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BUG: DataFrame constructor reordering elements with ndarray from datetime dtype not datetime64[ns] #39442

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Merged
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Jan 28, 2021
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BUG: DataFrame constructor reordering elements with ndarray from datetime dtype not datetime64[ns] #39442

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c4570b1
BUG: DataFrame constructor reordering elements with ndarray from date…
phofl Jan 27, 2021
3cdd101
Parametrize over contiguity
phofl Jan 27, 2021
6238485
Add order
phofl Jan 27, 2021
6b39f01
Change empty construction
phofl Jan 27, 2021
85f0bd4
Add timedelta tests
phofl Jan 28, 2021
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.3.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -233,6 +233,7 @@ Datetimelike
- Bug in constructing a :class:`DataFrame` or :class:`Series` with mismatched ``datetime64`` data and ``timedelta64`` dtype, or vice-versa, failing to raise ``TypeError`` (:issue:`38575`, :issue:`38764`, :issue:`38792`)
- Bug in constructing a :class:`Series` or :class:`DataFrame` with a ``datetime`` object out of bounds for ``datetime64[ns]`` dtype or a ``timedelta`` object out of bounds for ``timedelta64[ns]`` dtype (:issue:`38792`, :issue:`38965`)
- Bug in :meth:`DatetimeIndex.intersection`, :meth:`DatetimeIndex.symmetric_difference`, :meth:`PeriodIndex.intersection`, :meth:`PeriodIndex.symmetric_difference` always returning object-dtype when operating with :class:`CategoricalIndex` (:issue:`38741`)
- Bug in :class:`DataFrame` constructor reordering element when construction from datetime ndarray with dtype not ``"datetime64[ns]"`` (:issue:`39422`)
- Bug in :meth:`Series.where` incorrectly casting ``datetime64`` values to ``int64`` (:issue:`37682`)
- Bug in :class:`Categorical` incorrectly typecasting ``datetime`` object to ``Timestamp`` (:issue:`38878`)
- Bug in comparisons between :class:`Timestamp` object and ``datetime64`` objects just outside the implementation bounds for nanosecond ``datetime64`` (:issue:`39221`)
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2 changes: 1 addition & 1 deletion pandas/_libs/tslibs/conversion.pyx
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Expand Up @@ -222,7 +222,7 @@ def ensure_datetime64ns(arr: ndarray, copy: bool=True):
dtype = arr.dtype
arr = arr.astype(dtype.newbyteorder("<"))

ivalues = arr.view(np.int64).ravel("K")
ivalues = arr.view(np.int64).ravel("C")
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this is going to make a copy if arr has order="F" isnt it?

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Yeah unfortunately, but not sure how we can avoid this here. Could transpose back before passing in, but I think that is not an ideal solution

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could arr.flat be useful here?


result = np.empty(shape, dtype=DT64NS_DTYPE)
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would it make a difference it we constructed this with result = np.empty_like(arr, dtype=...) to ensure we keep the same contiguity?

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Oh yes, fantastic. Thanks very much

iresult = result.ravel("K").view(np.int64)
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31 changes: 31 additions & 0 deletions pandas/tests/frame/test_constructors.py
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Expand Up @@ -1762,6 +1762,37 @@ def test_constructor_datetimes_with_nulls(self, arr):
expected = Series([np.dtype("datetime64[ns]")])
tm.assert_series_equal(result, expected)

@pytest.mark.parametrize(
"dtype",
[
"datetime64[M]",
"datetime64[D]",
"datetime64[h]",
"datetime64[m]",
"datetime64[s]",
"datetime64[ms]",
"datetime64[us]",
"datetime64[ns]",
],
)
def test_constructor_datetimes_non_ns(self, dtype):
na = np.array(
[
["2015-01-01", "2015-01-02", "2015-01-03"],
["2017-01-01", "2017-01-02", "2017-02-03"],
],
dtype=dtype,
)
df = DataFrame(na)
expected = DataFrame(
[
["2015-01-01", "2015-01-02", "2015-01-03"],
["2017-01-01", "2017-01-02", "2017-02-03"],
]
)
expected = expected.astype(dtype=dtype)
tm.assert_frame_equal(df, expected)

def test_constructor_for_list_with_dtypes(self):
# test list of lists/ndarrays
df = DataFrame([np.arange(5) for x in range(5)])
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