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Version: Python

rolling_wavg_tick

rolling_wavg_tick creates a rolling weighted average in an update_by table operation using table ticks as the windowing unit. Ticks are row counts. The rolling weighted average can be calculated using forward and/or backward windows.

Syntax​

rolling_wavg_tick(wcol: str, cols: Union[str, list[str]], rev_ticks: int, fwd_ticks: int) -> UpdateByOperation

Parameters​

ParameterTypeDescription
wcolstr

The column containing the weight values.

colsUnion[str, list[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.

Example​

The following example performs an update_by on the source table using a rolling_wavg_tick operation.

from deephaven.updateby import rolling_wavg_tick
from deephaven import empty_table

source = empty_table(10).update(
    [
        "Letter = (i % 2 == 0) ? `A` : `B`",
        "X = randomInt(0, 40)",
        "Weight = randomInt(0, 40)",
    ]
)

result = source.update_by(
    ops=[rolling_wavg_tick(wcol="Weight", cols="X", rev_ticks=5, fwd_ticks=0)],
    by="Letter",
)