An interactive and intelligent data visualization and exploration app built with Streamlit, based on the Netflix dataset.
This dashboard helps users analyze, filter, and visualize Netflix content across genres, countries, ratings, and time — all with dynamic visualizations, sentiment analysis, and machine learning predictions.
🚀 Click here to view the Live App)
- Filter by Type (Movie / TV Show)
- Filter by Country, Rating, and Genre
- Full-text search across title, cast, and director
- 📅 Titles added to Netflix over time (by year)
- 🔞 Distribution of content ratings
- 🍿 Most common genres
- ⏱️ Average durations (Movies: minutes, TV Shows: seasons)
- 🌍 Top countries with Netflix content (Choropleth world map)
- Analyzes content descriptions using
TextBlob - Visualizes sentiment polarity from -1 (negative) to +1 (positive)
- Download the filtered dataset as CSV
├── app.py # Streamlit main app ├── netflix_titles.csv # Dataset file ├── requirements.txt # Python dependencies ├── .gitignore # Ignored files └── README.md # You're reading it!
- Python 3.8+
- pip
# 1. Clone the repo
git clone https://github.com/mansoobezahra/netflix-dashboard.git
cd netflix-dashboard
# 2. Create virtual environment (optional but recommended)
python -m venv venv
venv\Scripts\activate # On Windows
source venv/bin/activate # On Mac/Linuxpip install -r requirements.txt
streamlit run app.py
🛠️ To Do Improve genre classification model
Add IMDb rating scraping
CI/CD pipeline with GitHub Actions
Add user login with Streamlit auth
Export sentiment & ML results
🤝 Contributing Pull requests are welcome! If you’d like to fix a bug, suggest a feature, or add a new module — fork the repo and go ahead 🚀
📜 License This project is open-source under the MIT License.
🙋♀️ Maintainer Made with 💻 and ☕ by Mansoob E Zehra
If you found this useful, consider giving it a ⭐️!