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fix: assign NaN scalar to column error. #513

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Merged
merged 5 commits into from
Mar 29, 2024
Merged

fix: assign NaN scalar to column error. #513

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2256c89
fix: assign NaN scalar to column error.
Genesis929 Mar 25, 2024
01db0f9
Update test.
Genesis929 Mar 28, 2024
d9a8a93
remove import.
Genesis929 Mar 28, 2024
072c8ec
Merge branch 'main' into scalar-set-huanc
Genesis929 Mar 28, 2024
8d4f243
Merge branch 'main' into scalar-set-huanc
Genesis929 Mar 29, 2024
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4 changes: 4 additions & 0 deletions bigframes/core/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -229,6 +229,10 @@ def assign_constant(
value: typing.Any,
dtype: typing.Optional[bigframes.dtypes.Dtype],
) -> ArrayValue:
if pandas.isna(value):
# Need to assign a data type when value is NaN.
dtype = dtype or bigframes.dtypes.DEFAULT_DTYPE

if destination_id in self.column_ids: # Mutate case
exprs = [
(
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17 changes: 12 additions & 5 deletions tests/system/small/test_dataframe.py
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Expand Up @@ -605,17 +605,24 @@ def test_assign_new_column_w_loc(scalars_dfs):
pd.testing.assert_frame_equal(bf_result, pd_result)


def test_assign_new_column_w_setitem(scalars_dfs):
@pytest.mark.parametrize(
("scalar",),
[
(2.1,),
(None,),
],
)
def test_assign_new_column_w_setitem(scalars_dfs, scalar):
scalars_df, scalars_pandas_df = scalars_dfs
bf_df = scalars_df.copy()
pd_df = scalars_pandas_df.copy()
bf_df["new_col"] = 2
pd_df["new_col"] = 2
bf_df["new_col"] = scalar
pd_df["new_col"] = scalar
bf_result = bf_df.to_pandas()
pd_result = pd_df

# Convert default pandas dtypes `int64` to match BigQuery DataFrames dtypes.
pd_result["new_col"] = pd_result["new_col"].astype("Int64")
# Convert default pandas dtypes `float64` to match BigQuery DataFrames dtypes.
pd_result["new_col"] = pd_result["new_col"].astype("Float64")

pd.testing.assert_frame_equal(bf_result, pd_result)

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