Exploratory Data Analysis on Netflix Movies and TV Shows

Welcome to this captivating exploratory data analysis (EDA) project that delves deep into the vast universe of Netflix's movies and TV shows! 🎥📺

🎯 Objective

The primary objective of this project is to uncover hidden insights and patterns within Netflix's extensive content library. By analyzing various attributes such as genres, countries of origin, release years, and more, we aim to gain a comprehensive understanding of the platform's offerings and viewer preferences.

📊 Dataset

The dataset used in this project is sourced from Kaggle, a renowned platform for data science enthusiasts. It encompasses a wide array of information about Netflix's movies and TV shows, including titles, directors, cast, countries, release years, ratings, durations, and genres.

🔍 Methodology

The EDA process is divided into several key stages:

1. Data Acquisition: Obtaining the Netflix Movies and TV Shows dataset from Kaggle.
2. Data Wrangling: Cleaning and preprocessing the dataset to ensure consistency and reliability.
3. Data Exploration: Investigating the dataset's structure, distributions, and relationships using descriptive statistics and visualizations.
4. Data Mining and Analysis: Applying advanced techniques such as classification, regression, clustering, and feature engineering to uncover deeper insights.

📈 Key Findings

Through meticulous analysis, several fascinating insights emerged:

• The dataset comprises 30.3% TV shows and 69.7% movies, catering to a diverse audience.
• The United States and India dominate the content production, highlighting their significant influence.
• The years 2016 to 2018 witnessed a peak in both movie and TV show releases, indicating a surge in content creation.
• Genres like International Movies, Dramas, and Comedies have the highest representation, while niche genres such as Classic Movies, LGBTQ Movies, and Anime Features have a more limited presence.
• Interesting correlations exist between genres, such as the positive correlation between Action & Adventure and Sci-Fi & Fantasy.
• The majority of TV shows have a single season, while most movies fall within the 1.5 to 2 hours duration range.

🎨 Visualizations

This project features a rich collection of visually appealing and informative charts, graphs, and plots that bring the data to life. From pie charts showcasing the distribution of movies and TV shows to heatmaps revealing genre correlations, these visualizations provide a comprehensive overview of the dataset's intricacies.

🚀 Conclusion

The EDA on the Netflix Movies and TV Shows dataset has unveiled a treasure trove of insights that can inform content strategies, audience targeting, and industry decision-making. By leveraging these findings, stakeholders can enhance user engagement, identify new opportunities, and shape the future of entertainment.

🔧 Technologies Used

• Python 🐍
• Jupyter Notebook 📓
• Pandas 🐼
• Matplotlib 📊
• Seaborn 🎨

🌟 Acknowledgements

Special thanks to Kaggle for providing the dataset and to the vibrant data science community for their invaluable resources and inspiration.