Netflix Data Analysis
This project entails a thorough analysis of the Netflix dataset using Pandas. The dataset includes information about titles, genres, release dates, durations, and ratings. The objective is to uncover viewing trends, popular genres, release patterns, and user ratings. The analysis aims to provide valuable insights into Netflix's content library and viewer preferences, helping to understand what makes content popular on the platform.
Key Findings:
Total Number of Titles: The dataset contains a total count of titles available on Netflix.
Unique Genres: The analysis identifies various genres represented in the dataset.
Titles Released Each Year: Examination of the number of titles released each year, showcasing release trends over time.
Most Popular Genres: Identification of the most popular genres based on the number of titles.
Average Duration of Titles: Calculation of the average duration of titles in the dataset, providing insights into typical viewing lengths.
Highest Rated Titles: Analysis of titles with the highest ratings, highlighting top-rated content.
Titles by Content Type: Breakdown of titles by content type, such as movies and TV shows.
Age Distribution of Titles: Examination of the distribution of titles by age rating, identifying content targeted at different age groups.
Top Directors and Actors: Identification of the most frequent directors and actors featured in Netflix titles.
Titles Released by Country: Analysis of the number of titles released by different countries, showcasing global content diversity.
Viewing Patterns by Month: Examination of viewing patterns by month, identifying peak release periods.
Trending Titles Over Time: Analysis of titles that have trended over time, showcasing long-term popularity.
Parth Arora