Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

BUG: Fix fillna on multi indexed Dataframe doesn't work #47774

Merged
merged 9 commits into from
Aug 23, 2022
Merged

BUG: Fix fillna on multi indexed Dataframe doesn't work #47774

Show file tree
Hide file tree
Changes from 4 commits
Commits
Show all changes
9 commits
Select commit Hold shift + click to select a range
462134d
fix 47649
xr-chen Jul 17, 2022
1bcdaef
fix fillna ignore underlying issue
xr-chen Jul 20, 2022
5409961
fix pre commit
xr-chen Jul 20, 2022
764f0ab
add TODO
xr-chen Aug 3, 2022
f3d79a9
update TODO
xr-chen Aug 3, 2022
e384fd6
Add small changes
phofl Aug 18, 2022
336f92d
Merge branch 'main' into fillna
phofl Aug 18, 2022
79a542b
Merge branch 'main' into fillna
simonjayhawkins Aug 23, 2022
15db9ab
Update doc/source/whatsnew/v1.4.4.rst
jorisvandenbossche Aug 23, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.5.0.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -917,6 +917,7 @@ Missing
- Bug in :meth:`DataFrame.interpolate` with object-dtype column not returning a copy with ``inplace=False`` (:issue:`45791`)
- Bug in :meth:`DataFrame.dropna` allows to set both ``how`` and ``thresh`` incompatible arguments (:issue:`46575`)
- Bug in :meth:`DataFrame.fillna` ignored ``axis`` when :class:`DataFrame` is single block (:issue:`47713`)
- Bug in :meth:`DataFrame.fillna` not working on multiindexed DataFrame (:issue:`47649`)

MultiIndex
^^^^^^^^^^
Expand Down
7 changes: 5 additions & 2 deletions pandas/core/generic.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6674,9 +6674,12 @@ def fillna(
if k not in result:
continue
downcast_k = downcast if not is_dict else downcast.get(k)
result.loc[:, k] = result[k].fillna(
v, limit=limit, downcast=downcast_k
# GH47649
result.loc[:, k] = (
result[k].fillna(v, limit=limit, downcast=downcast_k).values
)
# TODO: Revert to result.loc[:, k] = result[k].fillna(...)
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Please put this right next to the todo and we want to use loc on both sides I think

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

You mean make comments like this?

# TODO: result.loc[:, k] = result.loc[:, k].fillna(
#     v, limit=limit, downcast=downcast_k
# )
# Revert when GH45751 is fixed

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thx

# when issue GH45751 is fixed
return result if not inplace else None

elif not is_list_like(value):
Expand Down
28 changes: 28 additions & 0 deletions pandas/tests/frame/methods/test_fillna.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -708,6 +708,34 @@ def test_single_block_df_with_horizontal_axis(self):
)
tm.assert_frame_equal(result, expected)

def test_fillna_with_multi_index_frame(self):
# GH 47649
pdf = DataFrame(
{
("x", "a"): [np.nan, 2.0, 3.0, 4.0, np.nan, 6.0],
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Could you simplify the DataFrame? 2 rows should be sufficient.

Also please add a test with ea dtypes

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Sure, could you be more specific about what dtypes we want in the test?

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Int64 for example

("x", "b"): [1.0, 2.0, np.nan, 4.0, np.nan, np.nan],
("y", "c"): [1.0, 2.0, 3.0, 4.0, np.nan, np.nan],
}
)
expected = DataFrame(
{
("x", "a"): [-1.0, 2.0, 3.0, 4.0, -1.0, 6.0],
("x", "b"): [1.0, 2.0, -1.0, 4.0, -1.0, -1.0],
("y", "c"): [1.0, 2.0, 3.0, 4.0, np.nan, np.nan],
}
)
tm.assert_frame_equal(pdf.fillna({"x": -1}), expected)
tm.assert_frame_equal(pdf.fillna({"x": -1, ("x", "b"): -2}), expected)

expected = DataFrame(
{
("x", "a"): [-1.0, 2.0, 3.0, 4.0, -1.0, 6.0],
("x", "b"): [1.0, 2.0, -2.0, 4.0, -2.0, -2.0],
("y", "c"): [1.0, 2.0, 3.0, 4.0, np.nan, np.nan],
}
)
tm.assert_frame_equal(pdf.fillna({("x", "b"): -2, "x": -1}), expected)


def test_fillna_nonconsolidated_frame():
# https://github.com/pandas-dev/pandas/issues/36495
Expand Down