Built on the powerful PySpark framework and packaged within a Docker environment, PyScrub offers a scalable, flexible, and efficient way to cleanse and profile large datasets. Whether you're dealing with inconsistencies, missing values, or you need to understand your data's structure and quality at a glance, PyScrub is here to help.
active 2024-04-09 → 2024-06-15 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 68 days from 2024-04-09 to 2024-06-15. Pushes: 2 total, peak 1 in a day. Pull requests: 1 total, peak 1 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 4 total, peak 1 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
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| rachit-mishra | 3 | 2 | 1 | 0 |
Recent activity
Latest issues, pull requests and releases
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 4 stars here means stars gained during the window, not the repo's star count.