@@ -24,6 +24,27 @@ and `good first issue
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where you could start out. Once you've found an interesting issue, you can
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return here to get your development environment setup.
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+ When you start working on an issue, it's a good idea to assign the issue to yourself,
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+ so nobody else duplicates the work on it. GitHub restricts assigning issues to maintainers
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+ of the project only. In most projects, and until recently in pandas, contributors added a
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+ comment letting others know they are working on an issue. While this is ok, you need to
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+ check each issue individually, and it's not possible to find the unassigned ones.
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+
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+ For this reason, we implemented a workaround consisting of adding a comment with the exact
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+ text `take `. When you do it, a GitHub action will automatically assign you the issue
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+ (this will take seconds, and may require refreshint the page to see it).
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+ By doing this, it's possible to filter the list of issues and find only the unassigned ones.
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+
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+ So, a good way to find an issue to start contributing to pandas is to check the list of
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+ `unassigned good first issues <https://github.com/pandas-dev/pandas/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22+no%3Aassignee >`_
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+ and assign yourself one you like by writing a comment with the exact text `take `.
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+
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+ If for whatever reason you are not able to continue working with the issue, please try to
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+ unassign it, so other people know it's available again. You can check the list of
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+ assigned issues, since people may not be working in them anymore. If you want to work on one
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+ that is assigned, feel free to kindly ask the current assignee if you can take it
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+ (please allow at least a week of inactivity before considering work in the issue discontinued).
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+
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Feel free to ask questions on the `mailing list
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<https://groups.google.com/forum/?fromgroups#!forum/pydata> `_ or on `Gitter `_.
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