# The pandas community
The community of pandas users and developers is large and decentraliazed. We try to direct certain conversations to certain channels.
- Use the #pandas tag on StackOverflow (opens new window) for usage questions (like “How do I do X in pandas?”)
- Use the GitHub issue tracker (opens new window) for
- Bug reports (like “
DataFrame.head()returns 6 rows, when it should return 5.”)
- Documentation issues (like “I found this section unclear”)
- Feature requests (like “I think the DataFrame repr should include a pandas emoji next to the shape.”)
- Bug reports (like “
- Use the pandas dev mailing list (opens new window) for longer-form discussion items. This is for things that concern the broader pandas community. Most users probably don’t care about an obscure edge-case in
Series.str.split(which should be reported on the issue tracker), but may care about larger-picture things like
- How should we have discussions about pandas and the community?
- Developing or adding items to a pandas roadmap
- Announcing sprints or conference talks
- Changes to the development workflow
- Announcements for pandas releases and developer meetings
- Use the pandas gitter (opens new window) for quick feedback on development issues
- I’m having trouble setting up the development environment.
- I messed up my git branches, can someone take a look?
To learn more about how to contribute to the ongoing development of pandas, please check out our contributing guidelines (opens new window). For deeper development discussions related to the direction of the project, you can join the developer mailing list (opens new window).
# History of Development
In 2008, pandas development began at AQR Capital Management (opens new window). By the end of 2009 it had been open sourced (opens new window), and is actively supported today by a community of like-minded individuals around the world who contribute their valuable time and energy to help make open source pandas possible. Thank you to all of our contributors (opens new window).
pandas is a NumFOCUS (opens new window) sponsored project. This will help ensure the success of development of pandas as a world-class open-source project.