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Version: Python

count_distinct

agg.count_distinct returns an aggregator that computes the number of distinct values, within an aggregation group, for each input column.

Syntax

count_distinct(cols: List[str]) -> Aggregation

Parameters

ParameterTypeDescription
colsList[str]

The source column(s) for the calculations.

  • ["X"] will output the number of distinct values in the X column for each group.
  • ["Y = X"] will output the number of distinct values in the X column for each group and rename it to Y.
  • ["X, A = B"] will output the number of distinct values in the X column for each group and the number of distinct values 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 number of distinct values, within an aggregation group, for each input column.

Examples

In this example, agg.count_distinct returns the number of distinct values of Y as grouped by X

from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg

source = new_table([
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "A", "A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "N", "M", "N", "N", "M", "O", "P", "N", "M", "N", "M", "N", "N", "M", "O", "P", "N"]),
int_col("Number", [55, 76, 55, 130, 230, 50, 76, 137, 214, 55, 76, 55, 130, 230, 50, 76, 137, 214]),
])

result = source.agg_by([agg.count_distinct(cols=["Y"])], by=["X"])

In this example, agg.count_distinct returns the number of distinct values of Y (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

source = new_table([
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "A", "A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "N", "M", "N", "N", "M", "O", "P", "N", "M", "N", "M", "N", "N", "M", "O", "P", "N"]),
int_col("Number", [55, 76, 55, 130, 230, 50, 76, 137, 214, 55, 76, 55, 130, 230, 50, 76, 137, 214]),
])

result = source.agg_by([agg.count_distinct(cols=["Z = Y"])], by=["X"])

In this example, agg.count_distinct returns the number of distinct values of Y and the number of distinct values of Number, as grouped by X.

from deephaven import new_table
from deephaven.column import string_col, int_col, double_col
from deephaven import agg

source = new_table([
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "A", "A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "N", "M", "N", "N", "M", "O", "P", "N", "M", "N", "M", "N", "N", "M", "O", "P", "N"]),
int_col("Number", [55, 76, 55, 130, 230, 50, 76, 137, 214, 55, 76, 55, 130, 230, 50, 76, 137, 214]),
])

result = source.agg_by([agg.count_distinct(cols=["Y", "Number"])],by=["X"])

In this example, agg.count_distinct returns the number of distinct values of Number, 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

source = new_table([
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "A", "A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "N", "M", "N", "N", "M", "O", "P", "N", "M", "N", "M", "N", "N", "M", "O", "P", "N"]),
int_col("Number", [55, 76, 55, 130, 230, 50, 76, 137, 214, 55, 76, 55, 130, 230, 50, 76, 137, 214]),
])

result = source.agg_by([agg.count_distinct(cols=["Number"])], by=["X","Y"])

In this example, agg.count_distinct returns the number of distinct values of Number, 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

source = new_table([
string_col("X", ["A", "B", "A", "C", "B", "A", "B", "B", "A", "A", "B", "A", "C", "B", "A", "B", "B", "C"]),
string_col("Y", ["M", "N", "M", "N", "N", "M", "O", "P", "N", "M", "N", "M", "N", "N", "M", "O", "P", "N"]),
int_col("Number", [55, 76, 55, 130, 230, 50, 76, 137, 214, 55, 76, 55, 130, 230, 50, 76, 137, 214]),
])

result = source.agg_by([\
agg.count_distinct(cols=["FirstNumber = Number"]),\
agg.last(cols=["LastNumber = Number"])], \
by=["X"])