Netflix Data Analysis Project

This project explores and analyzes Netflix’s global content library using Python. I performed data cleaning, exploratory data analysis (EDA), and created insightful visualizations to uncover trends in content distribution, release patterns, ratings, and contributors.

The project answers questions like:

• How is Netflix’s content split between Movies and TV Shows?

• Which years saw the highest content additions?

• How are content ratings distributed?

• Who are the most frequent directors and actors featured on Netflix?

Using libraries such as Pandas, Matplotlib, and Seaborn, the analysis uncovers meaningful patterns in Netflix’s global streaming catalog, delivering visualizations and summaries that simplify complex data for better understanding.