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Version: Python

count_by

count_by returns the number of rows for each group.

Syntax

table.count_by(count_column_name: str, by: List[str]=[])

Parameters

ParameterTypeDescription
count_column_nameString

The name of the output column containing the count.

by optionalList[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"])