkJAgF198sbz55pty6tSpCj+59j3TQHbhwoXyxRdfSKtWrcp8TK9evWTFihVF5mklBJ0PAACAmqVCwezmzZulc+fOMnHiRNMieuutt8q3335bodQCDYjnz59vas1q3qtOWVlZjmVGjRpl8l5td911lyxZskSmT58uP//8szzyyCOyceNGExQDAACgZqlQMKtlsF544QVJSkqS1157TQ4ePCgXXnih6bj17LPPmhJb7pg5c6bplNW/f39p3LixY3r33XcdyyQmJpr123r37m2C3zlz5kiXLl3kgw8+kEWLFpXaaQwAAAD+qVLqzGod15dfftm0oObk5EhoaKhce+218vTTT5vg1FfrltUE1JkFAAA1ts6snt7/85//bAJWbZG97777ZNeuXSaHVVtthw0bdiarBwAAACq/NJcGrnPnzpUdO3bI0KFD5Y033jCXgYG/x8bakWvevHnSsmXLiqweAAAAqLpgVnNdb7rpJhkzZkyJaQQ6LO2rr75akdUDAAAAVRfMahpB8+bNHS2xNk2/1RG29D7Nmx09enRFVg8AAAC4pUI5s61bt5ajR4+eNv/48eNu1YoFAAAAPBbMllQAISMjQ8LDw890mwAAAIDKTzPQQRJUQECATJ48WSIiIhz35efnyzfffGNq0AIAAABeF8xu2bLF0TK7bds2kxdr0+s6iIGW5wIAAAC8LphduXKluRw7dqwZAYxBBwAAAOBz1Qy0xiwAAADgM8Hs1VdfbQZC0NZYvV6aBQsWVMa2AQAAAJUTzOr4uNrxy74OAAAA+Eww65xaQJoBAAAAfLbObFZWlpw8edJxe9++ffL888/LsmXLKnPbAAAAgMoPZocNGyZvvPGGuZ6SkiI9evSQ6dOnm/kzZ86syCoBAACA6glmN2/eLBdddJG5/sEHH0hcXJxpndUA91//+ldFVgkAAABUTzCrKQZRUVHmuqYWaHWDwMBA6dmzpwlqAQAAAK8NZhMSEmTRokWyf/9+Wbp0qQwaNMjMP3z4MAMpAAAAwLuD2cmTJ5tha1u2bCkXXHCB9OrVy9FK261bt8reRgAAAKDyRgD74x//KBdeeKEcPHhQunTp4ph/ySWXyFVXXVWRVQIAAADVE8wq7fSlkzOtagAAAAB4dTCbmZkpTz31lKxYscLkyRYUFBS5f/fu3ZW1fQAAAEDlBrPjxo2T1atXy4033iiNGzd2DHMLAAAAeH0wu3jxYvn000+lT58+lb9FAAAAQFVWM6hbt67Uq1dPztSaNWvkiiuukPj4eNO6q+W+SrNq1SqzXPEpOTn5jLcFAAAAvqdCwezjjz9uynPp4AlnQnNvtRrCjBkzyvW4HTt2mEoK9hQbG3tG2wEAAIAalGYwffp02bVrlzRq1MjUmg0JCTltuFt3DBkyxEzlpcFrnTp1yv04AAAA+JcKBbPDhw8XT+ratatkZ2dLx44d5ZFHHik1d1eX08mWlpZWTVsJAAAArwxmp0yZIp6glRNmzZol5513nglQ//3vf0v//v3lm2++kXPPPdflY6ZOnSqPPvpotW8rAAAAql6AZVlWRR6YkpIiH3zwgUk3uP/++02HME0v0NSDJk2alH9DAgJk4cKF5W717devnzRv3lz+85//uN0y26xZM0lNTZXo6Gip6eYkJbm13C3x8VW+LQAAAHa8FhMT41a8VqGW2e+//14GDhxonmTv3r0yfvx4E8wuWLBAEhMT5Y033pDqoqOOffXVVyXeHxYWZiYAAAD4nwpVM5g4caKMGTNGfv31VwkPD3fMHzp0qCm3VZ22bt1q0g8AAABQ81SoZXbDhg0ye/bs0+ZrekF5ar5mZGTIzp07Hbf37NljglNt5dXUgUmTJsmBAwccLb3PP/+8tGrVSs455xw5deqUyZn94osvZNmyZRV5GQAAAKiJwayetndVFeCXX36Rhg0bur2ejRs3ysUXX1ykxVeNHj1a5s2bZ2rIatqCLScnR+69914T4EZEREjnzp3l888/L7IOAAAA1BwV6gA2btw4OXbsmLz33numFVVzaIOCgkznrb59+5oWVH9IKK4J6AAGAAB8OV4LrOigCZoioK2wWVlZpqJAQkKCREVFyZNPPlnR7QYAAACqPs1AI+Xly5fL119/Ld99950JbLXOq1Y4AAAAALw2mC0oKDD5rFqGS8tyaX1Y7ZQVFxcnmrGgtwEAAIDqUK40Aw1Wr7zySpMzq52wOnXqZCoL7Nu3z5Tquuqqq6puSwEAAIAzaZnVFlmtI7tixYrTKghoiSztAKZltEaNGlWe1QIAAABV3zL79ttvy0MPPeSyFNaAAQPkwQcflLfeeqtiWwIAAABUZTCrJbguu+yyEu8fMmSI6RAGAAAAeF0we/z4cWnUqFGJ9+t9J06cqIztAgAAACo3mM3Pz5fg4JLTbHXghLy8vPKsEgAAAKieDmBazUCrFuhwtq5kZ2dXfEsAAACAqgxmR48eXeYyVDIAAACAVwazc+fOrbotAQAAAKoyZxYAAADwJgSzAAAA8FkEswAAAPBZBLMAAADwWQSzAAAA8FkEswAAAPBZBLMAAADwWQSzAAAA8FkEswAAAPBZBLMAAADwWQSzAAAA8FnBnt4AwBfNSUoqc5lb4uOrZVsAAKjJPNoyu2bNGrniiiskPj5eAgICZNGiRWU+ZtWqVXLuuedKWFiYJCQkyLx586plWwEAAOB9PBrMZmZmSpcuXWTGjBluLb9nzx65/PLL5eKLL5atW7fK3XffLePGjZOlS5dW+bYCAADA+3g0zWDIkCFmctesWbOkVatWMn36dHO7ffv28tVXX8lzzz0ngwcPrsItBQAAgDfyqQ5g69atk4EDBxaZp0Gszi9Jdna2pKWlFZkAAADgH3wqmE1OTpZGjRoVmae3NUDNyspy+ZipU6dKTEyMY2rWrFk1bS0AAACqmk8FsxUxadIkSU1NdUz79+/39CZ5haM5OfLhkSPy9uHDsujoUcnKz/f0JgEAAPh3aa64uDg5dOhQkXl6Ozo6WmrVquXyMVr1QCf8zwO7dsm0YkH9pvR0uS0+XpqwrwAAgA/xqZbZXr16yYoVK4rMW758uZkP98w7eNARyJ4TESH9YmKkbnCwHM7NlamJibKBnGIAAOBDPNoym5GRITt37ixSektLbtWrV0+aN29uUgQOHDggb7zxhrn/tttuk5deekkeeOABuemmm+SLL76Q9957Tz799FMPvgrf8X1Ghvz511/N9cdatpS/t2xpiv9fmZ8vrx48KD+ePCmvJSdLfFiYz7TQujN4gWIAAwAA/JNHW2Y3btwo3bp1M5OaOHGiuT558mRz++DBg5KYmOhYXstyaeCqrbFan1ZLdP373/+mLJcbUvPy5I/bt0tWQYEMrltX/taiheO+yKAgubNJE+lcu7YUiMj8w4elwLIq/w0HAADwp5bZ/v37i1VK0ORqdC99zJYtW6p4y/zPw3v2yK9ZWdIsLEzebN9eAgMCityvt0fGxsrPe/fKzqwsWZeWJn1iYjy2vQAAAH6XM4uKVy7QNAL1atu20iA01OVy9UJC5Ir69c11rXSQQYUDAADg5Qhma4CZSUkmvaB7ZKQMrFu31GUvqVtX4kNDJbOgQBYePVpt2wgAAFARBLN+7lR+vrx44IC5fl+zZhJQLL2guKCAALm+cGCKtampcjw3t1q2EwAAoCIIZv3cfw4dkiO5udI8LEz+2LChW49JqFVLzq5Vy3QG+yIlpcq3EQAAoKIIZv2YViSYXlhT9p6mTSU40P23e1BhOsKXqamMDgYAALwWwawfW3z8uOzIypKYoCC5uXHjcj32nNq1pXFoqJwqKJA1qalVto0AAABngmDWj72enGwub2rcWKKCy1eFTUt1XVrYOqupBjkFmnQAAADgXQhm/VR6Xp7899gxc/3Gwg5d5dUjKsq06qbk5ck7hw9X8hYCAACcOYJZP7Xo6FGTItAuIkK6RkZWaB0hgYEyoLB19oXffit1gAsAAABPIJj1UzokrbouNrbMclyluTAmRkICAmRzRoZ8k5ZWiVsIAADg48PZomoczsmR5cePm+s6RO2ZiAwKkvOioszwtjOSkqRnKUPczklKcmudt8THn9E2AQAA2GiZ9UPvHzki+SJyflSUJEREnPH6+tepYy7fO3zYBMoAAADegmDWD80/dMiRYlAZWoaHm8A4x7Lk1YMHK2WdAAAAlYFg1s/szcqStWlpolmyIyopmFUTmjQxl7OSkiSfjmAAAMBLEMz6mQVHjzpSAxqHhVXaekc0bCj1g4MlMTtbPi0s+QUAAOBpBLN+ZsGRI+by6gYNKnW94U6jiM04cKBS1w0AAFBRBLN+5FBOjkkxUMMrOZhVt8XHm/SFZSdOyC8nT1b6+gEAAMqLYNaPfHT0qOiwBtpZq2l4eKWvv1WtWjK0Xj1zfaabZbgAAACqEsGsH1lYmC9b2SkGrjqCzT14UDLztQAYAACA5xDM+onUvDxZceKEuX5Vw4ZV9jyD69WT1uHhkpqf7ygBBgAA4CkEs35CKwzkWpa0j4iQtpUwUEJJAgMC5PbC1tmXk5LEokwXAADwIIJZP0sxuKoKUwxsY+PiJDwwULZmZMjXqalV/nwAAAAlIZj1A1n5+bK4sPbr1VWYYmCrFxIiNzZqZK5PTUys8ucDAAAoCcGsH1h+4oRkFhRI87AwOTcyslqe84FmzczB89nx47IlPb1anhMAAKA4glk/SjHQ2rIBAVoJtuolREQ4hsv9B62zAACgJgezM2bMkJYtW0p4eLhccMEF8u2335a47Lx580zA5jzp42qqvIIC+W815ss6e6h5c3P54ZEj8lNmZrU+NwAAgFcEs++++65MnDhRpkyZIps3b5YuXbrI4MGD5fDhwyU+Jjo6Wg4ePOiY9u3bV63b7E2+TE2VY3l5Uj84WC6MianW5+4YGSnD6tc3AzU8RessAACoicHss88+K+PHj5exY8dKhw4dZNasWRIRESGvvfZaiY/R1ti4uDjH1KiwM5Ir2dnZkpaWVmTyJwsKW2WHNWggwYHV/3b+rUULc/nWoUOSnJNT7c8PAABqNo8Gszk5ObJp0yYZOHDg/zYoMNDcXrduXYmPy8jIkBYtWkizZs1k2LBhsn379hKXnTp1qsTExDgmfYy/0BqvizyUYmA7Pzpa/lC/vuhYYO8dPkzdWQAAUK2CxYOOHj0q+fn5p7Ws6u2ff/7Z5WPatm1rWm07d+4sqamp8swzz0jv3r1NQNu0adPTlp80aZJJY7Bpy6y/BLQb09Plt+xsiQwKkoF163psO55t3VqWHT8u20+elO8zM6VLNVVUqGnmJCW5tdwt8fFVvi0AAHgLj6cZlFevXr1k1KhR0rVrV+nXr58sWLBAGjZsKLNnz3a5fFhYmMmxdZ78rYrBkHr1JDwoyGPb0SYiQiYW/kB478gRyS0o8Ni2AACAmsWjwWyDBg0kKChIDh06VGS+3tZcWHeEhIRIt27dZOfOnVKTaIrBgiNHzPWrPZRi4OxvzZtLneBgOZqbK8tOnPD05gAAgBrCo2kGoaGh0r17d1mxYoUMHz7czCsoKDC377jjDrfWoWkK27Ztk6FDh0pN8l1GhuzIypKwgAAZWr++pzdHIoOD5ZoGDeTV5GQzkEKn2rWleQ0umeYvSG0AAHg7j6cZaD7rK6+8Iq+//rr89NNPcvvtt0tmZqapbqA0pUDzXm2PPfaYLFu2THbv3m1Ked1www2mNNe4ceOkJnm7sHSZdr6KDvbobxKH86OipHPt2pJnWTL74EHJzNduYQAAAFXH41HQiBEj5MiRIzJ58mRJTk42ubBLlixxdApLTEw0FQ5sJ06cMKW8dNm6deualt21a9easl41RYFlyTuFwezIUsqSVTctmTYmLs6MCKbpBnOTk+XP8fESWE2jkgEAgJrH48Gs0pSCktIKVq1aVeT2c889Z6aabF1amiRmZ0tUUJAMrVdPvEntoCC5tXFjeXr/ftmWmSmfHj8uV3hBGgQAAPBPHk8zQPnNL+wwp7Vla3mwikFJNFd2ZGysuf7JsWPy32PHakT9WW0xBwAANbBlFu7LKyiQ9wurGNgBozfSoXXT8vLko2PHTECbU1Bgqi5oKoI/BK37s7Nlx8mTsjsrS47k5pq0ipMFBRIaECDhgYFSLyREEk+dksvq1ZOe0dEeGZ0NAICagGDWx6xISTHBU4OQELnEgwMluEOrLIQGBprgW8t1ncjL8+oAvLTg9desLFl54oR8kZIiK1NSTPDqSo5lSU5+vqTl58uTiYlmahIaKvc1a2YGM4jwwpZ0AAB8GcGsj6YY/KlhQwnxgdY+HZlMy4fNP3xYNqSny86sLOkcGVmlgfix3FwTfB7MyTHXj+fmyqykJBOUaiJATHCw+TFQPyTEXOqkNXJDAgIkOCBAThUUSHJOjpl+yMyUTenpJjh1pq8poVYtOTsiQhqHhkrDkBCTw5xtWZKVn29abvW6jox2ICdH7tm1ywS2D7doIRPi42mpBQCgkhDM+pATubmOFIMbvKiKQVkuqlNHmoaFyWvJyXI4N1cGfvedXNuwoUxp2VI61K59xuvXEcd+PHnS1N796eRJOZ6XJ5VNUwcuiIoyQfiAunXNc2ngW1yU/gkJkWbh4aYlNrugQF5PTpanEhNlz6lTcvfOnTIvOVlmn3229PCj0egAAPAUglkf8sahQ5JVUGAGJOjlY4FQq1q1TKvkB0eOyJrUVDPsrQbmGtTe1LixDKhTp1ytlSm5uaZSwuykJNmemWlaQW26lhbh4dI8LMzR+np1w4aioaculZqXZ9IEtNXWvkzNzzdBsdbI1dSIRqGhEhcaKq3Dw+X86GjpEBFRpCVcn9MdYYGBJqi9KS7ODCgxafdu2ZqRIT03bzZly6aedZZEeUmdYAAAfBH/RX2EVgOYeeCAuX57fLxPdqTSwO76Ro3kxTZt5NG9e2XB0aPy7pEjZooNCZErGzSQHlFR0j0qSs4KDzdlvjSA1I5ketpeO1utTUuTNSkp8m16ugk8bXWDg6VrZKQZtOGsWrVMS6qzwR4uYaaB+q3x8aYCxf27dpkfJjOSkuTjY8dMK+0Qypc5MOoYAKA8CGZ9hHY60uFrI4OCfCrFwBXNmf2wY0fZmp4ucw4elPcOHzbpB/8+eNBMzvRUvnPQ6kxbS7UFtltkpGmF9YUAPzY0VF5v315ubNRIbvnlF5N6MHTbNvOePte6tTQIDfX0JgIA4FMIZn3Ey4WtshoE+ctp6a5RUfJyVJS8kJAgn584IatSUkxnq00ZGZJSmPdqB7La8qp5tzpkbt86daRvTIxJXXC3Fc/bDKxXT7adf75M3rNHnv/tN3nz0CFZevy42Rf/FxvrE4E5AADewD+iIj+XlJ0ti44edaQY+BtNJdDT7Papdk2p0BJXmfn5cjI/31QaiPSTAN6ZplFMT0iQEbGxcvOOHaZywnU//SQv/Pab/OOss0xHMwAAUDrvr+0EU1Yqv3Aggk6RkX6/R7RVMqxw4IGm4eF+Gcg606oGm7p3l8dbtpSIwED5Jj1dLvnuOxmwdassOHLEdEwDAACu+XeU4Ae0p72ehlZ/adLE05uDKqIVFB5u2VLGx8fLk/v2mR8wmietk9ax1ZxabbHWzm1BpCAAAOBAMOvlnk5MlPT8fOlSu7Zc07ChpzcHVUxLgv2rTRszYpiWHdMOcTr4w7T9+839tQMDpU2tWtJSp/BwaRkWJrUYVQwAUIMRzHp5ruxLhR2/njzrLAmkRa7GaB4ebt5zHVjiv8eOmZzphUeOSGZBgWzNzDSTTevhalCrKRnaSe5oTg5VESrAnc6EWjMYAOBdCGa9mJ5u1kESdICEoR6ukwrPpR9oi7xOM6OjZe+pU6acl32pgz7YQ+9Kerp5jKalxIeGmhJo2qLfRS8jI+XsWrUYRhcA4HcIZr3UnqwseaWw5uo/WrWiVBNMrmzrWrXMZEvPyzOB7b7sbPmtcDqSmytJOTmSdPy4LDl+3LGsDiRxTkSECXJ1UIrGYWGmVVdrF+t9oYU1fXPtqaDAVFjIt6zfJxHH9QLLkvCgIIkOCpKooCBTdSKCdAcAgAcQzHohDRTG7dhhAoqBdetKf0o0oQRac1grXDhXubguNla2ZWbKdxkZ8l3hpd7OyM83NXx1qmyP7tsnTUJDpW1EhBluuWtha3CH2rVNZQoAAKoKwawXeu633+SLlBRTpunlNm08vTnwMVrKrFdMjJmcfyBpWoId2O4/dcp0LDuUkyMnCwpMOkt2QYEZcS3EngIDJTUvz7QIB8nvLcP2dc3f1sdo50QdbljXcSAnx0x67Np0fe0iIn4PbgtTHtpHRJhWYaoyAAAqA8Gsl9Fg46Hdu8315xMSpE1EhKc3CX4g0ClF4epyVMVwd4Q1zen99eRJ+fnkSdMavFVbhTMy5ERenklV0OlNp+U1WNahiBuGhJhBMWKCg82lTrqOsIAAky9sX+qklRyig4NNWoO/BMLu7l86ngFAyQhmvUhGXp5c/+OPZvSrYfXry7jGjT29SYBb6oeESP2YGOnp1BqsdXH3Z2f/nu6QkfF7gJuZafLBNYVmZ1aWmcpLw1gNaLUWr9bg1aBYg/SznC79faANAMD/8I3vJbQjz+Xbtsn2kyelUUiIvNK2LZ2+4PMjuWmJMZ2uaNDAMT+voMB0UNOOa8dzcyUlL88xpebnyzdpaZJTUGB+1OllduGlDm+clp8vloi53JKRIVtKeO7YkBAzwETr8HAT7DbQYNuegoPNbc031lSeWoGBVHkAAB9GMOsFNOdw6Pffy9dpaRITFCQfd+okDUNDPb1ZQJUIDgx0BLnlPfWuub+ap6u5vL1jYuRAdrYJinefOiW7srJkd1aWHMvLk8O5uWZan5bm3jYFBJhJKzpoSoOdN2xSHAICTLUHbQ3WPGP9samDW+gUV3hZm0oOAOAxBLMepnmG1//0k2xITzf5gss7d5bzoqM9vVmA1+b+an6tTkPr13e5jAa6GtTaAa6mOuiw0DoddbrUAShsWpJMp1N6I1+LkLm2OjXV5XzN57UDW/tSJ20h1kBXJ20Fti+1jJkGyNoa7dzprjoGRiFPF4C/IZj1ED3V+uxvv8mUvXvlVEGB1A0Ols+7dJFzo6I8tUmAX9BAt1tUlJlKo628+tnTqgxZ+fkyNznZpDZofV3nS51OFaY4NAkLMxUgzJSbay718RoY79Lg+ZQJhytMi5jZlSTs4FcD5TUpKVIvJETqBQc7LuuGhJjvDefr2pLsjQigAfh9MDtjxgyZNm2aJCcnS5cuXeTFF1+UHj16lLj8+++/L3//+99l79690qZNG3n66adl6NCh4gu0Vej15GSZnZQkvxR2frm0bl2ZffbZ0sqpGD6AqqWtoNpCagZ7KEwdKG9VAe3kpvV7DxWOwmYHuOZ6To4ZwEIHlNBg11wWXtfgWXOBdd7/2ofFXNf52fn5Zr2Sm2vm/3DypFuvqXZhABxemAtcy+m6fakDa9hpFa6mkGIpF2GFVSX00tGKXJiK4dyqbD9e96uG1M6X+jr1Utud7anIbT+pTgGghgaz7777rkycOFFmzZolF1xwgTz//PMyePBg2bFjh8TGxp62/Nq1a2XkyJEydepU+cMf/iDz58+X4cOHy+bNm6Vjx47ibfSf1rfp6fJVaqp8mZIiq1JSzD8rpS0pz7ZuLaPj4vgyB3yQBmHakUynhAqU0dMWSx1RzTHyWkGBua6twXYQrAGwjtqmneW01Jleal7widxcOa6XhZ3nlFneKX3iTLx1+LBUFw16NRB+cPduE3Q7B9CO2/b1MubrpMH1urS034PmwvfJDqztefb1y+rVM6XeAp3qKbu6bi4r8bq9XQD8IJh99tlnZfz48TJ27FhzW4PaTz/9VF577TV58MEHT1v+hRdekMsuu0zuv/9+c/vxxx+X5cuXy0svvWQe622u++knWXT0aJF53SIj5db4eDNSk/4TBFBz2YNRhJkbGu6Uv86sBsSphYGtBsGa+mCnUJhLp3krU1IcwbOdK6xpT/Z1e358WJgZSMNM2lpcuIxz0O0Y+rhwXkFh+oZe/v6T3T26vEnpKAzKq9PswmHDPUFDWTuwtY+D4tftFu7irdmOwDwgwHQitlu4nVu/nVu99W9saKjLAN/VZUBp97mYbz+fOF86PbfLy8LHSQUfW133F7+vyHvo4geJy+XcWaaa1xXgxrpdreuWxo1NapM38WgklZOTI5s2bZJJkyY55gUGBsrAgQNl3bp1Lh+j87Ul15m25C5atMjl8tnZ2WaypRZ24Ehzs5fzmTpXWwhyc6V3dLT0jI6WC2Ni5Jzatc3BYZ08KdWzFSXLSk93azl39ldlrstdnnhOd5/XE89Z2c9bU57TH95T/TIvMhyG5s+6yKHNcXM447FnWOdaUzCswuBW85Ht22Zyuq73a5c7DY6vrF/fBNw5hcGz83U7qDbz7NvOwbbTcrourWes6zbPUfg8jutO26Fl2sw2FAbh+c7XC5crMs/pugncC7ffzCsM7N0N5HW56gzfE6vxueC/BusIjtWQFml/7+nntEyWBx04cMB8n6xdu7bI/Pvvv9/q0aOHy8eEhIRY8+fPLzJvxowZVmxsrMvlp0yZ4vj+ZGIfcAxwDHAMcAxwDHAMcAyIz+yD/fv3lxlP+v05bm31dW7JLSgokOPHj0v9+vX9Ll9Jf8U0a9ZM9u/fL9GU92JfcVzxGfRifF+xrziu+AyWRltk09PTJb6MNCvl0WC2QYMGEhQUJIcOHSoyX2/HxcW5fIzOL8/yYWFhZnJWp04d8WcayBLMsq84rvgM+gK+r9hXHFd8BksS4zREemk8WpQwNDRUunfvLitWrCjScqq3e/Xq5fIxOt95eaUdwEpaHgAAAP7L42kGmgIwevRoOe+880xtWS3NlZmZ6ahuMGrUKGnSpIkpxaXuuusu6devn0yfPl0uv/xyeeedd2Tjxo0yZ84cD78SAAAA1LhgdsSIEXLkyBGZPHmyGTSha9eusmTJEmnUqJG5PzEx0VQ4sPXu3dvUln344YfloYceMoMmaCUDb6wxW900nWLKlCmnpVWAfcVxxWfQ2/B9xb7iuOIzWFkCtBdYpa0NAAAAqEbeOZA3AAAA4AaCWQAAAPgsglkAAAD4LIJZAAAA+CyCWT/15JNPmsoPERERfj9IRHnNmDFDWrZsKeHh4XLBBRfIt99+6+lN8kpr1qyRK664woy+oqPladUQuKalA88//3yJioqS2NhYGT58uOzYsYPd5cLMmTOlc+fOjsEStEb44sWL2VdleOqpp8zn8O6772ZfufDII4+Y/eM8tWvXjn1VggMHDsgNN9xgRkOtVauWdOrUyZQ59VUEs34qJydH/vSnP8ntt9/u6U3xKu+++66pbawlzDZv3ixdunSRwYMHy+HDhz29aV5H6z3r/tHgH6VbvXq1TJgwQdavX28GccnNzZVBgwaZfYiimjZtagKzTZs2mX+eAwYMkGHDhsn27dvZVSXYsGGDzJ492/wIQMnOOeccOXjwoGP66quv2F0unDhxQvr06SMhISHmh+SPP/5oavfXrVtXfBWlufzcvHnzzC/5lJQUT2+KV9CWWG1Be+mllxwjzjVr1kzuvPNOefDBBz29eV5LWzkWLlxoWhxRNq2drS20GuT27duXXVaGevXqybRp0+Tmm29mXxWTkZEh5557rrz88svyxBNPmFrsOrgQTm+Z1bNHW7duZdeUQf/Xff311/Lll1+Kv6BlFjWqtVpbgwYOHOiYpwNy6O1169Z5dNvgX1JTUx1BGkqWn59vRnHUFmyGJHdNW/x1tEvn7y249uuvv5q0qLPOOkuuv/56M+gSTvfxxx+bUVf17K3+6O7WrZu88sor4ssIZlFjHD161PzztEeXs+ltHX0OqAza2q9nQ/Q0HiMTurZt2zaJjIw0o4DddtttptW/Q4cOHIDFaKCv6VD2cO4o/aybnonUEUQ1L3vPnj1y0UUXSXp6OrutmN27d5t9pCOoLl261KQj/uUvf5HXX39dfJXHh7NF+U4NPP3006Uu89NPP5H0Dni4Je2HH34gX68Ubdu2NaeDtQX7gw8+kNGjR5uUDALa/9m/f7/cddddJgdbO6uidEOGDHFc19xiDW5btGgh7733HukrLn5wa8vsP/7xD3NbW2b1O2vWrFnms+iLCGZ9yL333itjxowpdRk9vQLXGjRoIEFBQXLo0KEi8/V2XFwcuw1n7I477pBPPvnEVILQjk5wLTQ0VBISEsz17t27mw5OL7zwgunkhN9pSpR2TNV8WZueWdJjS3P+s7OzzfcZXNMqPmeffbbs3LmTXVRM48aNT/vh2L59e/nwww/FVxHM+pCGDRuaCRX/B6r/OFesWOHoyKS/UPW2BiFARVmWZToR6unyVatWSatWrdiZ5aCfQw3O8D+XXHKJScdwNnbsWHPm7a9//SuBrBsd53bt2iU33ngjh1UxmgJVvHTgL7/8YlqyfRXBrJ/SxPfjx4+bS/01b/fw1NYQzVWrqbQsl55G0VMsPXr0ML2CtfOJ/pPA6f8MnFs1NAdNjyPt1NS8eXN2V7HUgvnz58tHH31kas3aOdgxMTGmhiP+Z9KkSeaUsB5Dms+o+01/AGjuHv5Hj6PiOde1a9c2dUHJxT7dfffdZ+pia0CWlJRkyi9qy/XIkSM5rIq55557TB16TTO49tprTa31OXPmmMlnWfBLo0ePtvTtLT6tXLnSqulefPFFq3nz5lZoaKjVo0cPa/369Z7eJK+kx4qrY0iPLRTlaj/pNHfuXHZVMTfddJPVokUL8/lr2LChdckll1jLli1jP7mhX79+1l133cW+cmHEiBFW48aNzXHVpEkTc3vnzp3sqxL897//tTp27GiFhYVZ7dq1s+bMmWP5MurMAgAAwGdRmgsAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgAAAD6LYBYAAAA+i2AWAAAAPotgFgB8TEBAgCxatMjTm1GjsM8B70UwCwAe9Mgjj0jXrl099vzz5s2TOnXqlOsxCxYskEGDBkn9+vVNkLd169Yi9x8/flzuvPNOadu2rdSqVUuaN28uf/nLXyQ1NVW8naffDwDlRzALwO/k5OR4ehP8WmZmplx44YXy9NNPu7w/KSnJTM8884z88MMPJmBesmSJ3HzzzdW+rQBqAAsAyqFfv37WnXfead1///1W3bp1rUaNGllTpkwx9+3Zs8fSr5UtW7Y4lj9x4oSZt3LlSnNbL/X2kiVLrK5du1rh4eHWxRdfbB06dMj67LPPrHbt2llRUVHWyJEjrczMTLe3acKECdZdd91l1a9f3+rfv7+Zv23bNuuyyy6zateubcXGxlo33HCDdeTIEcfjMjIyrBtvvNHcHxcXZz3zzDNmXboem27rwoULizxfTEyMNXfuXMftxMRE609/+pOZr/vkyiuvNPvCpq/5/PPPtyIiIswyvXv3tvbu3WvWoet3npzXW5Li2/TAAw9Ybdq0sWrVqmW1atXKevjhh62cnBzH/Vu3bjX7JDIy0uzbc88919qwYYPjvXCe7PfSHa7e75K89957VmhoqJWbm1vmshU9Rk6dOmWOzYYNG1phYWFWnz59rG+//fa09X7++edW9+7dzf7q1auX9fPPP5v7S3s/9Porr7xiDR8+3DwuISHB+uijjxzrPn78uHXddddZDRo0MNur97/22mtu70sAFUfLLIBye/3116V27dryzTffyD//+U957LHHZPny5eU+nfvSSy/J2rVrZf/+/XLttdfK888/L/Pnz5dPP/1Uli1bJi+++GK5tik0NFS+/vprmTVrlqSkpMiAAQOkW7dusnHjRtMyeOjQIfM8tvvvv19Wr14tH330kXm+VatWyebNm8v1OnJzc2Xw4MESFRUlX375pXn+yMhIueyyy0wLcV5engwfPlz69esn33//vaxbt05uueUWc3p+xIgRcu+998o555wjBw8eNJPOKy99bm39/PHHH+WFF16QV155RZ577jnH/ddff700bdpUNmzYIJs2bZIHH3xQQkJCpHfv3mafR0dHO57/vvvuk6qgKQb6PMHBwVV2jDzwwAPy4YcfmmNB38eEhATz3mjag7O//e1vMn36dHNc6PbcdNNNZn5Z78ejjz5qtkHfx6FDh5r9aq/773//u9n/ixcvlp9++klmzpwpDRo0qIQ9B6BMZxAIA6iBtOXywgsvLDJPWx3/+te/lqtlVlvHbFOnTjXzdu3a5Zh36623WoMHD3Z7m7p161Zk3uOPP24NGjSoyLz9+/eb59mxY4eVnp5uWgq1xdB27Ngx0+pWnpbZ//znP1bbtm2tgoICx/3Z2dlmPUuXLjXr1HWsWrXK5bZrS2iXLl3cep2lbZOzadOmmZZHm7Zizps3z+Wy+jr09VSEuy2z2hrevHlz66GHHnJrvRU5RrSVPSQkxHrrrbcc92vrdHx8vPXPf/6zxPV++umnZl5WVlap74cuoy3eNn0+nbd48WJz+4orrrDGjh3r1usDULlomQVQbp07dy5yu3HjxnL48OEKr6NRo0YSEREhZ511VpF55Vln9+7di9z+7rvvZOXKlaaV1J7atWtn7tu1a5eZtOX0ggsucDymXr16ptNSeejz7Ny507SO2s+j6zl16pR5Dr0+ZswY00J4xRVXmJZTbfGrTO+++6706dNH4uLizPM//PDDkpiY6Lh/4sSJMm7cOBk4cKA89dRTZruqS1pamlx++eXSoUMH09JaVceIviZtJdf9YNPW5x49epiW0pLWq8eucudYc36cnpnQlmb7cbfffru88847pvOYthBrazKA6kEwC6DcNEhwpqfMCwoKJDDw96+U3xuyfqcBRlnr0MeXtE53aXDhLCMjwwSP2tPeefr111+lb9++bq9Xt8P59RR/Tfo8GkgXf55ffvlFrrvuOrPM3LlzTXqBntbXwPPss8+W9evXS2XQ9erpbj3t/cknn8iWLVvMaXTnTnAaRG7fvt0ElV988YUJLBcuXChVLT093aRbaKCvz1f8PS5LZR8jJa1XubOe0p5/yJAhsm/fPrnnnntM57dLLrmkylI2ABRFMAug0jRs2NBcOrc8Fi/bVF3OPfdcE8C1bNnS5E46Txr4tm7d2gQnmvdrO3HihAlCi78m59ejwfDJkyeLPI/Oi42NPe15YmJiHMtp7u6kSZNMi13Hjh1N3qfSPN/8/PwKv05dX4sWLUwAe95550mbNm1MUFWcBtAaaGme6dVXX20C7Mp4/tJaZLV8l67/448/lvDwcKlK+n7aOdPOPzo0T1iDd3edyf7QY2X06NHy5ptvmtzeOXPmVGg9AMqHYBZApdGaoj179jSnsvXUrnau0lPenjBhwgTTOWfkyJEmoNHT0EuXLpWxY8eaYEVPx2upKO0Epq2VWkJK0wHs1mWbdiLTTkja4qkdhm677bYiLXTaKqodfYYNG2Y6gO3Zs8d0JNO6qr/99pu5rUGstqBqkKnBpAa/7du3N4/XYFuX0aD/6NGjkp2dXa7XqcGrphToKW59jf/617+KtLpmZWXJHXfcYbZJn1+DPd0fzs+vrcsrVqwwz+8cqJdE96tur3Z4Ujt27DC3k5OTiwSyWsLr1VdfNbf1Pp2qInBW+gNFT/Xr+6md/XTbxo8fb15PeUqCVfT9mDx5sulIqCkn+iNKW8ntfQygahHMAqhUr732munBr6fe7777bnniiSc8sofj4+NN4KbBkwZWnTp1MtujAwTYAeu0adPkoosuMukImk+qtVOL595qr/dmzZqZ5TRtQE8da+6mTa+vWbPGDAygLZ4awGjwpDmzmlOp9//8889yzTXXmNZRrWSggfatt95qHq/z9VT8xRdfbFr23n777XK9ziuvvNK0uGrAqvma2lKrPettQUFBcuzYMRk1apR5fu2Nr6fEtWe+0tQHDdC1174+v1anKIu2tGpLs6YtqP/7v/8zt7WKhNJKAtrivW3bNtNCrXmp9qRVCaqK/ojS/XnjjTeaFnMNLPUHTN26dd1eR0XfD23R1R8tmleraSy63/UHBoCqF6C9wKrheQDAJ/Tv398EhXqaGADg/WiZBQAAgM8imAXg1TQf1Lm8VvHJuQSVP3jrrbdKfK1azL+qad5vafu7MmhaQ0nr1/sAoDxIMwDg1TT/du/evaV22CnPqFLeTstZ6UhlrmjHM61cUJW0w9iBAwdKvF9zYM+U1mbVTmGuaJ6xVoYAAHcRzAIAAMBnkWYAAAAAn0UwCwAAAJ9FMAsAAACfRTALAAAAn0UwCwAAAJ9FMAsAAACfRTALAAAA8VX/DyFV3nPsOW+8AAAAAElFTkSuQmCC", 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", 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", 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", 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", 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df_std = pd.DataFrame(StandardScaler().fit_transform(df_final[numeric_final_cols].astype(\"float64\")),\n", " columns=numeric_final_cols)\n", "\n", "for feat in numeric_final_cols: \n", " distplot(feat, df_std, color=\"c\")" ] }, { "cell_type": "code", "execution_count": 80, "id": "bb54e2c0-cb05-4b80-a294-6fe08b28f079", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.591688Z", "iopub.status.busy": "2026-03-24T17:55:12.591586Z", "iopub.status.idle": "2026-03-24T17:55:12.599325Z", "shell.execute_reply": "2026-03-24T17:55:12.598480Z", "shell.execute_reply.started": "2026-03-24T17:55:12.591680Z" } }, "outputs": [], "source": [ "scaler= StandardScaler()\n", "\n", "X_train[numeric_final_cols] = scaler.fit_transform(X_train[numeric_final_cols])\n", "X_test[numeric_final_cols] = scaler.transform(X_test[numeric_final_cols])" ] }, { "cell_type": "markdown", "id": "57b63fef-2efc-440d-86b0-925ddfc32d60", "metadata": {}, "source": [ "## Modellieren\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: \n", "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": 81, "id": "5c7e3b0f-c27c-4562-ae4a-70088b92c5aa", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.599714Z", "iopub.status.busy": "2026-03-24T17:55:12.599635Z", "iopub.status.idle": "2026-03-24T17:55:12.601621Z", "shell.execute_reply": "2026-03-24T17:55:12.601041Z", "shell.execute_reply.started": "2026-03-24T17:55:12.599707Z" } }, "outputs": [], "source": [ "# Initiere das knn-Modell\n", "knn_model = KNeighborsClassifier(n_neighbors = 11) " ] }, { "cell_type": "code", "execution_count": 82, "id": "89492ad8-b601-45b6-8ef2-0be3b2b46edd", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.602000Z", "iopub.status.busy": "2026-03-24T17:55:12.601938Z", "iopub.status.idle": "2026-03-24T17:55:12.610964Z", "shell.execute_reply": "2026-03-24T17:55:12.610410Z", "shell.execute_reply.started": "2026-03-24T17:55:12.601994Z" }, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
KNeighborsClassifier(n_neighbors=11)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ], "text/plain": [ "KNeighborsClassifier(n_neighbors=11)" ] }, "execution_count": 82, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Trainiere das Modell mit unseren Trainingsdaten\n", "knn_model.fit(X_train,y_train)" ] }, { "cell_type": "code", "execution_count": 83, "id": "28bd4a9d-7abf-4f80-960e-bb22ec3c0ed8", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.611464Z", "iopub.status.busy": "2026-03-24T17:55:12.611378Z", "iopub.status.idle": "2026-03-24T17:55:12.685722Z", "shell.execute_reply": "2026-03-24T17:55:12.684787Z", "shell.execute_reply.started": "2026-03-24T17:55:12.611455Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "KNN accuracy: 0.7663507109004739\n", "0.7663507109004739\n" ] } ], "source": [ "# die \"score\"-Funktion scoret direkt die predicted Resultate vom X_test gegen die wahren y-Werte und gibt die Accuracy zurück\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": 84, "id": "7f2c2134-76de-4727-8f77-84ffc7e9109d", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.686572Z", "iopub.status.busy": "2026-03-24T17:55:12.686444Z", "iopub.status.idle": "2026-03-24T17:55:12.713080Z", "shell.execute_reply": "2026-03-24T17:55:12.712411Z", "shell.execute_reply.started": "2026-03-24T17:55:12.686556Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Precision for class 0: 0.8102232667450059, precision for class 1: 0.5833333333333334\n", "Recall for class 0: 0.8902517753389283, recall for class 1: 0.42424242424242425\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", "y_pred = knn_model.predict(X_test)\n", "\n", "prec = precision_score(y_test, y_pred, average=None)\n", "recall = recall_score(y_test, y_pred, average=None)\n", "\n", "print(f\"Precision for class 0: {prec[0]}, precision for class 1: {prec[1]}\")\n", "print(f\"Recall for class 0: {recall[0]}, recall for class 1: {recall[1]}\")" ] }, { "cell_type": "code", "execution_count": 85, "id": "37e4f2fb-f155-4f6f-a4c3-7af510128705", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.713670Z", "iopub.status.busy": "2026-03-24T17:55:12.713587Z", "iopub.status.idle": "2026-03-24T17:55:12.718274Z", "shell.execute_reply": "2026-03-24T17:55:12.717767Z", "shell.execute_reply.started": "2026-03-24T17:55:12.713662Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.5833333333333334\n", "0.42424242424242425\n" ] } ], "source": [ "prec = precision_score(y_test, y_pred, pos_label=1)\n", "print(prec)\n", "recall = recall_score(y_test, y_pred, pos_label=1)\n", "print(recall)" ] }, { "cell_type": "code", "execution_count": 86, "id": "eb46e2b3-c122-4dd4-815a-6697c24372f5", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.718616Z", "iopub.status.busy": "2026-03-24T17:55:12.718546Z", "iopub.status.idle": "2026-03-24T17:55:12.724027Z", "shell.execute_reply": "2026-03-24T17:55:12.723197Z", "shell.execute_reply.started": "2026-03-24T17:55:12.718609Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 0 0.81 0.89 0.85 1549\n", " 1 0.58 0.42 0.49 561\n", "\n", " accuracy 0.77 2110\n", " macro avg 0.70 0.66 0.67 2110\n", "weighted avg 0.75 0.77 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": "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": 87, "id": "ac8f8724-20a1-4d5b-901b-453ea35d8cfd", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.724755Z", "iopub.status.busy": "2026-03-24T17:55:12.724667Z", "iopub.status.idle": "2026-03-24T17:55:12.742504Z", "shell.execute_reply": "2026-03-24T17:55:12.741747Z", "shell.execute_reply.started": "2026-03-24T17:55:12.724746Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Logistic Regression accuracy is : 0.7943127962085308\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": 88, "id": "7deda99d-1526-4eaa-b3ec-e7b8c0d4f31e", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.743270Z", "iopub.status.busy": "2026-03-24T17:55:12.743173Z", "iopub.status.idle": "2026-03-24T17:55:12.753762Z", "shell.execute_reply": "2026-03-24T17:55:12.753200Z", "shell.execute_reply.started": "2026-03-24T17:55:12.743262Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 0 0.83 0.90 0.86 1549\n", " 1 0.64 0.51 0.57 561\n", "\n", " accuracy 0.79 2110\n", " macro avg 0.74 0.70 0.72 2110\n", "weighted avg 0.78 0.79 0.79 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": 89, "id": "51f483f4-da43-4314-8e77-cc7fb247b329", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.754162Z", "iopub.status.busy": "2026-03-24T17:55:12.754085Z", "iopub.status.idle": "2026-03-24T17:55:12.801042Z", "shell.execute_reply": "2026-03-24T17:55:12.800441Z", "shell.execute_reply.started": "2026-03-24T17:55:12.754154Z" } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "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": 90, "id": "b984849b-5817-459e-893e-95ee262b098c", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.801617Z", "iopub.status.busy": "2026-03-24T17:55:12.801529Z", "iopub.status.idle": "2026-03-24T17:55:12.836414Z", "shell.execute_reply": "2026-03-24T17:55:12.835874Z", "shell.execute_reply.started": "2026-03-24T17:55:12.801609Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Decision Tree accuracy is : 0.7161137440758294\n" ] } ], "source": [ "dt_model = DecisionTreeClassifier()\n", "dt_model.fit(X_train,y_train)\n", "y_pred = 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": 91, "id": "7e68f5a1-5f03-44f3-8b61-3e0ac7c5dd78", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.836942Z", "iopub.status.busy": "2026-03-24T17:55:12.836851Z", "iopub.status.idle": "2026-03-24T17:55:12.843025Z", "shell.execute_reply": "2026-03-24T17:55:12.842558Z", "shell.execute_reply.started": "2026-03-24T17:55:12.836934Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 0 0.81 0.80 0.80 1549\n", " 1 0.47 0.50 0.48 561\n", "\n", " accuracy 0.72 2110\n", " macro avg 0.64 0.65 0.64 2110\n", "weighted avg 0.72 0.72 0.72 2110\n", "\n" ] } ], "source": [ "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "markdown", "id": "57133593-2f9f-4423-a495-7346a1a779d7", "metadata": {}, "source": [ "### AdaBoost Classifier" ] }, { "cell_type": "code", "execution_count": 92, "id": "a7d0fad2-bc33-4c2b-8e30-6778640e5b4b", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:12.843555Z", "iopub.status.busy": "2026-03-24T17:55:12.843483Z", "iopub.status.idle": "2026-03-24T17:55:13.039065Z", "shell.execute_reply": "2026-03-24T17:55:13.038639Z", "shell.execute_reply.started": "2026-03-24T17:55:12.843548Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "AdaBoost Classifier accuracy\n" ] }, { "data": { "text/plain": [ "0.7924170616113744" ] }, "execution_count": 92, "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": 93, "id": "169efc97-29ef-4ddd-960f-f9e913ae70a8", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:13.039723Z", "iopub.status.busy": "2026-03-24T17:55:13.039630Z", "iopub.status.idle": "2026-03-24T17:55:13.046037Z", "shell.execute_reply": "2026-03-24T17:55:13.045550Z", "shell.execute_reply.started": "2026-03-24T17:55:13.039714Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 0 0.83 0.90 0.86 1549\n", " 1 0.64 0.49 0.56 561\n", "\n", " accuracy 0.79 2110\n", " macro avg 0.74 0.70 0.71 2110\n", "weighted avg 0.78 0.79 0.78 2110\n", "\n" ] } ], "source": [ "print(classification_report(y_test, a_preds))" ] }, { "cell_type": "code", "execution_count": 94, "id": "7bb2a523-487e-4d4d-a116-f02a0302540e", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:13.047629Z", "iopub.status.busy": "2026-03-24T17:55:13.047168Z", "iopub.status.idle": "2026-03-24T17:55:13.090616Z", "shell.execute_reply": "2026-03-24T17:55:13.089902Z", "shell.execute_reply.started": "2026-03-24T17:55:13.047621Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "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": 95, "id": "a2e8910d-b6f1-44d7-940c-752c0d762ff5", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:13.091291Z", "iopub.status.busy": "2026-03-24T17:55:13.090982Z", "iopub.status.idle": "2026-03-24T17:55:13.850013Z", "shell.execute_reply": "2026-03-24T17:55:13.849533Z", "shell.execute_reply.started": "2026-03-24T17:55:13.091282Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Gradient Boosting Classifier 0.790521327014218\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": 96, "id": "520bc7a9-82e9-429c-b8fa-2e0b86f360ce", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:13.850516Z", "iopub.status.busy": "2026-03-24T17:55:13.850410Z", "iopub.status.idle": "2026-03-24T17:55:13.856545Z", "shell.execute_reply": "2026-03-24T17:55:13.856013Z", "shell.execute_reply.started": "2026-03-24T17:55:13.850507Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 0 0.83 0.90 0.86 1549\n", " 1 0.64 0.49 0.56 561\n", "\n", " accuracy 0.79 2110\n", " macro avg 0.73 0.70 0.71 2110\n", "weighted avg 0.78 0.79 0.78 2110\n", "\n" ] } ], "source": [ "print(classification_report(y_test, gb_pred))" ] }, { "cell_type": "code", "execution_count": 97, "id": "c80a6983-cd60-48a3-a15b-d319a8e65e99", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:13.857527Z", "iopub.status.busy": "2026-03-24T17:55:13.857433Z", "iopub.status.idle": "2026-03-24T17:55:13.899784Z", "shell.execute_reply": "2026-03-24T17:55:13.899358Z", "shell.execute_reply.started": "2026-03-24T17:55:13.857519Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "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": 98, "id": "0e83a4da-50b9-4600-8b89-a2dd377f5c6b", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:13.900200Z", "iopub.status.busy": "2026-03-24T17:55:13.900124Z", "iopub.status.idle": "2026-03-24T17:55:14.846449Z", "shell.execute_reply": "2026-03-24T17:55:14.845653Z", "shell.execute_reply.started": "2026-03-24T17:55:13.900193Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Final Accuracy Score \n", "0.7933649289099526\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": 99, "id": "625e01ae-4164-4d6f-92fe-b623af867b15", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:14.847488Z", "iopub.status.busy": "2026-03-24T17:55:14.847355Z", "iopub.status.idle": "2026-03-24T17:55:14.852417Z", "shell.execute_reply": "2026-03-24T17:55:14.851999Z", "shell.execute_reply.started": "2026-03-24T17:55:14.847480Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 0 0.83 0.90 0.86 1549\n", " 1 0.64 0.50 0.56 561\n", "\n", " accuracy 0.79 2110\n", " macro avg 0.74 0.70 0.71 2110\n", "weighted avg 0.78 0.79 0.78 2110\n", "\n" ] } ], "source": [ "print(classification_report(y_test, predictions))" ] }, { "cell_type": "code", "execution_count": 100, "id": "f6bc6e7c-7a6a-41f8-b557-60b8828ac760", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:14.852771Z", "iopub.status.busy": "2026-03-24T17:55:14.852699Z", "iopub.status.idle": "2026-03-24T17:55:14.895659Z", "shell.execute_reply": "2026-03-24T17:55:14.895103Z", "shell.execute_reply.started": "2026-03-24T17:55:14.852764Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "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()" ] }, { "cell_type": "markdown", "id": "bbe9ba74-0001-49ef-bbc6-71d8ec8051e9", "metadata": {}, "source": [ "## Cross Validation Example! \n", "\n", "### Anhand eines einfachen Decision Trees\n" ] }, { "cell_type": "code", "execution_count": 101, "id": "d60e4633-ebe3-4b31-8fc7-9c8d1080d0cf", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:14.896497Z", "iopub.status.busy": "2026-03-24T17:55:14.896348Z", "iopub.status.idle": "2026-03-24T17:55:14.898531Z", "shell.execute_reply": "2026-03-24T17:55:14.898136Z", "shell.execute_reply.started": "2026-03-24T17:55:14.896487Z" } }, "outputs": [], "source": [ "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.model_selection import KFold, cross_validate\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 102, "id": "de3c714a-2e0b-4cfd-bd5f-82e15df72114", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:14.898881Z", "iopub.status.busy": "2026-03-24T17:55:14.898818Z", "iopub.status.idle": "2026-03-24T17:55:14.903722Z", "shell.execute_reply": "2026-03-24T17:55:14.903448Z", "shell.execute_reply.started": "2026-03-24T17:55:14.898874Z" } }, "outputs": [ { "data": { "text/html": [ "
DecisionTreeClassifier()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ], "text/plain": [ "DecisionTreeClassifier()" ] }, "execution_count": 102, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Annahme: X und y beinhalten jeweils deine Feature-Matrix und Zielvariable (Churn als 0/1)\n", "\n", "dt_model = DecisionTreeClassifier()\n", "dt_model" ] }, { "cell_type": "markdown", "id": "cf00fd6b-8749-4570-92d1-91375c36261e", "metadata": {}, "source": [ "#### Wähle k=10 für 10-fold Cross-Validation\n" ] }, { "cell_type": "code", "execution_count": 103, "id": "09f9eac6-566e-41e1-9826-f6f330051d2a", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:14.904161Z", "iopub.status.busy": "2026-03-24T17:55:14.904098Z", "iopub.status.idle": "2026-03-24T17:55:14.907589Z", "shell.execute_reply": "2026-03-24T17:55:14.906461Z", "shell.execute_reply.started": "2026-03-24T17:55:14.904155Z" } }, "outputs": [ { "data": { "text/plain": [ "KFold(n_splits=10, random_state=42, shuffle=True)" ] }, "execution_count": 103, "metadata": {}, "output_type": "execute_result" } ], "source": [ "k = 10\n", "kf = KFold(n_splits=k, shuffle=True, random_state=42)\n", "kf" ] }, { "cell_type": "markdown", "id": "e820817b-67de-4096-b14f-2523e30baa5a", "metadata": {}, "source": [ "#### Verwende cross_validate, um sowohl Trainings- als auch Validierungsscores zu erhalten\n" ] }, { "cell_type": "code", "execution_count": 104, "id": "168774d8-f6ea-4964-93b9-0196183b5874", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:14.908010Z", "iopub.status.busy": "2026-03-24T17:55:14.907940Z", "iopub.status.idle": "2026-03-24T17:55:15.319002Z", "shell.execute_reply": "2026-03-24T17:55:15.318437Z", "shell.execute_reply.started": "2026-03-24T17:55:14.908003Z" } }, "outputs": [ { "data": { "text/plain": [ "{'fit_time': array([0.03874516, 0.04276395, 0.03619814, 0.03640604, 0.0356729 ,\n", " 0.03642106, 0.03842902, 0.03649712, 0.036309 , 0.03726411]),\n", " 'score_time': array([0.00107479, 0.00114584, 0.00121593, 0.00115991, 0.00108218,\n", " 0.00104594, 0.00105691, 0.00105095, 0.0015471 , 0.00119972]),\n", " 'test_score': array([0.73579545, 0.68892045, 0.7254623 , 0.74253201, 0.70981508,\n", " 0.70981508, 0.7254623 , 0.68421053, 0.69274538, 0.7254623 ]),\n", " 'train_score': array([0.99968394, 0.99984197, 0.999842 , 0.99968399, 0.999842 ,\n", " 0.99968399, 0.99968399, 0.99968399, 0.99968399, 0.99968399])}" ] }, "execution_count": 104, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cv_results = cross_validate(dt_model, X, y, cv=kf, return_train_score=True)\n", "cv_results" ] }, { "cell_type": "markdown", "id": "ba687cce-590b-400e-9a00-0db8a40a68d3", "metadata": {}, "source": [ "#### Logge die Ergebnisse jeder einzelnen Fold\n" ] }, { "cell_type": "code", "execution_count": 105, "id": "6a0050b5-324b-4bdb-9f0b-ee9760eb0fd4", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:15.319487Z", "iopub.status.busy": "2026-03-24T17:55:15.319395Z", "iopub.status.idle": "2026-03-24T17:55:15.321751Z", "shell.execute_reply": "2026-03-24T17:55:15.321228Z", "shell.execute_reply.started": "2026-03-24T17:55:15.319479Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Trainings-Scores pro Fold:\n", "[0.99968394 0.99984197 0.999842 0.99968399 0.999842 0.99968399\n", " 0.99968399 0.99968399 0.99968399 0.99968399]\n" ] } ], "source": [ "print(\"Trainings-Scores pro Fold:\")\n", "print(cv_results[\"train_score\"])" ] }, { "cell_type": "code", "execution_count": 106, "id": "6c4906a3-c8e0-4b58-b7ec-6eed75680f47", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:15.322052Z", "iopub.status.busy": "2026-03-24T17:55:15.321977Z", "iopub.status.idle": "2026-03-24T17:55:15.324586Z", "shell.execute_reply": "2026-03-24T17:55:15.324060Z", "shell.execute_reply.started": "2026-03-24T17:55:15.322045Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Validierungs-Scores pro Fold:\n", "[0.73579545 0.68892045 0.7254623 0.74253201 0.70981508 0.70981508\n", " 0.7254623 0.68421053 0.69274538 0.7254623 ]\n" ] } ], "source": [ "print(\"Validierungs-Scores pro Fold:\")\n", "print(cv_results[\"test_score\"])" ] }, { "cell_type": "code", "execution_count": 107, "id": "8eab1dfb-0774-4760-9aa4-714862f797fd", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:15.325026Z", "iopub.status.busy": "2026-03-24T17:55:15.324953Z", "iopub.status.idle": "2026-03-24T17:55:15.328052Z", "shell.execute_reply": "2026-03-24T17:55:15.327533Z", "shell.execute_reply.started": "2026-03-24T17:55:15.325019Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Durchschnittlicher Validierungs-Score:\n", "0.7140220887753783\n" ] } ], "source": [ "print(\"Durchschnittlicher Validierungs-Score:\")\n", "print(np.mean(cv_results[\"test_score\"]))" ] }, { "cell_type": "markdown", "id": "0ea8ee45-efab-4daa-9751-4db619a0e267", "metadata": {}, "source": [ "### Next Step\n", "Falls es sich hierbei um ein sehr einfaches Modell handelt ohne jegliche Parameter (z.B. linear Regression oder logistic Regression), könnte man nun das Modell mit dem besten Validierungs-Score extrahieren. \n", "\n", "### Cross-Validation\n", "teilt die Daten auf und trainiert/evaluiert das Modell mehrfach (k-fach).\n", "\n", "### Komplexere Modelle?\n", "\n", "Wenn es sich um ein komplexeres Modell mit Hyperparameter handelt, kann sie helfen für das jeweilge Set an Hyperparameter eine robuste Performance-Metrik zu erhalten – sie ändert aber nicht selbst die Hyperparameter." ] }, { "cell_type": "markdown", "id": "9c1f5a1b-500b-460f-93c6-4d430290f56d", "metadata": {}, "source": [ "### Hyperparameter-Tuning (z. B. mit GridSearchCV)" ] }, { "cell_type": "markdown", "id": "ce9016f9-adaf-4164-8a66-0d5d8dd6e93b", "metadata": {}, "source": [ "**Hyperparameter-Tuning** (z. B. mit GridSearchCV) verwendet **CV (Cross-Validation)**, um verschiedene Hyperparameter-Kombinationen zu vergleichen, und wählt so die optimale Konfiguration." ] }, { "cell_type": "code", "execution_count": 108, "id": "6c91a3a8-f51a-40b2-9135-918092b1a6ab", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:15.328567Z", "iopub.status.busy": "2026-03-24T17:55:15.328470Z", "iopub.status.idle": "2026-03-24T17:55:15.330601Z", "shell.execute_reply": "2026-03-24T17:55:15.329995Z", "shell.execute_reply.started": "2026-03-24T17:55:15.328559Z" } }, "outputs": [], "source": [ "# Beispiel anhand Decision Tree\n", "\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.model_selection import GridSearchCV" ] }, { "cell_type": "code", "execution_count": 109, "id": "733cfda8-fc90-4aa0-8da7-dd20b7370f66", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:15.331654Z", "iopub.status.busy": "2026-03-24T17:55:15.331581Z", "iopub.status.idle": "2026-03-24T17:55:15.334093Z", "shell.execute_reply": "2026-03-24T17:55:15.333637Z", "shell.execute_reply.started": "2026-03-24T17:55:15.331646Z" } }, "outputs": [ { "data": { "text/plain": [ "{'max_depth': [None, 3, 5, 10, 20], 'min_samples_split': [2, 5, 10]}" ] }, "execution_count": 109, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Definiere den Parameterbereich\n", "param_grid = {\n", " \"max_depth\": [None, 3, 5, 10, 20], # default=None \n", " \"min_samples_split\": [2, 5, 10] # default=2, notwendige Anzahl an data points in einem Knoten, fürs weitere Teilen dieses Knoten\n", "}\n", "param_grid" ] }, { "cell_type": "code", "execution_count": 110, "id": "7909963c-8563-4b72-bafd-beabddd0b7f5", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:15.334435Z", "iopub.status.busy": "2026-03-24T17:55:15.334367Z", "iopub.status.idle": "2026-03-24T17:55:19.740659Z", "shell.execute_reply": "2026-03-24T17:55:19.739218Z", "shell.execute_reply.started": "2026-03-24T17:55:15.334428Z" } }, "outputs": [ { "data": { "text/html": [ "
GridSearchCV(cv=10, estimator=DecisionTreeClassifier(),\n",
       "             param_grid={'max_depth': [None, 3, 5, 10, 20],\n",
       "                         'min_samples_split': [2, 5, 10]},\n",
       "             return_train_score=True)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ], "text/plain": [ "GridSearchCV(cv=10, estimator=DecisionTreeClassifier(),\n", " param_grid={'max_depth': [None, 3, 5, 10, 20],\n", " 'min_samples_split': [2, 5, 10]},\n", " return_train_score=True)" ] }, "execution_count": 110, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# GridSearchCV kombiniert CV mit dem Hyperparameter-Tuning\n", "grid_search = GridSearchCV(DecisionTreeClassifier(), param_grid, cv=10, return_train_score=True)\n", "grid_search.fit(X, y)" ] }, { "cell_type": "code", "execution_count": 111, "id": "565e3c68-ebcf-4098-9959-7d17075f7d66", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:19.741462Z", "iopub.status.busy": "2026-03-24T17:55:19.741211Z", "iopub.status.idle": "2026-03-24T17:55:19.743942Z", "shell.execute_reply": "2026-03-24T17:55:19.743386Z", "shell.execute_reply.started": "2026-03-24T17:55:19.741452Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Beste Parameter: {'max_depth': 5, 'min_samples_split': 10}\n", "Bester CV-Score: 0.7912374321091427\n" ] } ], "source": [ "# Beste Parameter und entsprechender Score\n", "print(\"Beste Parameter:\", grid_search.best_params_)\n", "print(\"Bester CV-Score:\", grid_search.best_score_)" ] }, { "cell_type": "code", "execution_count": 112, "id": "9928926f-1f23-40eb-ba85-1323e5eec01a", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:19.744397Z", "iopub.status.busy": "2026-03-24T17:55:19.744326Z", "iopub.status.idle": "2026-03-24T17:55:19.746335Z", "shell.execute_reply": "2026-03-24T17:55:19.745703Z", "shell.execute_reply.started": "2026-03-24T17:55:19.744390Z" } }, "outputs": [], "source": [ "# Das finale Modell (trainiert auf den gesamten Daten mit den besten Parametern)\n", "best_model = grid_search.best_estimator_" ] }, { "cell_type": "code", "execution_count": 113, "id": "a845e51f-63b3-4e10-921e-df2dea4bf60b", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:19.748513Z", "iopub.status.busy": "2026-03-24T17:55:19.748283Z", "iopub.status.idle": "2026-03-24T17:55:19.753639Z", "shell.execute_reply": "2026-03-24T17:55:19.753293Z", "shell.execute_reply.started": "2026-03-24T17:55:19.748472Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.7341232227488151\n", "0.0\n", "0.0\n" ] } ], "source": [ "y_pred_best = best_model.predict(X_test)\n", "\n", "\n", "acc_best = accuracy_score(y_test, y_pred_best)\n", "print(acc_best)\n", "\n", "prec_best = precision_score(y_test, y_pred_best, pos_label=1)\n", "print(prec_best)\n", "\n", "recall_best = recall_score(y_test, y_pred_best, pos_label=1)\n", "print(recall_best)" ] }, { "cell_type": "code", "execution_count": 114, "id": "fecad5c4-4034-4236-b78b-d2adee75f20b", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:19.754100Z", "iopub.status.busy": "2026-03-24T17:55:19.754039Z", "iopub.status.idle": "2026-03-24T17:55:19.757563Z", "shell.execute_reply": "2026-03-24T17:55:19.756377Z", "shell.execute_reply.started": "2026-03-24T17:55:19.754093Z" } }, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 114, "metadata": {}, "output_type": "execute_result" } ], "source": [ "1 in y_test" ] }, { "cell_type": "code", "execution_count": 115, "id": "11817362-5ffa-47db-9d23-b7350ceb0412", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:19.757852Z", "iopub.status.busy": "2026-03-24T17:55:19.757794Z", "iopub.status.idle": "2026-03-24T17:55:19.760433Z", "shell.execute_reply": "2026-03-24T17:55:19.759989Z", "shell.execute_reply.started": "2026-03-24T17:55:19.757846Z" } }, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 115, "metadata": {}, "output_type": "execute_result" } ], "source": [ "1 in y_pred" ] }, { "cell_type": "code", "execution_count": 116, "id": "e86cea41-d2c6-4ede-92d7-9dfc5e1d8d84", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:19.760853Z", "iopub.status.busy": "2026-03-24T17:55:19.760758Z", "iopub.status.idle": "2026-03-24T17:55:19.763315Z", "shell.execute_reply": "2026-03-24T17:55:19.762928Z", "shell.execute_reply.started": "2026-03-24T17:55:19.760844Z" } }, "outputs": [ { "data": { "text/plain": [ "array([0, 0, 0, ..., 0, 0, 0], shape=(2110,))" ] }, "execution_count": 116, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y_test" ] }, { "cell_type": "code", "execution_count": 117, "id": "7a06b3e2-dcf3-4da7-a303-a191b3df0750", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:19.763808Z", "iopub.status.busy": "2026-03-24T17:55:19.763746Z", "iopub.status.idle": "2026-03-24T17:55:19.766273Z", "shell.execute_reply": "2026-03-24T17:55:19.765772Z", "shell.execute_reply.started": "2026-03-24T17:55:19.763802Z" } }, "outputs": [ { "data": { "text/plain": [ "array([0, 0, 0, ..., 0, 0, 0], shape=(2110,))" ] }, "execution_count": 117, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y_pred" ] }, { "cell_type": "markdown", "id": "3ac3197e-438d-4918-9f4c-4d8d38bbdd99", "metadata": {}, "source": [ "### Accuracy wurde genutzt - was wenn wir precision nutzen wollen?" ] }, { "cell_type": "code", "execution_count": 118, "id": "62e23626-e8c3-4db9-aa29-e3549768f710", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:19.766758Z", "iopub.status.busy": "2026-03-24T17:55:19.766693Z", "iopub.status.idle": "2026-03-24T17:55:24.034295Z", "shell.execute_reply": "2026-03-24T17:55:24.033664Z", "shell.execute_reply.started": "2026-03-24T17:55:19.766751Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Beste Parameter: {'max_depth': 5, 'min_samples_split': 10}\n", "Bester CV-Precision-Score: 0.6664281647925435\n" ] } ], "source": [ "from sklearn.model_selection import GridSearchCV\n", "from sklearn.tree import DecisionTreeClassifier\n", "\n", "param_grid = {\"max_depth\": [None, 3, 5, 10, 20],\n", " \"min_samples_split\": [2, 5, 10]}\n", "\n", "grid_search = GridSearchCV(DecisionTreeClassifier(), param_grid, \n", " cv=10, scoring=\"precision\", refit=True)\n", "grid_search.fit(X, y)\n", "\n", "print(\"Beste Parameter:\", grid_search.best_params_)\n", "print(\"Bester CV-Precision-Score:\", grid_search.best_score_)\n", "best_model = grid_search.best_estimator_" ] }, { "cell_type": "code", "execution_count": 119, "id": "fb53f4ca-7fcf-492b-8202-da6f045d19ea", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:24.034846Z", "iopub.status.busy": "2026-03-24T17:55:24.034677Z", "iopub.status.idle": "2026-03-24T17:55:24.040339Z", "shell.execute_reply": "2026-03-24T17:55:24.039955Z", "shell.execute_reply.started": "2026-03-24T17:55:24.034837Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.7341232227488151\n", "0.0\n", "0.0\n" ] } ], "source": [ "y_pred_best = best_model.predict(X_test)\n", "\n", "\n", "acc_best = accuracy_score(y_test, y_pred_best)\n", "print(acc_best)\n", "\n", "prec_best = precision_score(y_test, y_pred_best, pos_label=1)\n", "print(prec_best)\n", "\n", "recall_best = recall_score(y_test, y_pred_best, pos_label=1)\n", "print(recall_best)" ] }, { "cell_type": "markdown", "id": "44c03755-ac00-4982-95c1-a9eb57c0a35f", "metadata": {}, "source": [ "### Können wir mehrere Metriken gleichzeitig überwachen?" ] }, { "cell_type": "code", "execution_count": 120, "id": "87705aa9-ded9-476b-8bba-5944267f33c7", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:24.041030Z", "iopub.status.busy": "2026-03-24T17:55:24.040950Z", "iopub.status.idle": "2026-03-24T17:55:28.169341Z", "shell.execute_reply": "2026-03-24T17:55:28.168796Z", "shell.execute_reply.started": "2026-03-24T17:55:24.041022Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Beste Parameter: {'max_depth': 5, 'min_samples_split': 10}\n", "Bester CV-Precision-Score: 0.6670314466458254\n", "Params: {'max_depth': None, 'min_samples_split': 2} - Mean Precision: 0.4795\n", "Params: {'max_depth': None, 'min_samples_split': 5} - Mean Precision: 0.4939\n", "Params: {'max_depth': None, 'min_samples_split': 10} - Mean Precision: 0.5079\n", "Params: {'max_depth': 3, 'min_samples_split': 2} - Mean Precision: 0.6475\n", "Params: {'max_depth': 3, 'min_samples_split': 5} - Mean Precision: 0.6475\n", "Params: {'max_depth': 3, 'min_samples_split': 10} - Mean Precision: 0.6475\n", "Params: {'max_depth': 5, 'min_samples_split': 2} - Mean Precision: 0.6660\n", "Params: {'max_depth': 5, 'min_samples_split': 5} - Mean Precision: 0.6656\n", "Params: {'max_depth': 5, 'min_samples_split': 10} - Mean Precision: 0.6670\n", "Params: {'max_depth': 10, 'min_samples_split': 2} - Mean Precision: 0.5477\n", "Params: {'max_depth': 10, 'min_samples_split': 5} - Mean Precision: 0.5497\n", "Params: {'max_depth': 10, 'min_samples_split': 10} - Mean Precision: 0.5505\n", "Params: {'max_depth': 20, 'min_samples_split': 2} - Mean Precision: 0.4877\n", "Params: {'max_depth': 20, 'min_samples_split': 5} - Mean Precision: 0.4937\n", "Params: {'max_depth': 20, 'min_samples_split': 10} - Mean Precision: 0.5072\n" ] } ], "source": [ "from sklearn.metrics import make_scorer, precision_score, recall_score\n", "from sklearn.model_selection import GridSearchCV\n", "from sklearn.tree import DecisionTreeClassifier\n", "\n", "param_grid = {\"max_depth\": [None, 3, 5, 10, 20],\n", " \"min_samples_split\": [2, 5, 10]}\n", "\n", "scoring = {\n", " \"precision\": make_scorer(precision_score, pos_label=1),\n", " \"recall\": make_scorer(recall_score, pos_label=1)\n", "}\n", "\n", "grid_search = GridSearchCV(DecisionTreeClassifier(), param_grid, \n", " cv=10, scoring=scoring, refit=\"precision\") # refit='precision' lässt das finale Modell auf den besten Precision-Score ausgewählen.\n", "grid_search.fit(X, y)\n", "\n", "# Es werden alle Scores zurückgegeben:\n", "cv_results = grid_search.cv_results_\n", "print(\"Beste Parameter:\", grid_search.best_params_)\n", "print(\"Bester CV-Precision-Score:\", grid_search.best_score_)\n", "\n", "# Die Ergebnisse aller Folds (z.B. Precision und Recall) kannst du so ausgeben:\n", "for mean_score, params in zip(cv_results[\"mean_test_precision\"], cv_results[\"params\"]):\n", " print(f\"Params: {params} - Mean Precision: {mean_score:.4f}\")\n", "\n", "best_model = grid_search.best_estimator_" ] }, { "cell_type": "code", "execution_count": 121, "id": "14f62216-c924-41a9-b26f-1eb68f3ab5d9", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:28.169910Z", "iopub.status.busy": "2026-03-24T17:55:28.169804Z", "iopub.status.idle": "2026-03-24T17:55:28.175507Z", "shell.execute_reply": "2026-03-24T17:55:28.175047Z", "shell.execute_reply.started": "2026-03-24T17:55:28.169902Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.7341232227488151\n", "0.0\n", "0.0\n" ] } ], "source": [ "y_pred_best = best_model.predict(X_test)\n", "\n", "\n", "acc_best = accuracy_score(y_test, y_pred_best)\n", "print(acc_best)\n", "\n", "prec_best = precision_score(y_test, y_pred_best, pos_label=1)\n", "print(prec_best)\n", "\n", "recall_best = recall_score(y_test, y_pred_best, pos_label=1)\n", "print(recall_best)" ] }, { "cell_type": "markdown", "id": "c9bd2b4f-8369-4a8e-b575-2d7d2e616a08", "metadata": {}, "source": [ "### Vorhergesagte Wahrscheinlichkeit (anstatt der zugeteilten Klasse)\n", "\n", "Viele Klassifikationsmodelle in scikit-learn bieten die Methode predict_proba(), mit der wir die Wahrscheinlichkeit für jeden Datenpunkt und jede Klasse abrufen können. \n", "\n", "Bei einem binären Klassifikationsmodell liefert predict_proba() ein Array der Form (n_samples, 2), wobei die zweite Spalte (Index 1) die Wahrscheinlichkeit für Klasse 1 enthält.\n" ] }, { "cell_type": "code", "execution_count": 122, "id": "cb210e39-9cfb-480b-a581-bb6b2cbda4b9", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:28.175887Z", "iopub.status.busy": "2026-03-24T17:55:28.175802Z", "iopub.status.idle": "2026-03-24T17:55:28.179462Z", "shell.execute_reply": "2026-03-24T17:55:28.178834Z", "shell.execute_reply.started": "2026-03-24T17:55:28.175879Z" } }, "outputs": [ { "data": { "text/plain": [ "array([[0.65269461, 0.34730539],\n", " [0.65269461, 0.34730539],\n", " [0.65269461, 0.34730539],\n", " ...,\n", " [0.65269461, 0.34730539],\n", " [0.65269461, 0.34730539],\n", " [0.65269461, 0.34730539]], shape=(2110, 2))" ] }, "execution_count": 122, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Hole die Wahrscheinlichkeiten für den Testdatensatz\n", "y_prob = best_model.predict_proba(X_test)\n", "y_prob" ] }, { "cell_type": "code", "execution_count": 123, "id": "b59fec69-1749-42d9-80e3-b0dfb27ec21b", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:28.179828Z", "iopub.status.busy": "2026-03-24T17:55:28.179750Z", "iopub.status.idle": "2026-03-24T17:55:28.183133Z", "shell.execute_reply": "2026-03-24T17:55:28.182664Z", "shell.execute_reply.started": "2026-03-24T17:55:28.179821Z" } }, "outputs": [ { "data": { "text/plain": [ "array([0.34730539, 0.34730539, 0.34730539, ..., 0.34730539, 0.34730539,\n", " 0.34730539], shape=(2110,))" ] }, "execution_count": 123, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Extrahiere die Wahrscheinlichkeit für Klasse 1\n", "y_prob_class1 = y_prob[:, 1]\n", "y_prob_class1" ] }, { "cell_type": "code", "execution_count": 124, "id": "634aae87-a2f7-4614-bc9a-b8b4faee62bc", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:28.183538Z", "iopub.status.busy": "2026-03-24T17:55:28.183451Z", "iopub.status.idle": "2026-03-24T17:55:28.185428Z", "shell.execute_reply": "2026-03-24T17:55:28.184937Z", "shell.execute_reply.started": "2026-03-24T17:55:28.183530Z" } }, "outputs": [], "source": [ "# Definiere einen eigenen Schwellenwert (Threshold)\n", "threshold = 0.3 # Beispiel: 30% statt des üblichen 0.5\n", "\n", "# Wende den Threshold an: Werte >= threshold werden als 1 klassifiziert, ansonsten als 0.\n", "y_pred_custom = (y_prob_class1 >= threshold).astype(int)" ] }, { "cell_type": "code", "execution_count": 125, "id": "221c8eda-e827-4c9d-9074-edc1957daa25", "metadata": { "execution": { "iopub.execute_input": "2026-03-24T17:55:28.185775Z", "iopub.status.busy": "2026-03-24T17:55:28.185693Z", "iopub.status.idle": "2026-03-24T17:55:28.190320Z", "shell.execute_reply": "2026-03-24T17:55:28.189801Z", "shell.execute_reply.started": "2026-03-24T17:55:28.185767Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.26587677725118486\n", "Precision: 0.26587677725118486\n", "Recall: 1.0\n" ] } ], "source": [ "# Evaluation der angepassten Vorhersagen:\n", "from sklearn.metrics import accuracy_score, precision_score, recall_score\n", "\n", "print(\"Accuracy:\", accuracy_score(y_test, y_pred_custom))\n", "print(\"Precision:\", precision_score(y_test, y_pred_custom, pos_label=1))\n", "print(\"Recall:\", recall_score(y_test, y_pred_custom, pos_label=1))" ] } ], "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 }