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Version: Python

group_by

group_by groups column content into arrays.

Syntax

table.group_by(by: List[str]=[])

Parameters

ParameterTypeDescription
by optionalList[str]

The column(s) by which to group data.

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

Examples

In this example, group_by creates an array 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 an array 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 an array 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"])