luth2 commented on code in PR #45823:
URL: https://github.com/apache/superset/pull/45823#discussion_r4431524559
##########
superset/utils/pandas_postprocessing/resample.py:
##########
@@ -240,10 +240,19 @@ def resample( # pylint: disable=too-many-arguments
_validate_projected_rows(df.index.min(), df.index.max(), rule)
if method == "asfreq" and fill_value is not None:
+ string_columns = [
+ column
+ for column in df.columns
+ if isinstance(df[column].dtype, pd.StringDtype)
+ ]
+ if len(string_columns):
+ df = df.astype(dict.fromkeys(string_columns, object))
_df = df.resample(rule).asfreq(fill_value=fill_value)
_df = _df.fillna(fill_value)
elif method == "linear":
- _df = df.resample(rule).interpolate()
+ _df = df.resample(rule).asfreq()
Review Comment:
Validated as fixed; audit commit e8e1b5cf85. Linear resampling includes
datetime and timezone-aware datetime columns alongside numeric columns. The
regression checks the missing middle datetime for naive and timezone-aware
values; the complete resample module passed on Python 3.11/pandas 3.0.6 and
Python 3.15/pandas 3.1.0.
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