Facebook-Dataset-Analysis

This project analyses Facebook Live Sellers data to understand engagement patterns, post effectiveness, and user behaviour.

Repository

https://github.com/Prem-101/Facebook-Dataset-Analysis

Features

• Time-based analysis of post engagement
• Clustering analysis of post types and engagement metrics
• Statistical analysis of reactions, comments, and shares
• Visualisation of engagement patterns

Project Structure

.
├── data_analysis.py     # Core analysis functions
├── FacebookDataset.ipynb # Interactive analysis notebook
└── requirements.txt     # Project dependencies

Requirements

• Python 3.8+
• Required packages listed in requirements.txt

Installation

1. Clone the repository:

git clone https://github.com/Prem-101/Facebook-Dataset-Analysis.git
cd Facebook-Dataset-Analysis

2. Install dependencies:

pip install -r requirements.txt

3. Place your Facebook_Marketplace_data.csv in the project root directory

Usage

1. Core Analysis:

import data_analysis as da

# Load and prepare data
df = da.load_and_prepare_data('Facebook_Marketplace_data.csv')

# Add time features
df = da.add_time_features(df)

# Get engagement metrics
metrics = da.get_engagement_metrics(df)

2. Interactive Analysis:

jupyter notebook FacebookDataset.ipynb

Analysis Features

• Time-based engagement analysis
• Post type distribution analysis
• Clustering analysis of engagement patterns
• Correlation analysis of engagement metrics

License

MIT License

Contributing

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a new Pull Request