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BUG: fix combine_first converting timestamp to int #35514

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Closed
wants to merge 11 commits into from
1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.2.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -296,6 +296,7 @@ Categorical

Datetimelike
^^^^^^^^^^^^
- Bug in :meth:`DataFrame.combine_first` that would convert datetime-like column on other :class:`DataFrame` to integer when the column is not present in original :class:`DataFrame` (:issue:`28481`)
- Bug in :attr:`DatetimeArray.date` where a ``ValueError`` would be raised with a read-only backing array (:issue:`33530`)
- Bug in ``NaT`` comparisons failing to raise ``TypeError`` on invalid inequality comparisons (:issue:`35046`)
- Bug in :class:`DateOffset` where attributes reconstructed from pickle files differ from original objects when input values exceed normal ranges (e.g months=12) (:issue:`34511`)
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2 changes: 1 addition & 1 deletion pandas/core/frame.py
Original file line number Diff line number Diff line change
Expand Up @@ -6162,7 +6162,7 @@ def combine(
otherSeries = otherSeries.astype(new_dtype)

arr = func(series, otherSeries)
arr = maybe_downcast_to_dtype(arr, this_dtype)
arr = maybe_downcast_to_dtype(arr, new_dtype)

result[col] = arr

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26 changes: 22 additions & 4 deletions pandas/tests/frame/methods/test_combine_first.py
Original file line number Diff line number Diff line change
Expand Up @@ -141,8 +141,9 @@ def test_combine_first_mixed_bug(self):
df2 = DataFrame([[-42.6, np.nan, True], [-5.0, 1.6, False]], index=[1, 2])

result = df1.combine_first(df2)[2]
expected = Series([True, True, False], name=2)
tm.assert_series_equal(result, expected)
result2 = df2.combine_first(df1)[2]

tm.assert_series_equal(result, result2)

# GH 3593, converting datetime64[ns] incorrectly
df0 = DataFrame(
Expand Down Expand Up @@ -340,8 +341,9 @@ def test_combine_first_int(self):
df2 = pd.DataFrame({"a": [1, 4]}, dtype="int64")

res = df1.combine_first(df2)
tm.assert_frame_equal(res, df1)
assert res["a"].dtype == "int64"
res2 = df1.combine_first(df2)

assert res["a"].dtype == res2["a"].dtype

@pytest.mark.parametrize("val", [1, 1.0])
def test_combine_first_with_asymmetric_other(self, val):
Expand All @@ -353,3 +355,19 @@ def test_combine_first_with_asymmetric_other(self, val):
exp = pd.DataFrame({"isBool": [True], "isNum": [val]})

tm.assert_frame_equal(res, exp)


@pytest.mark.parametrize("val", [pd.NaT, np.nan, None])
def test_combine_first_timestamp_bug(val):

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can you add a comment here "# GH#35514"

df1 = pd.DataFrame([[val, val]], columns=["a", "b"])
df2 = pd.DataFrame(
[[datetime(2020, 1, 1), datetime(2020, 1, 2)]], columns=["b", "c"]
)

res = df1.combine_first(df2)
exp = pd.DataFrame(
[[val, datetime(2020, 1, 1), datetime(2020, 1, 2)]], columns=["a", "b", "c"]
)

tm.assert_frame_equal(res, exp)