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Version: Python

rolling_min_tick

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

Syntax

rolling_min_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 minimum 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 three rolling_min_tick operations. Each argument uses different rev_ticks and fwd_ticks values to show how they affect the output.

from deephaven.updateby import rolling_min_tick
from deephaven import empty_table

source = empty_table(10).update(
["Letter = (i % 2 == 0) ? `A` : `B`", "X = randomInt(0, 100)"]
)

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

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