Comments (7)
Thanks for the suggestion. Ideally, we would want to have docstrings for every function, but I think it's more beneficial to write docstrings for the public pandas methods over these internal scripts.
Feel free to submit a PR to add the docstrings, but we also have open issues for improving the public documentation (such as #58065), and would appreciate your help on these issues instead
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Hey @anishfish2 and @MrF1ow, thanks for the interest but there is already someone working on this issue. Happy to have your help on other issues with the Docs
label though!
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I'm new to open source but interested in tackling this issue! Happy to learn and contribute. Can I take this on?
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Can I take this on?
Of course!
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Hi! New to open source and just wondering what the progress was on this issue?
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Hello, I was wondering if I could tackle this as well?
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If someone's already working on it, can they assign the issue to themself? That would make it easier for the rest of us to find unassigned issues.
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Related Issues (20)
- BUG: HOT 2
- BUG: .mode(dropna=False) doesn't work with nullable integers HOT 1
- BUG: iterrows() on an awkward array with equal-length rows results in a ValueError HOT 2
- BUG: float64 convert to int64 get confuse result HOT 1
- QST: HOT 2
- BUG: `diff()` returns confusing output when dealing with negative timestamp deltas HOT 1
- ENH: add "right" argument to "qcut", like "cut" has HOT 1
- BUG: default value for dtype_backend is not applied by default HOT 2
- DOC: add detailed comments pandas/tests/arithmatic/datetime/ line no: 750, test_dti_cmp_tdi_tzawareness HOT 1
- BUG: Refactor test_dti_cmp_tdi_tzawareness function to reduce redundancy pandas/tests/arithmetic/test_datetime64.py HOT 2
- BUILD: HOT 1
- BUG: AttributeError: 'Engine' object has no attribute 'cursor' HOT 5
- BUG: FutureWarning when following documentation HOT 1
- BUG: Column of dtype Categorical in DataFrame encounters error when taking a row that includes nan in the column HOT 2
- DOC: Searching DataFrame.eval( blocks me from the documentation HOT 2
- PERF: groupby is significantly slower for `DatetimeIndex` with timezone HOT 2
- Potential performance regression with "CLN: enforce deprecation of frequencies deprecated for offsets"
- PERF: 100% CPU utilization with matplotlib (macosx)
- BUG: `interval_range` ignores type of `start` (regression from pandas 2.2.2)
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