TMDB Interactive Movie EDA 🎬📊

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📖 Project Overview

Interactive Exploratory Data Analysis (EDA) of movies using The Movie Database (TMDB) API. Fetch real-world data on box office, ratings, and more, then explore trends with dynamic, interactive charts directly in a Jupyter Notebook.

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📋 Table of Contents

• Features
• Technologies
• Requirements
• Installation
• TMDB API Setup
• Usage
• Demo
• Contributing
• License
• Contact

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✨ Features

• 📊 Interactive Visualizations: Scatter plots, bar charts, and line graphs with hover details.
• 🔎 Dynamic Filters: Filter by year, genre, popularity, and more using ipywidgets controls.
• 📈 Data Insights: Analyze box office trends, rating distributions, and popularity metrics.
• 🔄 Automated Data Pipeline: Fetch, clean, and preprocess data from TMDB with pandas and requests.

Why include an API section?
Highlighting API integration shows practical skills in real-world data retrieval and backend communication—qualities recruiters value for data-centric roles.

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🛠 Technologies

• Language: Python 3.8+
• Notebook Environment: Jupyter Notebook
• Libraries:
  • pandas for data manipulation
  • requests for API calls
  • plotly-express for interactive charts
  • ipywidgets for user controls

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📦 Requirements

• Python 3.8 or higher
• TMDB account and API key
• pip package manager

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🚀 Installation

# Clone this repository
git clone https://github.com/Vinicius-Mangueira/TMDB-Interactive-Movie-EDA.git
cd TMDB-Interactive-Movie-EDA

# (Optional) Create and activate a virtual environment
python -m venv venv
# Linux/macOS
source venv/bin/activate
# Windows
venv\\Scripts\\activate

# Install dependencies
pip install -r requirements.txt

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🔑 TMDB API Setup

1. Sign up for a free account at TMDB.
2. Generate an API key under Settings → API.
3. Add your API key to the notebook or a .env file:

import os
os.environ['TMDB_API_KEY'] = 'YOUR_API_KEY_HERE'

Note: Including an API setup section demonstrates your ability to work with external services and configure environments, which recruiters often look for.

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🎓 Usage

1. Launch the Jupyter Notebook:

   jupyter notebook Notebooks/TMDB_EDA.ipynb

2. Run all cells in sequence to:

   • Download and preprocess data
   • Generate interactive visualizations
   • Use widgets for custom filtering

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📸 Demo

Example: Action Movies Released in 2020

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🤝 Contributing

Contributions are welcome!

1. Fork the repo
2. Create a new branch: git checkout -b feature-name
3. Commit your changes: git commit -m 'Add new feature'
4. Push to your branch: git push origin feature-name
5. Open a Pull Request

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📄 License

This project is licensed under the MIT License.

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📬 Contact

Vinícius Mangueira – GitHub – LinkedIn – [email protected]