avg_by

avg_by returns the average (mean) of each non-key column for each group. Null values are ignored.

Caution

Applying this aggregation to a column where the average can not be computed will result in an error. For example, the average is not defined for a column of string values.

Syntax

table.avg_by(by: Union[str, list[str]]) -> Table

Parameters

Parameter Type Description

Union[str, list[str]]

Parameter	Type	Description
by	Union[str, list[str]]	The column(s) by which to group data. `[]` returns total average for all non-key columns (default). `["X"]` will output the total average of each group in column `X`. `["X", "Y"]` will output the total average of each group designated from the `X` and `Y` columns.

The column(s) by which to group data.

[] returns total average for all non-key columns (default).
["X"] will output the total average of each group in column X.
["X", "Y"] will output the total average of each group designated from the X and Y columns.

Returns

A new table containing the average for each group.

Examples

In this example, avg_by returns the average value for the table. Because an average can not be computed for the string columns X and Y, these columns are dropped before applying avg_by.

from deephaven import new_table
from deephaven.column import string_col, int_col

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]),
    ]
)

result = source.drop_columns(cols=["X", "Y"]).avg_by()

In this example, avg_by returns the average value, as grouped by X. Because an average can not be computed for the string column Y, this column is dropped before applying avg_by.

from deephaven import new_table
from deephaven.column import string_col, int_col

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]),
    ]
)

result = source.drop_columns(cols=["Y"]).avg_by(by=["X"])

In this example, avg_by returns the average value, as grouped by X and Y.

from deephaven import new_table
from deephaven.column import string_col, int_col

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]),
    ]
)

result = source.avg_by(by=["X", "Y"])

avg_by

Syntax

Parameters

Returns

Examples

Related documentation