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BUG: pd.NA showing up as NaN in Categorical repr #52681

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BUG: pd.NA showing up as NaN in Categorical repr #52681

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lithomas1
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  • closes #xxxx (Replace xxxx with the GitHub issue number)
  • Tests added and passed if fixing a bug or adding a new feature
  • All code checks passed.
  • Added type annotations to new arguments/methods/functions.
  • Added an entry in the latest doc/source/whatsnew/vX.X.X.rst file if fixing a bug or adding a new feature.

@lithomas1 lithomas1 added Bug Categorical Categorical Data Type labels Apr 15, 2023
@lithomas1 lithomas1 marked this pull request as ready for review April 15, 2023 12:20
@lithomas1 lithomas1 added the Output-Formatting __repr__ of pandas objects, to_string label Apr 15, 2023
@topper-123
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I have been thinking about a change to the use of the na value in Categorical, and just wrote up #52687 after being reminded by this PR. This would also change the repr IMO as a consequence of the change, so I think that would make this PR unnecessary,.

@lithomas1
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Sure, happy to see what you got.

Feel free to take my test(or any parts of this PR) if you need it.

jbrockmendel
jbrockmendel reviewed Apr 21, 2023
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pandas/tests/arrays/categorical/test_repr.py
def test_categorical_repr_nullable_int_NA(self, values_dtype):
arr = array([1, 2, np.nan], dtype=values_dtype)
c = Categorical(arr)
c_exp = f"""[1, 2, {NA}]\nCategories (2, {values_dtype}): [1, 2]"""
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so if you did c[2] would you get pd.NA or np.nan? i'm wary of changing the repr without changing the item

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This pull request is stale because it has been open for thirty days with no activity. Please update and respond to this comment if you're still interested in working on this.

@github-actions github-actions bot added the Stale label May 22, 2023
@mroeschke
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Looks like this has gone stale. Closing to clear the queue but feel free to reopen if you want to continue

@mroeschke mroeschke closed this Jun 1, 2023
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FYI, there is a slightly related #53190, which isn’t getting traction though…

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@lithomas1 @topper-123 @mroeschke @jbrockmendel