📽️Netflix - Exploratory Data Analysis🎬
Overview This project involves performing exploratory data analysis (EDA) on Netflix's dataset, which contains information about TV shows and movies available on the platform. The analysis focuses on key metrics, content distribution, and patterns to extract insights about content types, genres, countries of origin, and ratings.
Project Objective The main objective of this project is to analyze the Netflix dataset to identify trends and patterns in the content offered. The project aims to uncover:
*Popular content types (Movies vs. TV Shows)
*Distribution of content by genre and country
*Top-performing actors and directors
*Trends in content release by year and month
*Insights on content duration for both movies and TV shows
Key Highlights
*Content Distribution: Analyzed the breakdown between movies and TV shows, revealing that 60% of the content consists of movies.
*Top Genres: Identified that International Movies, Dramas, and Comedies are the most popular genres on Netflix.
*Country-Based Content: Found that the United States, India, and the UK are the leading contributors in terms of content production.
*Top Performers: Discovered the most frequent actors (e.g., Anupam Kher, Shah Rukh Khan) and directors (e.g., Rajiv Chilaka) in Netflix’s catalog.
*Content Duration: Most movies are between 90-150 minutes long, while most TV shows have 1-2 seasons. *Release Trends: Movies are frequently released towards the end of the year, while TV shows are typically added in mid-year months (July/August).