TYP overload fillna

[MarcoGorelli]

fillna has a different return type according to whether inplace is True or False. We could overload it to provide a better typing experience

See #40197 for a very similar issue

Task here is:

1. read through TYP: use overload to refine return type of set_axis #40197, make sure you understand it
2. try doing the same for fillna
3. check it works. See the above PR for an example, but it should be something like the following (but for fillna instead of reset_index - some of the other arguments probably need changing too)

# t.py

import pandas as pd

inplace: bool

reveal_type(pd.DataFrame([1,2,3]).reset_index(level=0))
reveal_type(pd.DataFrame([1,2,3]).reset_index(inplace=False))
reveal_type(pd.DataFrame([1,2,3]).reset_index(drop=True, inplace=True))
reveal_type(pd.DataFrame([1,2,3]).reset_index(level=0, inplace=True))
reveal_type(pd.DataFrame([1,2,3]).reset_index(level=0, drop=False, inplace=True))
reveal_type(pd.DataFrame([1,2,3]).reset_index(level=0, inplace=True, col_fill='a'))
reveal_type(pd.DataFrame([1,2,3]).reset_index(level=0, col_fill='a'))
reveal_type(pd.DataFrame([1,2,3]).reset_index(inplace=True))
reveal_type(pd.DataFrame([1,2,3]).reset_index(inplace=inplace))
reveal_type(pd.DataFrame([1,2,3]).reset_index(drop=True, inplace=inplace))
reveal_type(pd.DataFrame([1,2,3]).reset_index(level=0, inplace=inplace))
reveal_type(pd.DataFrame([1,2,3]).reset_index(level=0, drop=False, inplace=inplace))
reveal_type(pd.DataFrame([1,2,3]).reset_index(level=0, inplace=inplace, col_fill='a'))
reveal_type(pd.DataFrame([1,2,3]).reset_index(inplace=inplace))

output:

$ mypy t.py 
t.py:5: note: Revealed type is 'pandas.core.frame.DataFrame'
t.py:6: note: Revealed type is 'pandas.core.frame.DataFrame'
t.py:7: note: Revealed type is 'None'
t.py:8: note: Revealed type is 'None'
t.py:9: note: Revealed type is 'None'
t.py:10: note: Revealed type is 'None'
t.py:11: note: Revealed type is 'pandas.core.frame.DataFrame'
t.py:12: note: Revealed type is 'None'
t.py:13: note: Revealed type is 'Union[pandas.core.frame.DataFrame, None]'
t.py:14: note: Revealed type is 'Union[pandas.core.frame.DataFrame, None]'
t.py:15: note: Revealed type is 'Union[pandas.core.frame.DataFrame, None]'
t.py:16: note: Revealed type is 'Union[pandas.core.frame.DataFrame, None]'
t.py:17: note: Revealed type is 'Union[pandas.core.frame.DataFrame, None]'
t.py:18: note: Revealed type is 'Union[pandas.core.frame.DataFrame, None]'

---

I've marked this as 'good first issue' as it doesn't require any knowledge of the pandas core codebase, though it's probably not the easiest if you're not at least somewhat familiar with mypy / typing

[MarcoGorelli]

This issue would unblock some of the typing difficulties in #38594

[LarWong]

take

[LarWong]

@MarcoGorelli Hi! I'm a first-time contributor, and this is my first attempt at an issue. So forgive me if this takes a few days to do while I get used to this codebase and to the rules associated with this project. Thanks!

[LarWong]

Hi @MarcoGorelli. After reading #40197 and the pandas documentation, I am under the impression that I would need to add overloads to the following files: pandas/core/frame.py, pandas/core/series.py, and pandas/core/generic.py. Is this correct?

[MarcoGorelli]

Hi @LarWong - yup, that's right! This one's a bit more complicated, as there's some extra arguments, but please do ping me if you get stuck

[LarWong]

@MarcoGorelli Will do!

[LarWong]

@AlPalll I am still working on this.

[LarWong]

@MarcoGorelli Hi. I'm getting a redundant cast error after adding overloads to series.py.
This is the error I'm getting:

pandas/core/strings/object_array.py:374: error: Redundant cast to "Series"  [redundant-cast]
pandas/core/strings/object_array.py:376: error: Redundant cast to "Series"  [redundant-cast]

and this the part of the code that the warning refers to:

370: arr = Series(self).fillna("")
371: try:
372:     arr = sep + arr + sep
373: except TypeError:
374:     arr = cast(Series, arr)
375:     arr = sep + arr.astype(str) + sep
376:  arr = cast(Series, arr)

I am new to Python typing, so I am a bit confused on how to resolve this. Thanks