rolling_std

statistics

Calculates rolling (moving) standard deviation over a window of rows

Syntax

rolling_std(column, window_size, min_periods?)

column (string)

Column name to calculate rolling std on

window_size (number)

Number of periods in the rolling window

min_periods (number) optional

Minimum number of observations required to have a result (defaults to window_size)

dataframe or array

DataFrame or Array with additional {column}_rolling_std field/column

3-period rolling standard deviation

Input:

.value | rolling_std(3)

Output:

[null, null, 1.2, 1.5, 1.1, ...]

7-day window, requires at least 5 values

Input:

.price | rolling_std(7, 5)

Output:

[null, null, null, null, 2.3, 2.8, 3.1, ...]

Analyze volatility

Input:

{ price: .price, volatility: (.price | rolling_std(30)) }

Output:

{"price": [100, 102, 98], "volatility": [null, null, 1.63]}

The rolling_std() function calculates rolling (moving) standard deviation over a sliding window of rows.

Use rolling_std() for analyzing volatility, detecting changes in variance over time, and monitoring data stability in time series.