Comments (3)
I am aware that this repo is "born" from the existing stubs, but it seems like there are some stubs that live in the pylance bundle (I have no idea where on GitHub, though) that we can probably add in?
A bit of history here. It used to be that in https://github.com/microsoft/python-type-stubs, the complete distribution of the pandas stubs that were shipped with pylance were included.
At some point in time, only some of them were in that repo that passed the typing tests, but Microsoft would add the "missing" stubs back (but I don't know from where) when packaging pylance
.
When we took the Microsoft stubs and made this project, we pulled the ones in that repo, but missed the ones Microsoft was merging in. I'm planning on fixing that today (7/3) or tomorrow.
Related issue is #55
from pandas-stubs.
I think a lot of these are already in pandas. It might be that these are stripped out for convenience by pylance.
I'm pretty sure io is fully typed in pandas.
from pandas-stubs.
I think a lot of these are already in pandas. It might be that these are stripped out for convenience by pylance.
I'm pretty sure io is fully typed in pandas.
You're right, they areโbut until pandas adds the py.typed
flag, mypy and pylance are going to have depend on stub files, unless I'm mistaken?
from pandas-stubs.
Related Issues (20)
- Allow 'integer' in select_dtypes include argument HOT 1
- Unexpected, Misleading mypy Failures After pandas-stubs Update: DataFrame.from_dict() Behavior HOT 5
- Should from_dict be annotated to allow sequence data values? HOT 8
- Index.rename() should return Self HOT 3
- Annotation of `get_loc` does no longer fit to `iloc` resulting in many false positive type errors. HOT 2
- Can't pass `dict` to `DataFrame.apply` HOT 1
- `Series.map()` needs type for `arg` and result HOT 5
- pd.notna does not work with pyright strict mode. HOT 1
- `df.merge` partially unknown.
- `Series.astype` is partially unknown. HOT 2
- `df.drop` signature does not capture all constraints HOT 1
- Type of "apply" is partially unknown HOT 6
- Switch `to_timedelta` argument type from `list` to `Sequence` HOT 1
- Invalid typing for `df.to_csv` HOT 1
- read_csv: parameter usecols has wrong type hint HOT 17
- GroupBy[Series].count() should have return type Series[int] HOT 1
- Check incorrect when using a TimestampSeries and YearEnd from pandas.tseries.offsets HOT 1
- Pandas stubs forces numpy <2.0.0 for python < 3.12 HOT 1
- Restore nightly CI build due to new pandas version (3.0.0)
- Series constructor does not accept TypedDict HOT 1
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from pandas-stubs.