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Exploratory Data Analysis (EDA) and insights from a Netflix movie dataset, including genre trends, popularity patterns, and year-wise movie production stats.

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Netflix Movie Data Analysis

Exploratory Data Analysis (EDA) and insights from a Netflix movie dataset, focusing on genre trends, popularity patterns, and year-wise movie production. This beginner-friendly Data Science project involves data cleaning, visualization, and analysis to uncover meaningful insights from the dataset.


πŸ“Œ Project Overview

This analysis answers key questions such as:

  • What is the most frequent genre?
  • Which genres are the most popular?
  • Which movie has the highest and lowest popularity?
  • Which year saw the most movie releases?

The dataset has been processed and visualized using Python libraries like Pandas, Matplotlib, and Seaborn.


πŸ› οΈ Tools & Libraries

  • Python
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Jupyter Notebook

πŸ“Š Key Insights

  • Most Frequent Genre: Drama (appeared in over 14% of movies)
  • Highest Popular Genre: Drama (dominates popular vote movies too)
  • Most Popular Movie: Spider-Man: No Way Home
    Genres: Action, Adventure, Science Fiction
  • Least Popular Movie: The United States, Thread
    Genres: Music, Drama, War, Sci-Fi, History
  • Most Active Year: 2020

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Exploratory Data Analysis (EDA) and insights from a Netflix movie dataset, including genre trends, popularity patterns, and year-wise movie production stats.

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