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Fix ndarray allany #12901

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Fix ndarray allany #12901

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8a4d6a1
Fix for wrong any and all return value when ndarray is an object
artheist Apr 13, 2016
6ec7123
Associated tests for any_all nanops
artheist Apr 14, 2016
9343c2d
Added whatsnew doc
artheist Apr 14, 2016
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.18.1.txt
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Expand Up @@ -273,6 +273,7 @@ Bug Fixes

- Bug in ``pivot_table`` when ``margins=True`` and ``dropna=True`` where nulls still contributed to margin count (:issue:`12577`)

- Bug in ``Series.any`` and ``Series.all`` for dtype object (:issue:`12863`)
- Bug in ``Series.name`` when ``name`` attribute can be a hashable type (:issue:`12610`)
- Bug in ``.describe()`` resets categorical columns information (:issue:`11558`)
- Bug where ``loffset`` argument was not applied when calling ``resample().count()`` on a timeseries (:issue:`12725`)
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10 changes: 8 additions & 2 deletions pandas/core/nanops.py
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Expand Up @@ -254,12 +254,18 @@ def _wrap_results(result, dtype):

def nanany(values, axis=None, skipna=True):
values, mask, dtype, _ = _get_values(values, skipna, False, copy=skipna)
return values.any(axis)
if is_object_dtype(dtype):
return any(values)
else:
return values.any(axis)


def nanall(values, axis=None, skipna=True):
values, mask, dtype, _ = _get_values(values, skipna, True, copy=skipna)
return values.all(axis)
if is_object_dtype(dtype):
return all(values)
else:
return values.all(axis)


@disallow('M8')
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23 changes: 19 additions & 4 deletions pandas/tests/series/test_analytics.py
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Expand Up @@ -549,16 +549,31 @@ def test_all_any(self):

# Alternative types, with implicit 'object' dtype.
s = Series(['abc', True])
self.assertEqual('abc', s.any()) # 'abc' || True => 'abc'
self.assertEqual(True, s.any())
self.assertEqual(True, s.all())
s = Series(['abc', False])
self.assertEqual(True, s.any())
self.assertEqual(False, s.all())

def test_all_any_params(self):
# Check skipna, with implicit 'object' dtype.
s1 = Series([np.nan, True])
s2 = Series([np.nan, False])
self.assertTrue(s1.all(skipna=False)) # nan && True => True
self.assertTrue(s1.all(skipna=True))
self.assertTrue(np.isnan(s2.any(skipna=False))) # nan || False => nan
self.assertTrue(s1.all(skipna=False))
self.assertFalse(s2.all(skipna=False))
self.assertTrue(s2.any(skipna=False))
self.assertFalse(s2.any(skipna=True))
self.assertFalse(s2.all(skipna=True))
s1 = Series([None, True])
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why would these not be exactly the same? (as np.nan)

s2 = Series([None, False])
self.assertFalse(s1.all(skipna=False))
self.assertTrue(s1.any(skipna=False))
self.assertFalse(s2.all(skipna=False))
self.assertFalse(s2.any(skipna=False))
self.assertTrue(s1.all(skipna=True))
self.assertFalse(s2.all(skipna=True))
self.assertFalse(s2.any(skipna=False))


# Check level.
s = pd.Series([False, False, True, True, False, True],
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