count_by

count_by returns the number of rows for each group.

Syntax

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

Parameters

Parameter Type Description

col

str

Parameter	Type	Description
col	str	The name of the output column containing the count.
by optional	Union[str, list[str]]	The column(s) by which to group data. `[]` returns the total count of rows in the table (default). `["X"]` will output the count of each group in column `X`. `["X", "Y"]` will output the count of each group designated from the `X` and `Y` columns.

The name of the output column containing the count.

by optional

Union[str, list[str]]

The column(s) by which to group data.

[] returns the total count of rows in the table (default).
["X"] will output the count of each group in column X.
["X", "Y"] will output the count of each group designated from the X and Y columns.

Returns

A new table containing the number of rows for each group.

Examples

In this example, count_by returns the number of rows in the table and stores that in a new column, Count.

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.count_by("Count")

In this example, count_by returns the number of rows in the table as grouped by X and stores that in a new column, Count.

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.count_by("Count", by=["X"])

In this example, count_by returns the number of rows in the table as grouped by X and Y, and stores that in a new column Count.

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.count_by("Count", by=["X", "Y"])

count_by

Syntax

Parameters

Returns

Examples

Related documentation