atoti.agg.square_sum()

@overload
atoti.agg.square_sum(
operand: LevelOrVariableColumnConvertible,
/,
) → MeasureDefinition

@overload
atoti.agg.square_sum(
    operand: VariableMeasureConvertible,
    /,
    *,
    scope: CumulativeScope | SiblingsScope | OriginScope,
) → MeasureDefinition

Return a measure equal to the sum of the square of the passed measure across the specified scope.

Parameters

operand

The measure or table column to aggregate.

scope

The aggregation scope.

>>> df = pd.DataFrame(
...     columns=["id", "Quantity", "Price", "Other"],
...     data=[
...         ("a1", 100, 12.5, 1),
...         ("a2", 10, 43, 2),
...         ("a3", 1000, 25.9, 2),
...     ],
... )
>>> table = session.read_pandas(
...     df,
...     keys=["id"],
...     table_name="Product",
... )
>>> table.head().sort_index()
    Quantity  Price  Other
id
a1       100   12.5      1
a2        10   43.0      2
a3      1000   25.9      2
>>> cube = session.create_cube(table)
>>> m = cube.measures
    >>> m["Other.SQUARE_SUM"] = tt.agg.square_sum(table["Other"])
    >>> cube.query(m["Other.SQUARE_SUM"])
      Other.SQUARE_SUM
    0                9