BUG: df.agg(sum, axis=1) uses different method than when axis=0 #21222
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Outdated suggestions cannot be applied.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.
git diff upstream/master -u -- "*.py" | flake8 --diff
This is a splitoff from #21123, to only fix #21134. #19629 will be fixed in a separate PR afterwards.
Passing builtins to
df.agg
is ok whenaxis=0
, but can give wrong result, whenaxis=1
when NaNs are supplied.Explanation
Passing the functions in
SelectionMixin._cython_table
todf.agg
should defer to use the relevant cython functions. This currently works as expected whenaxis=0
, but not always whenaxis=1
.The reason for this difference is that
df.aggregate
currently defers todf._aggregate
whenaxis=0
, but defers todf.apply
, whenaxis=1
, and these give different result when passed funcions and the series/frame contains Nan values. I've solved this by transposing df in_aggragate
whenaxis=1
.The tests have been heavily parametrized, helping ensure that the various ways to call
df.agg
now give correct result.