ktmud commented on a change in pull request #10286:
URL:
https://github.com/apache/incubator-superset/pull/10286#discussion_r452922238
##########
File path: superset/charts/schemas.py
##########
@@ -395,6 +395,19 @@ class
ChartDataSortOptionsSchema(ChartDataPostProcessingOperationOptionsSchema):
aggregates = ChartDataAggregateConfigField()
+class
ChartDataContributionOptionsSchema(ChartDataPostProcessingOperationOptionsSchema):
+ """
+ Contribution operation config.
+ """
+
+ orientation = fields.String(
+ description="Should cell values be calculated across the row or
column.",
+ required=True,
+ validate=validate.OneOf(choices=("row", "column",)),
Review comment:
Can these two also based on the enum?
##########
File path: superset/utils/pandas_postprocessing.py
##########
@@ -517,3 +518,29 @@ def _parse_location(location: str) -> Tuple[float, float,
float]:
return _append_columns(df, geodetic_df, columns)
except ValueError:
raise QueryObjectValidationError(_("Invalid geodetic string"))
+
+
+def contribution(
+ df: DataFrame, orientation: PostProcessingContributionOrientation
+) -> DataFrame:
+ """
+ Calculate cell contibution to row/column total.
+
+ :param df: DataFrame containing all-numeric data (temporal column ignored)
+ :param orientation: calculate by dividing cell with row/column total
+ :return: DataFrame with contributions, with temporal column at beginning
if present
+ """
+ temporal_series: Optional[Series] = None
+ contribution_df = df.copy()
+ if DTTM_ALIAS in df.columns:
+ temporal_series = cast(Series, contribution_df.pop(DTTM_ALIAS))
+
+ if orientation == PostProcessingContributionOrientation.ROW:
+ contribution_dft = contribution_df.T
+ contribution_df = (contribution_dft / contribution_dft.sum()).T
+ else:
+ contribution_df = contribution_df / contribution_df.sum()
Review comment:
Could probably utilize "axis" parameter for `sum`
##########
File path: superset/utils/pandas_postprocessing.py
##########
@@ -517,3 +518,29 @@ def _parse_location(location: str) -> Tuple[float, float,
float]:
return _append_columns(df, geodetic_df, columns)
except ValueError:
raise QueryObjectValidationError(_("Invalid geodetic string"))
+
+
+def contribution(
+ df: DataFrame, orientation: PostProcessingContributionOrientation
+) -> DataFrame:
Review comment:
Maybe it makes more things to keep things simple, but is it possible to
allow specifying which column(s) to compute on? I could imagine this operator
being used to support "percent metrics" in table charts and it’ll need the
ability to select specific columns.
Maybe the API can be something like this
```
{
# compute row wise contribution and override the columns
"columns": ["foo", "bar"],
"orientation": "row"
}
{
# compute column wise computation and insert new columns
"columns": ["pct_abc"],
"sources": ["abc"]
}
```
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