📺 TV Data Insights

A data storytelling project exploring Netflix movie trends through Python and curiosity.
By Quatia.A. | The Data Nomadic

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🧭 Overview

This project investigates patterns in Netflix movie data from genre popularity to release year trends.
It’s part of my journey transitioning into data engineering, where I blend technical analysis with cultural and creative insight.

Whether you're a data enthusiast, a curious viewer, or a fellow nomadic learner, welcome aboard.

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📂 Project Structure

TV_Data_Insights/
├── datasets/               # Raw and cleaned data files
│   └── netflix_movies.csv  # Example dataset (replace with actual name)
├── TV_data_insights.ipynb  # Main analysis notebook
├── requirements.txt        # Python dependencies
├── .gitignore              # Git setup to exclude cache and venv
└── README.md               # Project documentation

🚀 Getting Started To run the notebook locally:

1. Clone the repository

git clone https://github.com/the-data-nomadic/TV_Data_Insights.git
cd TV_Data_Insights

2. (Optional) Create a virtual environment

bash
python -m venv venv
source venv/bin/activate      # macOS/Linux
venv\Scripts\activate         # Windows

4. Install dependencies

pip install -r requirements.txt

6. Launch the notebook

bash
jupyter notebook TV_data_insights.ipynb

🤝 Connect & Collaborate Feel free to fork the repo, suggest improvements, or reach out for collaboration. Let’s build data stories that resonate across cultures, platforms, and perspectives.