{ "cells": [ { "cell_type": "code", "execution_count": null, "id": "e32b2301", "metadata": { "id": "e32b2301" }, "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "id": "e1a30dc7", "metadata": { "id": "e1a30dc7" }, "source": [ "## Download the dataset" ] }, { "cell_type": "markdown", "id": "b514fe82", "metadata": { "id": "b514fe82" }, "source": [ "Go to [Kaggle](https://www.kaggle.com/datasets/blastchar/telco-customer-churn) and download the telco customer churn dataset.\n", "\n", "source: https://www.kaggle.com/datasets/blastchar/telco-customer-churn" ] }, { "cell_type": "markdown", "id": "c5711d8a", "metadata": { "id": "c5711d8a" }, "source": [ "## Load the data" ] }, { "cell_type": "code", "execution_count": null, "id": "67e8ec66", "metadata": { "id": "67e8ec66" }, "outputs": [], "source": [ "# locate the dataset on your computer and fill in the path below:\n", "filepath = \"WA_Fn-UseC_-Telco-Customer-Churn.csv\"" ] }, { "cell_type": "code", "execution_count": null, "id": "8d9f8f37", "metadata": { "id": "8d9f8f37" }, "outputs": [], "source": [ "# Load the csv file into a Pandas DataFrame\n", "df = pd.read_csv(filepath, na_values = [' '])" ] }, { "cell_type": "code", "execution_count": null, "id": "39705746", "metadata": { "id": "39705746", "outputId": "ad8c5875-360b-417a-caed-f9fe0335e3f9" }, "outputs": [ { "data": { "text/html": [ "
\n", " | customerID | \n", "gender | \n", "SeniorCitizen | \n", "Partner | \n", "Dependents | \n", "tenure | \n", "PhoneService | \n", "MultipleLines | \n", "InternetService | \n", "OnlineSecurity | \n", "... | \n", "DeviceProtection | \n", "TechSupport | \n", "StreamingTV | \n", "StreamingMovies | \n", "Contract | \n", "PaperlessBilling | \n", "PaymentMethod | \n", "MonthlyCharges | \n", "TotalCharges | \n", "Churn | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", "7590-VHVEG | \n", "Female | \n", "0 | \n", "Yes | \n", "No | \n", "1 | \n", "No | \n", "No phone service | \n", "DSL | \n", "No | \n", "... | \n", "No | \n", "No | \n", "No | \n", "No | \n", "Month-to-month | \n", "Yes | \n", "Electronic check | \n", "29.85 | \n", "29.85 | \n", "No | \n", "
1 | \n", "5575-GNVDE | \n", "Male | \n", "0 | \n", "No | \n", "No | \n", "34 | \n", "Yes | \n", "No | \n", "DSL | \n", "Yes | \n", "... | \n", "Yes | \n", "No | \n", "No | \n", "No | \n", "One year | \n", "No | \n", "Mailed check | \n", "56.95 | \n", "1889.50 | \n", "No | \n", "
2 | \n", "3668-QPYBK | \n", "Male | \n", "0 | \n", "No | \n", "No | \n", "2 | \n", "Yes | \n", "No | \n", "DSL | \n", "Yes | \n", "... | \n", "No | \n", "No | \n", "No | \n", "No | \n", "Month-to-month | \n", "Yes | \n", "Mailed check | \n", "53.85 | \n", "108.15 | \n", "Yes | \n", "
3 | \n", "7795-CFOCW | \n", "Male | \n", "0 | \n", "No | \n", "No | \n", "45 | \n", "No | \n", "No phone service | \n", "DSL | \n", "Yes | \n", "... | \n", "Yes | \n", "Yes | \n", "No | \n", "No | \n", "One year | \n", "No | \n", "Bank transfer (automatic) | \n", "42.30 | \n", "1840.75 | \n", "No | \n", "
4 | \n", "9237-HQITU | \n", "Female | \n", "0 | \n", "No | \n", "No | \n", "2 | \n", "Yes | \n", "No | \n", "Fiber optic | \n", "No | \n", "... | \n", "No | \n", "No | \n", "No | \n", "No | \n", "Month-to-month | \n", "Yes | \n", "Electronic check | \n", "70.70 | \n", "151.65 | \n", "Yes | \n", "
5 rows × 21 columns
\n", "