Trait polars::prelude::RollingAgg

pub trait RollingAgg {
    fn rolling_mean(
        &self,
        options: RollingOptionsImpl<'_>
    ) -> Result<Series, PolarsError>;
    fn rolling_sum(
        &self,
        options: RollingOptionsImpl<'_>
    ) -> Result<Series, PolarsError>;
    fn rolling_min(
        &self,
        options: RollingOptionsImpl<'_>
    ) -> Result<Series, PolarsError>;
    fn rolling_max(
        &self,
        options: RollingOptionsImpl<'_>
    ) -> Result<Series, PolarsError>;
    fn rolling_median(
        &self,
        options: RollingOptionsImpl<'_>
    ) -> Result<Series, PolarsError>;
    fn rolling_quantile(
        &self,
        quantile: f64,
        interpolation: QuantileInterpolOptions,
        options: RollingOptionsImpl<'_>
    ) -> Result<Series, PolarsError>;
    fn rolling_var(
        &self,
        options: RollingOptionsImpl<'_>
    ) -> Result<Series, PolarsError>;
    fn rolling_std(
        &self,
        options: RollingOptionsImpl<'_>
    ) -> Result<Series, PolarsError>;
}

Required Methods

fn rolling_mean(
    &self,
    options: RollingOptionsImpl<'_>
) -> Result<Series, PolarsError>

Apply a rolling mean (moving mean) 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 weights vector. The resulting values will be aggregated to their mean.

fn rolling_sum(
    &self,
    options: RollingOptionsImpl<'_>
) -> Result<Series, PolarsError>

Apply a rolling sum (moving sum) 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 weights vector. The resulting values will be aggregated to their sum.

fn rolling_min(
    &self,
    options: RollingOptionsImpl<'_>
) -> Result<Series, PolarsError>

Apply a rolling min (moving min) 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 weights vector. The resulting values will be aggregated to their min.

fn rolling_max(
    &self,
    options: RollingOptionsImpl<'_>
) -> Result<Series, PolarsError>

Apply a rolling max (moving max) 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 weights vector. The resulting values will be aggregated to their max.

fn rolling_median(
    &self,
    options: RollingOptionsImpl<'_>
) -> Result<Series, PolarsError>

Apply a rolling median (moving median) 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 weighted according to the weights vector.

fn rolling_quantile(
    &self,
    quantile: f64,
    interpolation: QuantileInterpolOptions,
    options: RollingOptionsImpl<'_>
) -> Result<Series, PolarsError>

Apply a rolling quantile (moving quantile) 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 weighted according to the weights vector.

fn rolling_var(
    &self,
    options: RollingOptionsImpl<'_>
) -> Result<Series, PolarsError>

Apply a rolling var (moving var) 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 weights vector. The resulting values will be aggregated to their var.

fn rolling_std(
    &self,
    options: RollingOptionsImpl<'_>
) -> Result<Series, PolarsError>

Apply a rolling std (moving std) 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 weights vector. The resulting values will be aggregated to their std.

Implementors