Analyze Netflix’s dataset to find insights about movies, TV shows, genres, countries, and ratings.
- Python
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Jupyter Notebook
The dataset (netflix_data.csv) contains 1,500 records with columns like:
| Column | Description |
|---|---|
| show_id | Unique identifier |
| type | Movie or TV Show |
| title | Title of the content |
| director | Director name |
| country | Country of production |
| date_added | Date added on Netflix |
| release_year | Release year |
| rating | Age rating |
| duration | Duration (min or seasons) |
| listed_in | Genre |
| description | Short content description |
- Import and explore dataset
- Data cleaning and preparation
- Visualization of content trends
- Country and genre analysis
- Insights and conclusion
- Netflix’s content has grown rapidly post-2015.
- Movies slightly outnumber TV shows.
- Top genres include Drama and Comedy.
- USA and India dominate content creation.
This project highlights Netflix’s evolving global content strategy, genre diversity, and audience preferences.
pip install -r requirements.txt
jupyter notebook Netflix_Data_Analysis.ipynb