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TST: add test for .unique() dtype preserving #29515

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Merged
merged 5 commits into from
Nov 14, 2019
Merged

TST: add test for .unique() dtype preserving #29515

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777e801
add test for .unique() preserving dtype
ganevgv Nov 9, 2019
09a602d
move test
ganevgv Nov 9, 2019
6af0391
use np.sctypes to extract all dtypes
ganevgv Nov 11, 2019
0dea22d
use any_numpy_dtype to extract dtypes
ganevgv Nov 13, 2019
14793af
sort imports using isort
ganevgv Nov 13, 2019
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19 changes: 19 additions & 0 deletions pandas/tests/test_algos.py
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Original file line number Diff line number Diff line change
Expand Up @@ -353,6 +353,25 @@ def test_on_index_object(self):

tm.assert_almost_equal(result, expected)

@pytest.mark.parametrize(
"data, uniques, dtype_list",
[
([1, 2, 2], [1, 2], np.sctypes["int"]),
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i would rather not use numpy references here and instead use our fixtures or definitions in pandas/conftest.py they are much more comprehensive and include pandas types

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Thanks for the feedback, @jreback - now using any_numpy_dtype to extract the dtypes.

([1, 2, 2], [1, 2], np.sctypes["uint"]),
([1, 2, 2], [1.0, 2.0], np.sctypes["float"]),
([1, 2, 2], [1.0, 2.0], np.sctypes["complex"]),
([True, True, False], [True, False], np.sctypes["others"]), # bool, object
],
)
def test_dtype_preservation(self, data, uniques, dtype_list):
# GH 15442
for dtype in dtype_list:
if dtype not in [bytes, str, np.void]:
result = Series(data, dtype=dtype).unique()
expected = np.array(uniques, dtype=dtype)

tm.assert_numpy_array_equal(result, expected)

def test_datetime64_dtype_array_returned(self):
# GH 9431
expected = np_array_datetime64_compat(
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