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In [2]: s = pd.Series([1, None, 3], dtype='datetime64[ns]') In [3]: s.max(skipna=False) Out[3]: Timestamp('1970-01-01 00:00:00.000000003')
That should be NaT.
NaT
We get min correct, but think just because iNaT is already the min.
min
Probably affects datetimetz / timedelta as well.
The text was updated successfully, but these errors were encountered:
Fixed datetimelike-max
8c6f2db
Working around pandas-dev#24265
added whatsnew for pandas-dev#24265
a965519
BUG: Fix+test timezone-preservation in DTA.repeat (#24483)
1ebfd8a
Also add whatsnew for gh-24265
BUG: Fix+test timezone-preservation in DTA.repeat (pandas-dev#24483)
217510b
Also add whatsnew for pandas-devgh-24265
9a83cd7
Successfully merging a pull request may close this issue.
That should be
NaT
.We get
min
correct, but think just because iNaT is already the min.Probably affects datetimetz / timedelta as well.
The text was updated successfully, but these errors were encountered: