sadpandajoe commented on code in PR #43693:
URL: https://github.com/apache/superset/pull/43693#discussion_r3939265596
##########
superset/utils/pandas_postprocessing/pivot.py:
##########
@@ -187,6 +187,25 @@ def _restore_dropped_metric_columns(
return df
+def _fill_dimension_column(df: DataFrame, col: str, fill_value: str) -> None:
+ """Fill missing values in a groupby dimension column before pivoting.
+
+ Handles categorical dtypes (adding fill_value to categories) and datetime
+ dtypes (converting to string representation with fill_value for NaT) to
prevent
+ dtype errors and preserve NULL/NaN/NaT keys through pivot_table().
+ """
+ s = df[col]
+ if isinstance(s.dtype, pd.CategoricalDtype) and fill_value not in
s.cat.categories:
Review Comment:
Adding the fill category even when this dimension has no missing values
makes `pivot_table()` materialize an unobserved `<NULL>` group (or column)
under its default `observed=False`, so ordinary categorical pivots gain a
zero-valued bucket that was not in the input. Could this only add the category
when `s.isna().any()`?
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