pandas-dev GitHub Actions Analytics

The pandas-dev GitHub organization experienced notable activity in January 2026, characterized by robust pull request dynamics and a thriving code review culture. Throughout the month, the organization executed a total of 2,177 GitHub Actions runs, achieving 1,060 successful runs and reflecting an overall success rate of 48.69%. This data indicates a resilient foundation for ongoing development, despite a slight decline in success compared to previous periods.

The analysis of pull request metrics reveals a significant success-to-failure ratio of 8.48:1, with successful runs outnumbering failures by a substantial margin. Specifically, 1,060 successes were recorded against 125 failures, underscoring the organization’s commitment to high-quality code and effective continuous integration practices.

Examining the workflow insights, the Unit Tests workflow, which accounted for 202 runs, achieved a commendable success rate of 63.37%. In contrast, the Code Checks workflow excelled with an impressive 98.02% success rate, while the Doc Build and Upload workflow achieved a stellar 99.48% success rate, highlighting the organization’s dedication to maintaining comprehensive documentation.

From a development velocity tracking perspective, the average execution time for workflows was 561.68 seconds, with Unit Tests being the most time-consuming at an average of 3340.13 seconds per run. This suggests potential areas for optimization to enhance execution efficiency.

Overall, the pandas-dev organization demonstrates strong project health, high success rates, and active contributor engagement. The top contributors, including mroeschke and jorisvandenbossche, have significantly impacted the development landscape, completing 1,219 and 205 runs respectively, with success rates of 62.43% and 54.63%. These insights not only highlight the strength of the pandas ecosystem but also offer valuable perspectives for those interested in developer contribution trends and engineering investment analysis.