Skip to content

GH-49255: Fix pandas deprecation warnings in Categorical tests #49271

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

Closed
shashbha14 wants to merge 1 commit into from
Closed

GH-49255: Fix pandas deprecation warnings in Categorical tests #49271

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
22 changes: 13 additions & 9 deletions python/pyarrow/tests/test_pandas.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3069,15 +3069,19 @@ def test_category(self):
v2 = [4, 5, 6, 7, 8]
v3 = [b'foo', None, b'bar', b'qux', np.nan]

cat_strings = pd.Categorical(v1 * repeats)
cat_strings_with_na = cat_strings.set_categories(['foo', 'bar'])

@AlenkaF AlenkaF Mar 12, 2026

Copy link
Copy Markdown
Member

Choose a reason for hiding this comment

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

We are probably still getting into missing categories being silently converted to NaN here and Pandas is moving away from that AFAIU.

As the idea in the test is to have NaN in the constructed categorical array, we might simply remove this line as the cat_strings actually already includes them:

In [19]: pd.Categorical(v1 * repeats)
    ...: 
Out[19]: 
['foo', NaN, 'bar', 'qux', NaN, ..., 'foo', NaN, 'bar', 'qux', NaN]
Length: 25
Categories (3, str): ['bar', 'foo', 'qux']

What we can do is to add:

v0 = ['foo', 'bar', 'qux']

and use this for cat_strings? This way we do not have to look for a workaround where we use deprecated behavior to construct NaN values due to missing categories.


cat_strings_ordered = pd.Categorical(
v1 * repeats, categories=['bar', 'qux', 'foo'], ordered=True
)

arrays = {
'cat_strings': pd.Categorical(v1 * repeats),
'cat_strings_with_na': pd.Categorical(v1 * repeats,
categories=['foo', 'bar']),
'cat_strings': cat_strings,
'cat_strings_with_na': cat_strings_with_na,
'cat_ints': pd.Categorical(v2 * repeats),
'cat_binary': pd.Categorical(v3 * repeats),
'cat_strings_ordered': pd.Categorical(
v1 * repeats, categories=['bar', 'qux', 'foo'],
ordered=True),
'cat_strings_ordered': cat_strings_ordered,
'ints': v2 * repeats,
'ints2': v2 * repeats,
'strings': v1 * repeats,
Expand All @@ -3096,10 +3100,10 @@ def _check(v):
result = arr.to_pandas()
tm.assert_series_equal(pd.Series(result), pd.Series(v))

base = pd.Categorical(['a', 'b', 'c'])
arrays = [
pd.Categorical(['a', 'b', 'c'], categories=['a', 'b']),
pd.Categorical(['a', 'b', 'c'], categories=['a', 'b'],
ordered=True)
base.set_categories(['a', 'b']),
base.set_categories(['a', 'b']).as_ordered(),
Comment on lines -3100 to +3106

@AlenkaF AlenkaF Mar 12, 2026

Copy link
Copy Markdown
Member

Choose a reason for hiding this comment

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

I think it would be simpler to do:

pd.Categorical(['a', 'b', None], categories=['a', 'b'])

This should be the same use case as reported here #19704.

]
for arr in arrays:
_check(arr)
Expand Down
Loading