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Netflix Data Analysis Project

Project Overview

This repository contains the code, documentation, and presentation for a comprehensive analysis of the Netflix content catalog. The project explores content trends in Movies and TV Shows, genre popularity, and country-wise contributions using Python, data visualization, and statistical analysis.

Problem Statement

With increasing competition in the streaming industry, Netflix must strategically analyze its content catalog to identify strengths, gaps, and opportunities. This project aims to deliver actionable insights by examining content distribution, genres, and geographic representation over time.

Objectives

  • Analyze the distribution of Movies vs. TV Shows from 2008 to 2021.
  • Identify the most common genres and how their popularity has changed.
  • Compare country-wise contributions to Netflix’s catalog.

Technologies Used

  • Python (Pandas, NumPy)
  • Matplotlib, Seaborn, Plotly
  • Google Colab / Jupyter Notebook
  • GitHub
  • Microsoft PowerPoint

Repository Structure

  • Netflix_VOIS.ipynb — Main analysis notebook
  • Netflix Dataset.csv — Source dataset
  • README.md — Project documentation

Results

  • Clear insights into Netflix’s evolving content strategy
  • Identification of top genres, countries, and categories
  • Strategic recommendations for future content focus

Author

Debangshu Bhattacharjee AICTE Internship Project — October 2025


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