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API: add return_inverse to pd.unique #24119

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API: add return_inverse to pd.unique #24119

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158d925
Code & whatsnew
h-vetinari Feb 1, 2019
49e42f1
Extend and parametrize unique-test to all numpy dtypes
h-vetinari Feb 1, 2019
9285e8c
Also test inverse in test_unique_all_dtypes
h-vetinari Feb 1, 2019
45eff67
Parametrize test_timedelta64_dtype_array_returned
h-vetinari Feb 1, 2019
de22c62
Add inverse to test_timedelta64_dtype_array_returned
h-vetinari Feb 1, 2019
2a4f4a7
Add inverse to test_nan_in_object_array
h-vetinari Feb 1, 2019
39a2e64
Parametrize test_categorical
h-vetinari Feb 2, 2019
bfc310f
Add inverse to test_categorical
h-vetinari Feb 2, 2019
af7d8f3
Parametrize test_datetime64tz_aware
h-vetinari Feb 2, 2019
c089f1f
Add inverse to test_datetime64tz_aware
h-vetinari Feb 2, 2019
78d4758
Remove test case that is covered elsewhere
h-vetinari Feb 2, 2019
006d7ad
Fix DatetimeArray-case in test_datetime64tz_aware; create TODO
h-vetinari Feb 2, 2019
b310b48
blackify conflict files
h-vetinari Oct 11, 2019
df375ad
Merge remote-tracking branch 'upstream/master' into pd_unique_inv
h-vetinari Oct 11, 2019
786159f
lint
h-vetinari Oct 11, 2019
39f23ff
Merge remote-tracking branch 'upstream/master' into pd_unique_inv
h-vetinari Oct 11, 2019
dfee500
fix oversight from merge
h-vetinari Oct 11, 2019
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Parametrize test_datetime64tz_aware
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@h-vetinari
h-vetinari committed Feb 2, 2019
commit af7d8f3b33d87f0d8b96060278fa7a9b48df46a3
60 changes: 18 additions & 42 deletions pandas/tests/test_algos.py
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Original file line number Diff line number Diff line change
Expand Up @@ -472,36 +472,26 @@ def test_categorical(self, method, box, ordered):
reconstr = box(result_uniques[result_inverse])
assert_series_or_index_or_array_or_categorical_equal(reconstr, c)

def test_datetime64tz_aware(self):
@pytest.mark.parametrize('box', [Series, Index])
@pytest.mark.parametrize('method', [lambda x, **kwargs: x.unique(**kwargs),
pd.unique],
ids=['classmethod', 'toplevel'])
def test_datetime64tz_aware(self, method, box):
# GH 15939

result = Series(
Index([Timestamp('20160101', tz='US/Eastern'),
Timestamp('20160101', tz='US/Eastern')])).unique()
expected = DatetimeArray._from_sequence(np.array([
Timestamp('2016-01-01 00:00:00-0500', tz="US/Eastern")
]))
tm.assert_extension_array_equal(result, expected)

result = Index([Timestamp('20160101', tz='US/Eastern'),
Timestamp('20160101', tz='US/Eastern')]).unique()
expected = DatetimeIndex(['2016-01-01 00:00:00'],
dtype='datetime64[ns, US/Eastern]', freq=None)
tm.assert_index_equal(result, expected)

result = pd.unique(
Series(Index([Timestamp('20160101', tz='US/Eastern'),
Timestamp('20160101', tz='US/Eastern')])))
expected = DatetimeArray._from_sequence(np.array([
Timestamp('2016-01-01', tz="US/Eastern"),
]))
tm.assert_extension_array_equal(result, expected)

result = pd.unique(Index([Timestamp('20160101', tz='US/Eastern'),
Timestamp('20160101', tz='US/Eastern')]))
expected = DatetimeIndex(['2016-01-01 00:00:00'],
dtype='datetime64[ns, US/Eastern]', freq=None)
tm.assert_index_equal(result, expected)
ts = Timestamp('20160101', tz='US/Eastern')
obj = box([ts, ts])

if box == Series:
expected = DatetimeArray._from_sequence(np.array([
Timestamp('2016-01-01 00:00:00-0500', tz="US/Eastern")
]))
else: # Index
expected = DatetimeIndex(['2016-01-01 00:00:00'],
dtype='datetime64[ns, US/Eastern]',
freq=None)
result = method(obj)
assert_series_or_index_or_array_or_categorical_equal(result, expected)

def test_order_of_appearance(self):
# 9346
Expand All @@ -515,20 +505,6 @@ def test_order_of_appearance(self):
tm.assert_numpy_array_equal(result,
np.array([2, 1], dtype='int64'))

result = pd.unique(Series([Timestamp('20160101'),
Timestamp('20160101')]))
expected = np.array(['2016-01-01T00:00:00.000000000'],
dtype='datetime64[ns]')
tm.assert_numpy_array_equal(result, expected)

result = pd.unique(Index(
[Timestamp('20160101', tz='US/Eastern'),
Timestamp('20160101', tz='US/Eastern')]))
expected = DatetimeIndex(['2016-01-01 00:00:00'],
dtype='datetime64[ns, US/Eastern]',
freq=None)
tm.assert_index_equal(result, expected)

result = pd.unique(list('aabc'))
expected = np.array(['a', 'b', 'c'], dtype=object)
tm.assert_numpy_array_equal(result, expected)
Expand Down