weighted_sum
agg.weighted_sum
returns an aggregator that computes the weighted sum of values, within an aggregation group, for each input column.
Syntax
weighted_sum(wcol: str, cols: List[str]) > Aggregation
Parameters
Parameter  Type  Description 

wcol  String  The weight column for the calculation. 
cols  List[str]  The source column(s) for the calculations.

caution
If an aggregation does not rename the resulting column, the aggregation column will appear in the output table, not the input column. If multiple aggregations on the same column do not rename the resulting columns, an error will result, because the aggregations are trying to create multiple columns with the same name. For example, in table.agg_by([agg.sum_(cols=[“X”]), agg.avg(cols=["X"])
, both the sum and the average aggregators produce column X
, which results in an error.
Returns
An aggregator that computes the weighted sum of values, within an aggregation group, for each input column.
Examples
In this example, agg.weighted_sum
returns the weighted sum of values of Number
, as weighed by Weight
and grouped by X
.
from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg as agg
source = new_table([
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "N", "O", "N", "P", "M", "O", "P", "M"]),
int_col("Number", [55, 76, 20, 130, 230, 50, 73, 137, 214]),
int_col("Weight", [1, 2, 1, 3, 2, 1, 4, 1, 2]),
])
result = source.agg_by([agg.weighted_sum(wcol="Weight", cols=["Number"])], by=["X"])
 source
 result
In this example, agg.weighted_sum
returns the weighted sum of values of Number
(renamed to WSumNumber
), as weighed by Weight
and grouped by X
.
from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg as agg
source = new_table([
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "N", "O", "N", "P", "M", "O", "P", "M"]),
int_col("Number", [55, 76, 20, 130, 230, 50, 73, 137, 214]),
int_col("Weight", [1, 2, 1, 3, 2, 1, 4, 1, 2]),
])
result = source.agg_by([agg.weighted_sum(wcol="Weight", cols=["WSumNumber = Number"])], by=["X"])
 source
 result
In this example, agg.weighted_sum
returns the weighted sum of values of Number
(renamed to WSumNumber
), as weighed by Weight
and grouped by X
.
from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg as agg
source = new_table([
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "N", "O", "N", "P", "M", "O", "P", "M"]),
int_col("Number", [55, 76, 20, 130, 230, 50, 73, 137, 214]),
int_col("Weight", [1, 2, 1, 3, 2, 1, 4, 1, 2]),
])
result = source.agg_by([agg.weighted_sum(wcol="Weight", cols=["WSumNumber = Number"]),agg.sum_(cols=["Sum = Number"])], by=["X"])
 source
 result