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Data Analysis Statistical Thinking

The data is about IBM Telco Customer Churn. The dataset is downloaded from Strivatsan88's Github Repo

Content

  1. Title: IBM Customer Churn Dataset

  2. Sources:

    Origin: This dataset was taken from Srivatsan88' YoutubeLI Github Repository. I downloaded the dataset in order to walkthrough the Youtube video published by AIEngineering, Statistical Thinking - Imputing Missing Values Date: October 10, 2021

Description of Data

The data is stored in the /dataset/orignal folder, where you can find customer_data.csv

Details on the original data:

  • Number of instances: 7044

  • Number of attributes: 10

  • Attribute information:

    Attribute Name Description Attribute Type
    customerID Unique ID of customer Qualitative
    Gender Gender of customer Qualitative
    SeniorCitizen Flag indicating if customer is a senior citizen Multi-value discrete
    Tenure Period of tenure Continous
    ServiceCount Number of service made by customer Continous
    Contract Type of contract for the service Qualitative
    PaperlessBilling Boolean indicating method of payment made by customer Qualitative
    MonthlyCharges Monthly charges for the services Continous
    Churn Boolean as label if customer churn Qualitative

  • Missing attribute values: The data exploration is not conducted yet.

Inspiration

Inspired by Data Analysis on Rozie's Dataset. I decided to sharpen my statistics to improve my analysis skills. This is sole for training purposes. Feel free to join along :)