8000 fix: Product operation produces float result for all input types by TrevorBergeron · Pull Request #501 · googleapis/python-bigquery-dataframes · GitHub
[go: up one dir, main page]
Skip to content

fix: Product operation produces float result for all input types #501

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
gcf-merge-on-green merged 8 commits into from
Mar 26, 2024
Merged

fix: Product operation produces float result for all input types #501

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
168ebb8
fix: Product operation produces float result for all input types
TrevorBergeron Mar 22, 2024
e1c76a2
simplify output_type def
TrevorBergeron Mar 22, 2024
c3b7b49
Merge remote-tracking branch 'github/main' into float_prod
TrevorBergeron Mar 23, 2024
243fe08
amend test_groupby_prod to expect float
TrevorBergeron Mar 23, 2024
a9761e2
Merge remote-tracking branch 'github/main' into float_prod
TrevorBergeron Mar 25, 2024
9d30b05
update df.cumprod doc example
TrevorBergeron Mar 25, 2024
10BC0 e53713a
Merge branch 'main' into float_prod
TrevorBergeron Mar 26, 2024
78ab6b4
Merge branch 'main' into float_prod
TrevorBergeron Mar 26, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion bigframes/core/compile/aggregate_compiler.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -190,7 +190,7 @@ def _(
.else_(magnitude * pow(-1, negative_count_parity))
.end()
)
return float_result.cast(column.type()) # type: ignore
return float_result


@compile_unary_agg.register
Expand Down
5 changes: 1 addition & 4 deletions bigframes/operations/aggregations.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -139,10 +139,7 @@ class ProductOp(UnaryAggregateOp):
name: ClassVar[str] = "product"

def output_type(self, *input_types: dtypes.ExpressionType):
if pd.api.types.is_bool_dtype(input_types[0]):
return dtypes.INT_DTYPE
else:
return input_types[0]
return dtypes.FLOAT_DTYPE


@dataclasses.dataclass(frozen=True)
Expand Down
3 changes: 1 addition & 2 deletions tests/system/small/test_groupby.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -228,8 +228,7 @@ def test_dataframe_groupby_multi_sum(
(lambda x: x.cumsum(numeric_only=True)),
(lambda x: x.cummax(numeric_only=True)),
(lambda x: x.cummin(numeric_only=True)),
# pandas 2.2 uses floating point for cumulative product even for
# integer inputs.
# Pre-pandas 2.2 doesn't always proeduce float.
(lambda x: x.cumprod().astype("Float64")),
(lambda x: x.shift(periods=2)),
],
Expand Down
2 changes: 1 addition & 1 deletion tests/system/small/test_series.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1481,7 +1481,7 @@ def test_groupby_prod(scalars_dfs):
bf_series = scalars_df[col_name].groupby(scalars_df["int64_col"]).prod()
pd_series = (
scalars_pandas_df[col_name].groupby(scalars_pandas_df["int64_col"]).prod()
)
).astype(pd.Float64Dtype())
# TODO(swast): Update groupby to use index based on group by key(s).
bf_result = bf_series.to_pandas()
assert_series_equal(
Expand Down
8 changes: 4 additions & 4 deletions third_party/bigframes_vendored/pandas/core/frame.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4416,10 +4416,10 @@ def cumprod(self) -> DataFrame:
[3 rows x 2 columns]

>>> df.cumprod()
A B
0 3 1
1 3 2
2 6 6
A B
0 3.0 1.0
1 3.0 2.0
2 6.0 6.0
<BLANKLINE>
[3 rows x 2 columns]

Expand Down
0