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Version: Python

group_by

group_by groups column content into vectors.

Syntax​

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

Parameters​

ParameterTypeDescription
by optionalUnion[str, list[str]]

The column(s) by which to group data.

  • [] the content of each column is grouped into its own vector (default).
  • ["X"] will output an array of values for each group in column X.
  • ["X", "Y"] will output a vector of values for each group designated from the X and Y columns.

Returns​

A new table containing grouping columns and grouped data. Column content is grouped into vectors.

Examples​

In this example, group_by creates a vector of values for each column.

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.group_by()

In this example, group_by creates a vector of values, as grouped by X.

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.group_by(by=["X"])

In this example, group_by creates a vector of values, 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.group_by(by=["X", "Y"])