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Version: Python

first

agg.first returns an aggregator that computes the first value, within an aggregation group, for each input column.

Syntax​

first(cols: Union[str, list[str]]) -> Aggregation

Parameters​

ParameterTypeDescription
colsUnion[str, list[str]]

The source column(s) for the calculations.

  • ["X"] will output the first value in the X column for each group.
  • ["Y = X"] will output the first value in the X column for each group and rename it to Y.
  • ["X, A = B"] will output the first value in the X column for each group and the first value in the B column while renaming it to A.
caution

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 first value, within an aggregation group, for each input column.

Examples​

In this example, agg.first returns the first 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.first(cols=["Y"])], by=["X"])

In this example, agg.first returns the first 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.first(cols=["Z = Y"])], by=["X"])

In this example, agg.first returns the first Y string and first 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.first(cols=["Y", "Number"])], by=["X"])

In this example, agg.first returns the first 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", "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.first(cols=["Number"])], by=["X", "Y"])

In this example, agg.first returns the first 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.first(cols=["FirstNumber = Number"]), agg.last(cols=["LastNumber = Number"])],
    by=["X"],
)