📊 Netflix Data Analytics

This project performs exploratory data analysis (EDA) on the Netflix Titles dataset to uncover trends and insights about the platform's global content distribution, genre preferences, and content evolution over time.

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📁 Dataset

• File: netflix_titles.csv
• Total Records: ~8,800+
• Features: Title, Type, Director, Cast, Country, Release Year, Rating, Duration, Genres, and more.

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🔍 Objectives

• 📅 Analyze release trends over the years
• 🌍 Identify top countries producing Netflix content
• 🎬 Explore popular genres and content types
• 🎭 Analyze most frequent actors and directors
• 📌 Understand the distribution of Movies vs TV Shows
• 📈 Visualize missing data and key patterns using Python

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🧰 Tools & Libraries

• pandas for data analysis
• numpy for numerical operations
• matplotlib and seaborn for data visualization
• missingno for missing data handling
• wordcloud for visualizing top actors and genres

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📊 Key Visualizations

• Movie vs TV Show distribution pie chart
• Year-wise content addition bar graph
• Top 10 countries by content volume
• Wordclouds for cast and genre
• Heatmaps of missing data
• Rating-wise content analysis

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▶️ How to Run

1. Clone the repo

   git clone https://github.com/shruthika-tr/Netflix-Data-Analytics.git cd Netflix-Data-Analytics

2. Install required libraries

   pip install -r requirements.txt

3. Launch the Jupyter Notebook

   jupyter notebook netflix_data_analytics.ipynb