rolling_avg_time

rolling_avg_time creates a simple moving average in an update_by table operation using time as the windowing unit. Time can be specified as integer numbers of nanoseconds or strings. The moving average can be calculated using forward and/or backward windows.

$SMA = \frac{\sum_{1}^{n}x_{i}}{n}$

Where:

• $n$ is the number window size in ticks
• $x_{i}$ is the current value

For a time-based SMA, n is the number of observations in the window, determined by fwd_time and rev_time.

Syntax

Parameters

Parameter	Type	Description
ts_col	str	The name of the column containing timestamps.
cols	list[str]	The column(s) to be operated on. These can include expressions to rename the output (e.g., NewCol = Col). If None, the rolling average is calculated for all applicable columns.
rev_time	Union[int,str]	The look-behind window size. This can be expressed as an integer in nanoseconds or a string duration, e.g., "PT00:00:00.001" or "PTnHnMnS", where H is hour, M is minute, and S is second.
fwd_time	Union[int,str]	The look-forward window size. This can be expressed as an integer in nanoseconds or a string duration, e.g., "PT00:00:00.001" or "PTnHnMnS", where H is hour, M is minute, and S is second.

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_avg_time operations. Each uses different rev_time and fwd_time values to show how they affect the output.

Related documentation

• How to use update_by
• Create an empty table
• Time in Deephaven
• Ternary conditional operator
• update
• update_by
• Javadoc
• Pydoc