Instagram Data Parsing & Analysis (Pure Python)

A Python project that parses Instagram-style raw text data, cleans it, converts it into structured JSON, and performs analysis to extract insights like:

• Most followed profile
• Profile with maximum posts
• Profile following the most users
• Category distribution

This repository contains both:

• ✅ A runnable script version (main.py)
• ✅ A Jupyter notebook (notebooks/instagram_data_parsing_analysis.ipynb)

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🚀 Features

• Parse unstructured raw text records
• Clean & normalize fields
• Store structured data as JSON
• Run analytics (top accounts, category counts)
• Export cleaned CSV

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📂 Project Structure

instagram-data-analysis/
│── main.py
│── src/
│   ├── parser.py
│   ├── analysis.py
│   └── utils.py
│── notebooks/
│   └── instagram_data_parsing_analysis.ipynb
│── data/
│   ├── initialdata.txt
│   ├── finaldata.csv
│   └── data.json
│── README.md
│── requirements.txt
│── .gitignore
│── LICENSE

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⚙️ Installation

git clone https://github.com/Nandd11/instagram-data-analysis.git
cd instagram-data-analysis
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt

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▶️ Run (Script Mode)

python main.py

It will:

1. Parse data/initialdata.txt
2. Create data/data.json
3. Create data/finaldata.csv
4. Print analytics summary

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🧪 Example Output

Total profiles: 150
Top by followers: user_abc (1,200,000)
Top by posts: user_xyz (12,430)
Top by following: user_pqr (7,210)

Category distribution:
Blogger: 42
Fitness: 31
Business: 21
...

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👤 Author

Nand Patel
GitHub: https://github.com/Nandd11