Churn Analysis Project

This repository contains the code and data files for a churn analysis project, aimed at identifying key variables that contribute to customer churn. The project is divided into four main parts:

1. Data Acquisition
2. Data Exploration
3. Data Cleaning
4. Principal Component Analysis

Getting Started

These instructions will help you set up the project on your local machine.

Prerequisites

• Python 3.x
• Jupyter Notebook

Installing

1. Clone the repository to your local machine.
2. Navigate to the project directory.
3. Install the required packages using the following command:

pip install -r requirements.txt

4. Open Jupyter Notebook and navigate to the project directory to start working on the notebooks.

Project Structure

The project is divided into the following sections:

Data

This folder contains the data files used in the project. It includes CSV files with information about customers, services, and survey responses.

Src

This folder contains the python scripts used for assessing and mitigating data quality issues. These scripts are organized in separate files for easy management and understanding.

Notebooks

This folder contains Jupyter Notebooks used for data exploration, visualization, and analysis. You can open these notebooks using Jupyter Notebook or JupyterLab and run the cells to see the results.

Results

This folder contains the output files and results obtained from the analysis. It may include charts, tables, or other visualizations that provide insights into the telecom market and customer preferences.

Authors

• Javier Lopez - Initial work - GitHub Profile