https://github.com/hrishixd/netflix-exploratory-data-analysis
This project showcases a comprehensive analysis of Netflix data using Python and its powerful libraries. The analysis includes data cleaning, manipulation, and visualization to extract meaningful insights into Netflix's content and audience trends.
https://github.com/hrishixd/netflix-exploratory-data-analysis
Last synced: 9 months ago
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This project showcases a comprehensive analysis of Netflix data using Python and its powerful libraries. The analysis includes data cleaning, manipulation, and visualization to extract meaningful insights into Netflix's content and audience trends.
- Host: GitHub
- URL: https://github.com/hrishixd/netflix-exploratory-data-analysis
- Owner: HrishixD
- Created: 2024-11-17T09:58:26.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-17T09:59:49.000Z (over 1 year ago)
- Last Synced: 2025-03-29T06:46:30.203Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 93.8 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
This project showcases a comprehensive analysis of Netflix data using Python and its powerful libraries. The analysis includes data cleaning, manipulation, and visualization to extract meaningful insights into Netflix's content and audience trends.
Key Features:
Data Cleaning: Utilized pandas to handle null values, remove duplicates, and preprocess the dataset.
Data Manipulation: Transformed and manipulated the data to prepare it for analysis.
Visualization: Used seaborn to create insightful visualizations, including heatmaps and bar graphs, for better interpretation of trends.
Exploratory Data Analysis (EDA): Identified patterns in content categories, release years, and user engagement.
This repository demonstrates the practical use of Python libraries like pandas and seaborn to analyze and visualize real-world datasets effectively.