8000 fix: scalar timestamp assignment (#19843) by DylanDmitri · Pull Request #19973 · pandas-dev/pandas · GitHub
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fix: scalar timestamp assignment (#19843) #19973

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Merged
merged 7 commits into from
Aug 2, 2018
Merged

fix: scalar timestamp assignment (#19843) #19973

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5a9b1b9
fix: scalar timestamp assignment (#19843)
DylanDmitri Mar 2, 2018
601cf54
moved tests
DylanDmitri Mar 2, 2018
33f8651
issue number in tests
DylanDmitri Mar 2, 2018
59069b9
added whatsnew
DylanDmitri Mar 3, 2018
edcb4e2
Merge branch 'master' into PR_TOOL_MERGE_PR_19973
jreback Aug 2, 2018
c48fbe9
update docs
jreback Aug 2, 2018
1b9649c
clean
jreback Aug 2, 2018
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clean
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@jreback
jreback committed Aug 2, 2018
commit 1b9649c8957a9e0fdc25a8a1a2a4039eedfeba7e
2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.24.0.txt
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Expand Up @@ -559,7 +559,7 @@ Timezones
- Bug in :class:`DatetimeIndex` where constructing with an integer and tz would not localize correctly (:issue:`12619`)
- Fixed bug where :meth:`DataFrame.describe` and :meth:`Series.describe` on tz-aware datetimes did not show `first` and `last` result (:issue:`21328`)
- Bug in :class:`DatetimeIndex` comparisons failing to raise ``TypeError`` when comparing timezone-aware ``DatetimeIndex`` against ``np.datetime64`` (:issue:`22074`)
- Bug in ``DataFrame`` assignment with a timezone-aware object (:issue:`19843`)
- Bug in ``DataFrame`` assignment with a timezone-aware scalar (:issue:`19843`)

< 8000 /span>
Offsets
^^^^^^^
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9 changes: 4 additions & 5 deletions pandas/core/frame.py
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Expand Up @@ -27,6 +27,7 @@
maybe_upcast,
cast_scalar_to_array,
construct_1d_arraylike_from_scalar,
infer_dtype_from_scalar,
maybe_cast_to_datetime,
maybe_infer_to_datetimelike,
maybe_convert_platform,
Expand Down Expand Up @@ -3508,14 +3509,12 @@ def reindexer(value):

else:
# cast ignores pandas dtypes. so save the dtype first
from pandas.core.dtypes.cast import infer_dtype_from_scalar
pd_dtype, _ = infer_dtype_from_scalar(value, pandas_dtype=True)
infer_dtype, _ = infer_dtype_from_scalar(
value, pandas_dtype=True)

# upcast
value = cast_scalar_to_array(len(self.index), value)

# then add dtype back in
value = maybe_cast_to_datetime(value, pd_dtype)
value = maybe_cast_to_datetime(value, infer_dtype)

# return internal types directly
if is_extension_type(value) or is_extension_array_dtype(value):
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14 changes: 3 additions & 11 deletions pandas/tests/frame/test_indexing.py
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Expand Up @@ -37,8 +37,6 @@

from pandas.tests.frame.common import TestData

from pandas.core.dtypes.dtypes import DatetimeTZDtype


class TestDataFrameIndexing(TestData):

Expand Down Expand Up @@ -3141,15 +3139,9 @@ def test_scalar_assignment(self):
# issue #19843
df = pd.DataFrame(index=(0, 1, 2))
df['now'] = pd.Timestamp('20130101', tz='UTC')
assert isinstance(df.dtypes[0], DatetimeTZDtype)

def test_datetime_index_assignment(self):
# issue #19843
df = pd.DataFrame(index=(0, 1, 2))
di = pd.DatetimeIndex(
[pd.Timestamp('20130101', tz='UTC')]).repeat(len(df))
df['now'] = di
assert isinstance(df.dtypes[0], DatetimeTZDtype)
expected = pd.DataFrame(
{'now': pd.Timestamp('20130101', tz='UTC')}, index=[0, 1, 2])
tm.assert_frame_equal(df, expected)


class TestDataFrameIndexingUInt64(TestData):
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0