codeant-ai-for-open-source[bot] commented on code in PR #45823:
URL: https://github.com/apache/superset/pull/45823#discussion_r4404144860
##########
superset/commands/dataset/importers/v1/utils.py:
##########
@@ -770,7 +770,7 @@ def _convert_temporal_columns(df: pd.DataFrame, dtype:
dict[str, Any]) -> None:
for column_name, sqla_type in dtype.items():
if isinstance(sqla_type, (Date, DateTime)):
try:
- df[column_name] = pd.to_datetime(df[column_name])
+ df[column_name] =
pd.to_datetime(df[column_name]).dt.as_unit("ns")
Review Comment:
✅ **CodeAnt verified this suggestion was addressed in subsequent commits and
marked this thread resolved** as of `34048a8`.
The code checks that `pd.to_datetime` returned a datetime dtype before
calling `.dt.as_unit`. Other results fall through to per-value conversion
instead of raising on `.dt`.
<sub>If that's not right, unresolve this thread and CodeAnt will leave it
open.</sub>
<!-- codeant-auto-resolve-reply -->
##########
superset/utils/pandas_postprocessing/pivot.py:
##########
@@ -404,8 +404,6 @@ def pivot( # pylint: disable=too-many-arguments # noqa:
C901
df = _apply_show_values_as(df, percent_mode)
if combine_value_with_metric:
- # dropna=False preserves restored all-NaN metric rows that would
otherwise
- # be silently dropped by stack's default dropna=True behavior.
- df = df.stack(level=0, dropna=False).unstack()
+ df = df.stack(level=0, future_stack=True).unstack()
Review Comment:
✅ **CodeAnt verified this suggestion was addressed in subsequent commits and
marked this thread resolved** as of `34048a8`.
The columns are reshaped by reordering and sorting the MultiIndex levels,
rather than stacking and unstacking, which would recreate absent pairs.
<sub>If that's not right, unresolve this thread and CodeAnt will leave it
open.</sub>
<!-- codeant-auto-resolve-reply -->
##########
superset/utils/pandas_postprocessing/boxplot.py:
##########
@@ -135,7 +135,7 @@ def outliers(series: Series) -> set[float]:
# nanpercentile needs numeric values, otherwise the isnan function
# that's used in the underlying function will fail
for column in metrics:
- if is_object_dtype(df[column]):
- df.loc[:, column] = to_numeric(df[column], errors="coerce")
+ if is_object_dtype(df[column]) or is_string_dtype(df[column]):
+ df[column] = to_numeric(df[column], errors="coerce")
Review Comment:
✅ **CodeAnt verified this suggestion was addressed in subsequent commits and
marked this thread resolved** as of `34048a8`.
String/object metric columns are converted with
`to_numeric(errors="raise")`; malformed values now raise
`InvalidPostProcessingError` instead of being silently turned into NaN.
<sub>If that's not right, unresolve this thread and CodeAnt will leave it
open.</sub>
<!-- codeant-auto-resolve-reply -->
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