max_
agg.max_
returns an aggregator that computes the maximum value, within an aggregation group, for each input column.
max
is a reserved Python keyword, so an underscore is used to maintain Python conventions.
Syntax
max_(cols: Union[str, list[str]]) -> Aggregation
Parameters
Parameter | Type | Description |
---|---|---|
cols | Union[str, list[str]] | The source column(s) for the calculations.
|
If an aggregation does not rename the resulting column, the aggregation column will appear in the output table, not the input column. If multiple aggregations on the same column do not rename the resulting columns, an error will result, because the aggregations are trying to create multiple columns with the same name. For example, in table.agg_by([agg.sum_(cols=[“X”]), agg.avg(cols=["X"])
, both the sum and the average aggregators produce column X
, which results in an error.
Returns
An aggregator that computes the maximum value, within an aggregation group, for each input column.
Examples
In this example, agg.max_
returns the maximum Y
value as grouped by X
.
from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg as agg
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.agg_by([agg.max_(cols=["Y"])], by=["X"])
- source
- result
In this example, agg.max_
returns the maximum Y
value (renamed to Z
), as grouped by X
.
from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg as agg
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.agg_by([agg.max_(cols=["Z = Y"])], by=["X"])
- source
- result
In this example, agg.max_
returns the maximum Y
string and maximum Number
integer as grouped by X
.
from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg as agg
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.agg_by([agg.max_(cols=["Y", "Number"])], by=["X"])
- source
- result
In this example, agg.max_
returns the maximum Number
integer, as grouped by X
and Y
.
from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg as agg
source = new_table(
[
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "P", "O", "N", "P", "M", "O", "P", "N"]),
int_col("Number", [55, 76, 20, 130, 230, 50, 73, 137, 214]),
]
)
result = source.agg_by([agg.max_(cols=["Number"])], by=["X", "Y"])
- source
- result
In this example, agg.max_
returns the maximum Number
integer, and agg.last
returns the last Number
integer, as grouped by X
.
from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg as agg
source = new_table(
[
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "P", "O", "N", "P", "M", "O", "P", "N"]),
int_col("Number", [55, 76, 20, 130, 230, 50, 73, 137, 214]),
]
)
result = source.agg_by(
[agg.max_(cols=["MaxNumber = Number"]), agg.last(cols=["LastNumber = Number"])],
by=["X"],
)
- source
- result