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Version: Python

rolling_sum_tick

rolling_sum_tick creates a tick-based (row-based) windowed sum operator to be used in an update_by table operation. Data is windowed by a number of reverse and forward ticks (rows) relative to the current row, and the sum of the window is calculated.

Syntax​

rolling_sum_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). If None, the rolling sum 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. rev_ticks is includes the current row, so rev_ticks=0 means that the window starts at 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. fwd_ticks is not inclusive of the current row, so fwd_ticks=1 means that the window ends at the current row.

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 three rolling_sum_tick operations. Each operation gives varying rev_ticks and fwd_ticks values to show how they affect the output. The windows for each operation are as follows:

  • op_before: The window contains two rows. It starts two rows before the current row, and ends at the row before the current row.
  • op_after: The window contains three rows. It starts one row after the current row, and ends three rows after the current row.
  • op_middle: The window contains three rows. It starts one row before the current row, and ends one row ahead of the current row.
from deephaven.updateby import rolling_sum_tick
from deephaven import empty_table

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

op_before = rolling_sum_tick(cols=["WindowBeforeX = X"], rev_ticks=3, fwd_ticks=-1)
op_after = rolling_sum_tick(cols=["WindowAfterX = X"], rev_ticks=-1, fwd_ticks=3)
op_middle = rolling_sum_tick(cols=["WindowMiddleX = X"], rev_ticks=2, fwd_ticks=1)

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