Netflix-data-analysis

🎬 Netflix Data Analysis & Visualization (EDA Project)

This project is an exploratory data analysis (EDA) of the Netflix Titles dataset. It involves data cleaning, handling missing values, analyzing content trends, and visualizing key insights using Pandas, NumPy, Matplotlib, and Seaborn.

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📌 Objectives

• Understand Netflix’s content distribution
• Identify top genres, countries, and content types
• Visualize trends over time (e.g. releases per year)
• Extract valuable insights that help in understanding Netflix’s global strategy

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📂 Dataset

• Source: Netflix Titles Dataset on Kaggle
• Size: ~8,800+ entries
• Columns: type, title, director, cast, country, date_added, release_year, duration, listed_in, description

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📊 Tools & Libraries Used

• Python 🐍
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Google Colab

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📈 Key Insights

✅ Most of the content on Netflix is Movies, not TV Shows
✅ Content production exploded after 2017, showing platform growth
✅ United States, India, and UK contribute the most content
✅ Genres like Dramas, International Movies, and Comedies dominate
✅ Top directors and recurring actors help analyze Netflix’s partnerships

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