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Version: Python

rolling_count_tick

rolling_count_tick creates an update_by table operation that keeps a count of the number of values that exist in a rolling window, using using table ticks as the windowing unit. Ticks are row counts. The rolling count can be calculated using forward and/or backward windows.

Syntax​

rolling_count_tick(cols: list[str], rev_ticks: int, fwd_ticks: int) -> UpdateByOperation

Parameters​

ParameterTypeDescription
colslist[str]

The column(s) to be operated on. These can include expressions to rename the output (e.g., NewCol = Col). When left empty, the rolling count is calculated for all applicable columns.

rev_ticksint

The look-behind window size in rows. If positive, it defines the maximum number of rows before the current row that will be used. If negative, it defines the minimum number of rows after the current row that will be used. Includes the current row.

fwd_ticksint

The look-forward window size in rows. If positive, it defines the maximum number of rows after the current row that will be used. If negative, it defines the minimum number of rows before the current row that will be used.

Returns​

An UpdateByOperation to be used in an update_by table operation.

Examples​

The following example performs an update_by on the source table using rolling_count_tick.

from deephaven.updateby import rolling_count_tick
from deephaven import new_table
from deephaven.constants import NULL_INT
from deephaven.column import int_col, string_col

source = new_table(
    cols=[
        string_col("Letter", ["A", "B", "A", "B", "A", "B", "A", "B", "A", "B"]),
        int_col("X", [1, 3, NULL_INT, 3, 4, NULL_INT, NULL_INT, 5, NULL_INT, 4]),
    ]
)

op_before = rolling_count_tick(cols=["OpBefore = X"], rev_ticks=3, fwd_ticks=-1)
op_after = rolling_count_tick(cols=["OpAfter = X"], rev_ticks=-1, fwd_ticks=3)
op_middle = rolling_count_tick(cols=["OpMiddle = X"], rev_ticks=1, fwd_ticks=1)

result = source.update_by(ops=[op_before, op_after, op_middle], by="Letter")