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BUG: Make DTI/TDI/PI argsort match their underlying arrays #37965

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Merged
merged 5 commits into from
Dec 17, 2020
Merged

BUG: Make DTI/TDI/PI argsort match their underlying arrays #37965

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d8c504b
BUG: Make DTI/TDI/PI argsort match their underlying arrays
jbrockmendel Nov 19, 2020
474c18c
Merge branch 'master' of https://github.com/pandas-dev/pandas into bu…
jbrockmendel Nov 21, 2020
5ba963c
non-ea compat
jbrockmendel Nov 21, 2020
f08ad69
Merge branch 'master' of https://github.com/pandas-dev/pandas into bu…
jbrockmendel Dec 2, 2020
2a47536
Merge branch 'master' of https://github.com/pandas-dev/pandas into bu…
jbrockmendel Dec 2, 2020
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3 changes: 2 additions & 1 deletion pandas/core/groupby/grouper.py
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Expand Up @@ -374,7 +374,8 @@ def _set_grouper(self, obj: FrameOrSeries, sort: bool = False):
# possibly sort
if (self.sort or sort) and not ax.is_monotonic:
# use stable sort to support first, last, nth
indexer = self.indexer = ax.argsort(kind="mergesort")
# TODO: why does putting na_position="first" fix datetimelike cases?
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I am not really familiar with the history of NaTs with respect to resample. I would have assumed NaT would/should have been dropped by this point since we just exclude them from the result #13164.

I'm okay with this solution as a stop gap solution.

indexer = self.indexer = ax.argsort(kind="mergesort", na_position="first")
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   def argsort(
        self,
        ascending: bool = True,
        kind: str = "quicksort",
        na_position: str = "last",

in arrays/base.py so this is strange

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i think it must involve the fact that on older numpys, dt64.argsort used to put NaT at the beginning instead of the end

ax = ax.take(indexer)
obj = obj.take(indexer, axis=self.axis)

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4 changes: 0 additions & 4 deletions pandas/core/indexes/base.py
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Expand Up @@ -4743,10 +4743,6 @@ def argsort(self, *args, **kwargs) -> np.ndarray:
>>> idx[order]
Index(['a', 'b', 'c', 'd'], dtype='object')
"""
if needs_i8_conversion(self.dtype):
# TODO: these do not match the underlying EA argsort methods GH#37863
return self.asi8.argsort(*args, **kwargs)

# This works for either ndarray or EA, is overriden
# by RangeIndex, MultIIndex
return self._data.argsort(*args, **kwargs)
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8 changes: 8 additions & 0 deletions pandas/tests/indexes/datetimelike.py
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Expand Up @@ -9,6 +9,14 @@


class DatetimeLike(Base):
def test_argsort_matches_array(self):
rng = self.create_index()
rng = rng.insert(1, pd.NaT)

result = rng.argsort()
expected = rng._data.argsort()
tm.assert_numpy_array_equal(result, expected)

def test_argmax_axis_invalid(self):
# GH#23081
msg = r"`axis` must be fewer than the number of dimensions \(1\)"
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