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 | The name of the output column containing the count. |
by optional | Union[str, list[str]] | The column(s) by which to group data.
|
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")
- source
- result
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"])
- source
- result
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"])
- source
- result