https://github.com/jnnjenga/video-game-analysis
Performs exploratory data analysis on a video game dataset, examining titles, release dates, teams, ratings, genres, and user engagement metrics to uncover trends, popular genres, and developer insights.
https://github.com/jnnjenga/video-game-analysis
data-analysis data-science dataset eda exploratory-data-analysis game-analysis games genres jupyter-notebook pandas python trends user-engagement video-game visualization
Last synced: 2 months ago
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Performs exploratory data analysis on a video game dataset, examining titles, release dates, teams, ratings, genres, and user engagement metrics to uncover trends, popular genres, and developer insights.
- Host: GitHub
- URL: https://github.com/jnnjenga/video-game-analysis
- Owner: Jnnjenga
- Created: 2025-05-27T18:38:34.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-27T18:40:26.000Z (about 1 year ago)
- Last Synced: 2025-06-07T15:06:15.270Z (about 1 year ago)
- Topics: data-analysis, data-science, dataset, eda, exploratory-data-analysis, game-analysis, games, genres, jupyter-notebook, pandas, python, trends, user-engagement, video-game, visualization
- Language: Jupyter Notebook
- Homepage:
- Size: 1.63 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Video Game Analysis
This notebook explores a video game dataset, analyzing titles, release dates, developers, ratings, genres, and user engagement (plays, backlogs, wishlists). It uncovers trends, popular genres, and developer insights through data cleaning and summary statistics.
## How to Run
1. Open `Video-game-analysis.ipynb` in Jupyter Notebook.
2. Run all cells to reproduce the analysis.
## Requirements
- Python 3.x
- pandas
- numpy
- (Optional) matplotlib, seaborn