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Version: Python

weighted_avg

agg.weighted_avg returns an aggregator that computes the weighted average of values, within an aggregation group, for each input column.

Syntax​

weighted_avg(wcol: str, cols: Union[str, list[str]]) -> Aggregation

Parameters​

ParameterTypeDescription
wcolstr

The weight column for the calculation.

colsUnion[str, list[str]]

The source column(s) for the calculations.

  • ["X"] will output the weighted average of values in the X column for each group.
  • ["Y = X"] will output the weighted average of values in the X column for each group and rename it to Y.
  • ["X, A = B"] will output the weighted average of values in the X column for each group and the weighted average of values in the B column and rename it to A.
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 average of values, within an aggregation group, for each input column.

Examples​

In this example, agg.weighted_avg returns the weighted average 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_avg(wcol="Weight", cols=["Number"])], by=["X"])

In this example, agg.weighted_avg returns the weighted average of values of Number (renamed to WAvgNumber), 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_avg(wcol="Weight", cols=["WAvgNumber = Number"])], by=["X"]
)

In this example, agg.weighted_avg returns the weighted average of values of Number (renamed to WAvgNumber), as weighed by Weight and grouped by X and Y.

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_avg(wcol="Weight", cols=["WAvgNumber = Number"])], by=["X", "Y"]
)

In this example, agg.weighted_avg returns the weighted average of values of Number1 (renamed to WAvgNumber1), and the weighted average of values of Number2 (renamed to WAvgNumber2), both 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"]),
        int_col("Weight", [1, 2, 1, 3, 2, 1, 4, 1, 2]),
        int_col("Number1", [55, 76, 20, 130, 230, 50, 73, 137, 214]),
        int_col("Number2", [25, 14, 51, 23, 12, 15, 17, 72, 21]),
    ]
)

result = source.agg_by(
    [
        agg.weighted_avg(
            wcol="Weight", cols=["WAvgNumber1 = Number1", "WAvgNumber2 = Number2"]
        )
    ],
    by=["X"],
)

In this example, agg.weighted_avg returns the weighted average of values of Number (renamed to WAvgNumber), as weighed by Weight and grouped by X, and agg.avgreturns the total average of values of Number, as 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_avg(wcol="Weight", cols=["WAvgNumber = Number"]),
        agg.avg(cols=["Avg = Number"]),
    ],
    by=["X"],
)