Netflix Data Visualization & Exploratory Data Analysis (EDA)

Project Overview This project focuses on performing an in-depth Exploratory Data Analysis (EDA) on a comprehensive Netflix dataset using Python. The primary objective was to uncover hidden patterns, global content trends, and distribution strategies employed by the streaming giant. By transforming raw data into actionable visual insights, this project demonstrates the power of data storytelling in understanding the entertainment industry.

Key Insights & Objectives Content Trend Analysis: Identified the growth trajectory of Movies vs. TV Shows over the last decade.

Genre Distribution: Visualized the most popular genres globally to understand audience preferences.

Geographical Insights: Mapped content availability across different countries to highlight regional focus.

Rating & Duration Analysis: Analyzed the distribution of content ratings (e.g., TV-MA, PG-13) and the average runtime of movies.

Tech Stack Programming Language: Python.

Libraries:

Pandas & NumPy: For data cleaning, manipulation, and processing.

Matplotlib & Seaborn: For creating high-quality static visualizations and heatmaps.

Plotly: To develop interactive charts that allow for deeper data exploration.