A data analysis project exploring descriptive, predictive, and sentiment analysis for my favorite YouTube program. Using the YouTube API, I scraped data from playlists across three channels. Built with Jupyter Notebook in a virtual environment, this project reflects my passion for understanding content performance
active 2024-12-20 → 2024-12-20 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-12-20 to 2024-12-20. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
Nobody pushed, opened or commented here in the loaded window — this repo's activity is stars and forks only.
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.