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BUG: DataFrame.idxmin/idxmax with mixed dtypes #38195

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Merged
merged 6 commits into from
Dec 2, 2020
Merged

BUG: DataFrame.idxmin/idxmax with mixed dtypes #38195

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f29fff2
REF: do idxmax, idxmin block-wise
jbrockmendel Nov 30, 2020
84d5b31
BUG: DataFrame.idxmin/idxmax with mixed dtypes
jbrockmendel Nov 30, 2020
1b2ba47
Merge branch 'master' of https://github.com/pandas-dev/pandas into en…
jbrockmendel Dec 1, 2020
0639bb1
Merge branch 'master' of https://github.com/pandas-dev/pandas into en…
jbrockmendel Dec 2, 2020
a526398
whatsnew
jbrockmendel Dec 2, 2020
0f215e9
Merge branch 'master' of https://github.com/pandas-dev/pandas into en…
jbrockmendel Dec 2, 2020
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.2.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -619,6 +619,7 @@ Numeric
- Bug in :class:`DataFrame` allowing arithmetic operations with list of array-likes with undefined results. Behavior changed to raising ``ValueError`` (:issue:`36702`)
- Bug in :meth:`DataFrame.std` with ``timedelta64`` dtype and ``skipna=False`` (:issue:`37392`)
- Bug in :meth:`DataFrame.min` and :meth:`DataFrame.max` with ``datetime64`` dtype and ``skipna=False`` (:issue:`36907`)
- Bug in :meth:`DataFrame.idxmax` and :meth:`DataFrame.idxmin` with mixed dtypes incorrectly raising ``TypeError`` (:issue:`38195`)

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^^^^^^^^^^
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12 changes: 10 additions & 2 deletions pandas/core/frame.py
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Expand Up @@ -9001,7 +9001,11 @@ def idxmin(self, axis=0, skipna=True) -> Series:
dtype: object
"""
axis = self._get_axis_number(axis)
indices = nanops.nanargmin(self.values, axis=axis, skipna=skipna)

res = self._reduce(
nanops.nanargmin, "argmin", axis=axis, skipna=skipna, numeric_only=False
)
indices = res._values

# indices will always be np.ndarray since axis is not None and
# values is a 2d array for DataFrame
Expand Down Expand Up @@ -9074,7 +9078,11 @@ def idxmax(self, axis=0, skipna=True) -> Series:
dtype: object
"""
axis = self._get_axis_number(axis)
indices = nanops.nanargmax(self.values, axis=axis, skipna=skipna)

res = self._reduce(
nanops.nanargmax, "argmax", axis=axis, skipna=skipna, numeric_only=False
)
indices = res._values

# indices will always be np.ndarray since axis is not None and
# values is a 2d array for DataFrame
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14 changes: 14 additions & 0 deletions pandas/tests/frame/test_reductions.py
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Expand Up @@ -969,6 +969,20 @@ def test_idxmax(self, float_frame, int_frame):
with pytest.raises(ValueError, match=msg):
frame.idxmax(axis=2)

def test_idxmax_mixed_dtype(self):
# don't cast to object, which would raise in nanops
dti = pd.date_range("2016-01-01", periods=3)

df = DataFrame({1: [0, 2, 1], 2: range(3)[::-1], 3: dti})

result = df.idxmax()
expected = Series([1, 0, 2], index=[1, 2, 3])
tm.assert_series_equal(result, expected)

result = df.idxmin()
expected = Series([0, 2, 0], index=[1, 2, 3])
tm.assert_series_equal(result, expected)

# ----------------------------------------------------------------------
# Logical reductions

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