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🎬 Netflix Data Analysis 📊

Unlocking content trends, audience behavior, and business insights using SQL, Python & Visualizations.


📁 Project Overview

This project dives deep into Netflix’s content to extract actionable insights on content types, genres, countries, ratings, and more.
It uses SQL for data preparation and Python (Pandas + Matplotlib/Seaborn) for analysis and visuals, ideal for analytics portfolios.


🛠️ Tools & Technologies

  • SQL – Data extraction and filtering
  • Python (Pandas, Matplotlib, Seaborn) – Data cleaning & visualization
  • Jupyter Notebook – Interactive analysis
  • PowerPoint – For a client-facing summary deck

📌 Key Insights

  • 🍿 TV Shows retain users better than movies despite being fewer in number.
  • 🌎 U.S. dominates content, but India shows rapid regional growth.
  • 🎭 Top genres include International Movies, Dramas & Comedies.
  • 🔞 Most content is TV-MA rated, highlighting mature audience targeting.
  • 👤 Rajeev Chilaka is a leading director for kids’ shows.
  • 🎬 Anupam Kher is the most featured Indian actor on the platform.
  • 🧠 Sentiment classification flags 8465 as Good, 342 as Bad using keywords.

📊 Visual Gallery

You’ll find charts like:

  • Movies vs TV Shows 📊
  • Top 5 Countries by Content 🌍
  • Top 10 Genres 🎭
  • Indian Content Over the Years 🇮🇳
  • Good vs Bad Sentiment 📑

(Located in /charts folder) - https://drive.google.com/file/d/1S1igs1fYz4yfFABJBeUzZy_iCA3BgtaL/view?usp=sharing


✅ Final Recommendations

  • Invest in TV Shows for long-term retention
  • Expand Indian and regional content
  • Collaborate with frequent directors/actors
  • Balance mature and general audience content


🙌 Connect With Me

📧 Email: bishakhakapur7@gmail.com 🔗 LinkedIn: HTTPS://LINKEDIN.COM/IN/BISHAKHA-KAPUR-605181317

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A Netflix data analysis project using SQL and Python to explore content trends, top genres, ratings, and regional growth opportunities.

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