atoti.SiblingsScope#
- final class atoti.SiblingsScope#
Scope performing a “siblings” aggregation.
The aggregated value for each member of a given level in
hierarchy
is computed by aggregating all the members with the same parents (i.e. its siblings) with the given function.A siblings aggregation is appropriate for operations such as marginal aggregations (e.g. marginal VaR, marginal mean) for non-linear aggregation functions.
Example
Using this scope with
atoti.agg.sum()
to perform a “siblings” sum:>>> from datetime import date >>> df = pd.DataFrame( ... columns=["Date", "Quantity"], ... data=[ ... (date(2019, 7, 1), 15), ... (date(2019, 7, 2), 20), ... (date(2019, 7, 3), 30), ... (date(2019, 6, 1), 25), ... (date(2019, 6, 2), 15), ... (date(2018, 7, 1), 5), ... (date(2018, 7, 2), 10), ... (date(2018, 6, 1), 15), ... (date(2018, 6, 2), 5), ... ], ... ) >>> table = session.read_pandas(df, table_name="Siblings") >>> cube = session.create_cube(table, mode="manual") >>> h, l, m = cube.hierarchies, cube.levels, cube.measures >>> cube.create_date_hierarchy("Date", column=table["Date"]) >>> m["Quantity.SUM"] = tt.agg.sum(table["Quantity"]) >>> m["Siblings quantity"] = tt.agg.sum( ... m["Quantity.SUM"], scope=tt.SiblingsScope(h["Date"]) ... ) >>> cube.query( ... m["Quantity.SUM"], ... m["Siblings quantity"], ... levels=[l["Day"]], ... include_totals=True, ... ) Quantity.SUM Siblings quantity Year Month Day Total 140 140 2018 35 140 6 20 35 1 15 20 2 5 20 7 15 35 1 5 15 2 10 15 2019 105 140 6 40 105 1 25 40 2 15 40 7 65 105 1 15 65 2 20 65 3 30 65
- exclude_self: bool = False#
If
True
, the current member will not contribute to its aggregated value:>>> m["Siblings quantity excluding self"] = tt.agg.sum( ... m["Quantity.SUM"], ... scope=tt.SiblingsScope(h["Date"], exclude_self=True), ... ) >>> cube.query( ... m["Quantity.SUM"], ... m["Siblings quantity excluding self"], ... levels=[l["Day"]], ... include_totals=True, ... ) Quantity.SUM Siblings quantity excluding self Year Month Day Total 140 0 2018 35 105 6 20 15 1 15 5 2 5 15 7 15 20 1 5 10 2 10 5 2019 105 35 6 40 65 1 25 15 2 15 25 7 65 40 1 15 50 2 20 45 3 30 35
- hierarchy: HasIdentifier[HierarchyIdentifier] | HierarchyIdentifier#
The hierarchy along which the aggregation will be performed.