Trait polars_core::chunked_array::ops::ChunkWindow [−][src]
pub trait ChunkWindow { fn rolling_sum(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self>
where
Self: Sized, { ... } fn rolling_mean(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self>
where
Self: Sized, { ... } fn rolling_min(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self>
where
Self: Sized, { ... } fn rolling_max(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self>
where
Self: Sized, { ... } }
Expand description
Rolling window functions
Provided methods
fn rolling_sum(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self> where
Self: Sized,
[src]
fn rolling_sum(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self> where
Self: Sized,
[src]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 weight
vector. the resulting
values will be aggregated to their sum.
Arguments
window_size
- The length of the window.weight
- An optional slice with the same length of the window that will be multiplied elementwise with the values in the window.ignore_null
- Toggle behavior of aggregation regarding null values in the window.true
-> Null values will be ignored.false
-> Any Null in the window leads to a Null in the aggregation result.
fn rolling_mean(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self> where
Self: Sized,
[src]
fn rolling_mean(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self> where
Self: Sized,
[src]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 weight
vector. The resulting
values will be aggregated to their mean.
Arguments
window_size
- The length of the window.weight
- An optional slice with the same length of the window that will be multiplied elementwise with the values in the window.ignore_null
- Toggle behavior of aggregation regarding null values in the window.true
-> Null values will be ignored.false
-> Any Null in the window leads to a Null in the aggregation result.min_periods
- Amount of elements in the window that should be filled before computing a result.
fn rolling_min(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self> where
Self: Sized,
[src]
fn rolling_min(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self> where
Self: Sized,
[src]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 weight
vector. The resulting
values will be aggregated to their min.
Arguments
window_size
- The length of the window.weight
- An optional slice with the same length of the window that will be multiplied elementwise with the values in the window.ignore_null
- Toggle behavior of aggregation regarding null values in the window.true
-> Null values will be ignored.false
-> Any Null in the window leads to a Null in the aggregation result.min_periods
- Amount of elements in the window that should be filled before computing a result.
fn rolling_max(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self> where
Self: Sized,
[src]
fn rolling_max(
&self,
_window_size: u32,
_weight: Option<&[f64]>,
_ignore_null: bool,
_min_periods: u32
) -> Result<Self> where
Self: Sized,
[src]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 weight
vector. The resulting
values will be aggregated to their max.
Arguments
window_size
- The length of the window.weight
- An optional slice with the same length of the window that will be multiplied elementwise with the values in the window.ignore_null
- Toggle behavior of aggregation regarding null values in the window.true
-> Null values will be ignored.false
-> Any Null in the window leads to a Null in the aggregation result.min_periods
- Amount of elements in the window that should be filled before computing a result.
Implementors
impl ChunkWindow for BooleanChunked
[src]
impl ChunkWindow for CategoricalChunked
[src]
impl ChunkWindow for ListChunked
[src]
impl ChunkWindow for Utf8Chunked
[src]
impl<T> ChunkWindow for ChunkedArray<T> where
T: PolarsNumericType,
T::Native: Add<Output = T::Native> + Sub<Output = T::Native> + Mul<Output = T::Native> + Div<Output = T::Native> + Zero + Bounded + NumCast + PartialOrd + One + Copy,
[src]
impl<T> ChunkWindow for ChunkedArray<T> where
T: PolarsNumericType,
T::Native: Add<Output = T::Native> + Sub<Output = T::Native> + Mul<Output = T::Native> + Div<Output = T::Native> + Zero + Bounded + NumCast + PartialOrd + One + Copy,
[src]fn rolling_sum(
&self,
window_size: u32,
weight: Option<&[f64]>,
ignore_null: bool,
min_periods: u32
) -> Result<Self>
[src]
&self,
window_size: u32,
weight: Option<&[f64]>,
ignore_null: bool,
min_periods: u32
) -> Result<Self>
fn rolling_mean(
&self,
window_size: u32,
weight: Option<&[f64]>,
ignore_null: bool,
min_periods: u32
) -> Result<Self>
[src]
&self,
window_size: u32,
weight: Option<&[f64]>,
ignore_null: bool,
min_periods: u32
) -> Result<Self>
fn rolling_min(
&self,
window_size: u32,
weight: Option<&[f64]>,
ignore_null: bool,
min_periods: u32
) -> Result<Self>
[src]
&self,
window_size: u32,
weight: Option<&[f64]>,
ignore_null: bool,
min_periods: u32
) -> Result<Self>
fn rolling_max(
&self,
window_size: u32,
weight: Option<&[f64]>,
ignore_null: bool,
min_periods: u32
) -> Result<Self>
[src]
&self,
window_size: u32,
weight: Option<&[f64]>,
ignore_null: bool,
min_periods: u32
) -> Result<Self>