Rolling variance
Description
Compute the rolling (= moving) variance over the values in this array. A
window of length window_size
will traverse the array. The
values that fill this window will (optionally) be multiplied with the
weights given by the weight
vector.
Usage
<Expr>$rolling_var(
window_size,
weights = NULL,
min_periods = NULL,
...,
center = FALSE,
ddof = 1
)
Arguments
window_size
|
Integer specifying the length of the window. |
weights
|
An optional slice with the same length as the window that will be multiplied elementwise with the values in the window. |
min_periods
|
The number of values in the window that should be non-null before
computing a result. If NULL , it will be set equal to window
size.
|
…
|
Ignored. |
center
|
Set the labels at the center of the window |
ddof
|
An integer representing "Delta Degrees of Freedom": the divisor used in
the calculation is N - ddof , where N
represents the number of elements. By default ddof is 1 .
|
Details
If you want to compute multiple aggregation statistics over the same
dynamic window, consider using
$rolling()
this method can cache
the window size computation.
Value
Expr
Examples
library("polars")
pl$DataFrame(a = c(1, 3, 2, 4, 5, 6))$
with_columns(roll_var = pl$col("a")$rolling_var(window_size = 2))
#> shape: (6, 2)
#> ┌─────┬──────────┐
#> │ a ┆ roll_var │
#> │ --- ┆ --- │
#> │ f64 ┆ f64 │
#> ╞═════╪══════════╡
#> │ 1.0 ┆ null │
#> │ 3.0 ┆ 2.0 │
#> │ 2.0 ┆ 0.5 │
#> │ 4.0 ┆ 2.0 │
#> │ 5.0 ┆ 0.5 │
#> │ 6.0 ┆ 0.5 │
#> └─────┴──────────┘