👉 Try the Interactive Dashboard here
Explore Netflix's entire content library interactively — filter by type, rating, and year!
Performed comprehensive Exploratory Data Analysis on Netflix's content catalog to uncover trends in content type, ratings, release years, regional distribution, and genre popularity.
Built an interactive dashboard that allows users to filter and explore the data in real time.
- How has Netflix content grown over the years?
- What's the split between Movies vs TV Shows?
- Which countries produce the most Netflix content?
- What are the most common ratings and genres?
- Who are the most prolific directors on Netflix?
| Insight | Finding |
|---|---|
| 🎬 Content Split | 70.3% Movies vs 29.7% TV Shows |
| 🌍 Top Country | United States with 3,593 titles |
| 📅 Peak Year | Content additions peaked in 2019 |
| ⭐ Top Rating | TV-MA is the most common rating |
| 🎭 Top Genre | International Movies leads with 2,748 titles |
| 🎬 Top Director | Rajiv Chilaka with 22 titles |
Python Pandas Matplotlib Seaborn Streamlit
Netflix-Analysis/
├── app.py ← Streamlit interactive dashboard
├── netflix_titles.csv ← Dataset (8,807 titles)
├── requirements.txt
├── notebooks/
│ └── Netflix_Analysis.ipynb ← Full EDA notebook
└── visuals/ ← Generated charts
├── movies_vs_tvshows.png
├── top_countries.png
├── content_growth.png
├── top_genres.png
├── top_ratings.png
└── top_directors.png
- 🥧 Movies vs TV Shows distribution
- 🌍 Top 10 Countries producing content
- 📅 Netflix content growth over time
- ⭐ Content ratings distribution
- 🎭 Top 10 genres
- 🎬 Most prolific directors
# Clone the repo
git clone https://github.com/bindhusaahithi/Netflix-Analysis
# Install dependencies
pip install -r requirements.txt
# Run the dashboard
streamlit run app.pyThe live dashboard includes:
- Filter by content type — Movies or TV Shows
- Filter by rating — TV-MA, TV-14, R, PG-13, etc.
- Filter by year range — Slider from 2008 to 2021
- Search bar — Search by title, director, or cast
- Auto-updating insights — Key facts update with filters
Built by Bindhu Saahithi — Data Science Graduate Student at UMass Dartmouth
🌍 Open to Data Scientist & Analyst roles in USA & UK
