📊 Telecom Churn Analysis

This Streamlit application provides a comprehensive analysis of telecom churn data. It allows users to upload a CSV file and generates various visualizations to explore key factors influencing customer churn.

Features

• 📂 CSV File Upload: Users can upload their own CSV files for analysis.
• 🧩 Data Overview: Display dataset information including shape, column names, and a preview of the data.
• 📊 Visualizations:
  • Network Usage by State: Bar chart showing total minutes spent across different states.
  • Churn Distribution: Pie chart depicting the proportion of churned vs non-churned users.
  • Correlation Heatmap: Heatmap illustrating the correlations between different features.
  • Churn vs Customer Service Calls: Line chart showing the relationship between customer service calls and churn rates.
  • Average Customer Service Calls by State: Bar chart of the average number of customer service calls across states.

Algorithms and Techniques

• Data Processing: Utilizes Pandas for data manipulation and transformation.
• Visualization: Leverages Seaborn and Matplotlib for creating insightful visualizations, including bar charts, pie charts, and heatmaps.
• Statistical Analysis: Computes feature correlations and analyzes the impact of customer service calls on churn rates.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/telecom-churn-analysis.git
   cd telecom-churn-analysis

2. Create and activate a virtual environment:

   • On Windows:

     python -m venv venv
     .\venv\Scripts\activate

   • On macOS/Linux:

     python3 -m venv venv
     source venv/bin/activate

3. Install the required packages:

   pip install -r requirements.txt

Usage

Run the Streamlit app:

streamlit run app.py