BUG: JoinUnit.is_na wrong for CategoricalDtype #37196
Merged
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
black pandas
git diff upstream/master -u -- "*.py" | flake8 --diff
JoinUnit.is_na is basically checking
isna(self.block.values).all()
. The check for is_categorical is an attempted optimization bc values.categories is often much smaller than values. But Categorical represents its NAs in its codes, not in its categories. So this will incorrectly always return False in the status quo.Having trouble coming up with a useful test. I can adapt a test from test_concat that returns an incorrect answer from is_na, but that does not appear to affect the result of the higher-level pd.concat call.