Type Definition polars_core::datatypes::Float32Chunked

pub type Float32Chunked = ChunkedArray<Float32Type>;

Implementations

impl Float32Chunked

pub fn rolling_mean(&self, options: RollingOptions) -> Result<Series>

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.

pub fn rolling_sum(&self, options: RollingOptions) -> Result<Series>

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.

pub fn rolling_min(&self, options: RollingOptions) -> Result<Series>

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.

pub fn rolling_max(&self, options: RollingOptions) -> Result<Series>

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.

pub fn rolling_median(&self, options: RollingOptions) -> Result<Series>

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.

pub fn rolling_quantile(
    &self,
    quantile: f64,
    interpolation: QuantileInterpolOptions,
    options: RollingOptions
) -> Result<Series>

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.

Trait Implementations

impl BitAnd<&'_ ChunkedArray<Float32Type>> for &Float32Chunked

type Output = ChunkedArray<Float32Type>

The resulting type after applying the & operator.

fn bitand(self, _rhs: Self) -> Self::Output

Performs the & operation.

impl BitOr<&'_ ChunkedArray<Float32Type>> for &Float32Chunked

type Output = ChunkedArray<Float32Type>

The resulting type after applying the | operator.

fn bitor(self, _rhs: Self) -> Self::Output

Performs the | operation.

impl BitXor<&'_ ChunkedArray<Float32Type>> for &Float32Chunked

type Output = ChunkedArray<Float32Type>

The resulting type after applying the ^ operator.

fn bitxor(self, _rhs: Self) -> Self::Output

Performs the ^ operation.

impl ChunkQuantile<f32> for Float32Chunked

fn quantile(
    &self,
    quantile: f64,
    interpol: QuantileInterpolOptions
) -> Result<Option<f32>>

Aggregate a given quantile of the ChunkedArray. Returns None if the array is empty or only contains null values.

fn median(&self) -> Option<f32>

Returns the mean value in the array. Returns None if the array is empty or only contains null values.

impl ChunkSort<Float32Type> for Float32Chunked

fn argsort_multiple(&self, other: &[Series], reverse: &[bool]) -> Result<IdxCa>

Panics

This function is very opinionated. We assume that all numeric Series are of the same type, if not it will panic

fn sort_with(&self, options: SortOptions) -> Float32Chunked

fn sort(&self, reverse: bool) -> Float32Chunked

Returned a sorted ChunkedArray.

fn argsort(&self, options: SortOptions) -> IdxCa

Retrieve the indexes needed to sort this array.

impl ChunkUnique<Float32Type> for Float32Chunked

fn unique(&self) -> Result<ChunkedArray<Float32Type>>

Get unique values of a ChunkedArray

fn arg_unique(&self) -> Result<IdxCa>

Get first index of the unique values in a ChunkedArray. This Vec is sorted.

fn is_unique(&self) -> Result<BooleanChunked>

Get a mask of all the unique values.

fn is_duplicated(&self) -> Result<BooleanChunked>

Get a mask of all the duplicated values.

fn n_unique(&self) -> Result<usize>

Number of unique values in the ChunkedArray

fn mode(&self) -> Result<ChunkedArray<T>>

Available on crate feature mode only.

The most occurring value(s). Can return multiple Values

impl ChunkVar<f32> for Float32Chunked

fn var(&self) -> Option<f32>

Compute the variance of this ChunkedArray/Series.

fn std(&self) -> Option<f32>

Compute the standard deviation of this ChunkedArray/Series.

impl IntoSeries for Float32Chunked

fn into_series(self) -> Series

fn is_series() -> bool

impl NumOpsDispatchChecked for Float32Chunked

fn checked_div(&self, rhs: &Series) -> Result<Series>

Checked integer division. Computes self / rhs, returning None if rhs == 0 or the division results in overflow.

fn checked_div_num<T: ToPrimitive>(&self, _rhs: T) -> Result<Series>

impl QuantileAggSeries for Float32Chunked

fn quantile_as_series(
    &self,
    quantile: f64,
    interpol: QuantileInterpolOptions
) -> Result<Series>

Get the quantile of the ChunkedArray as a new Series of length 1.

fn median_as_series(&self) -> Series

Get the median of the ChunkedArray as a new Series of length 1.

impl VarAggSeries for Float32Chunked

fn var_as_series(&self) -> Series

Get the variance of the ChunkedArray as a new Series of length 1.

fn std_as_series(&self) -> Series

Get the standard deviation of the ChunkedArray as a new Series of length 1.

impl VecHash for Float32Chunked

fn vec_hash(&self, random_state: RandomState) -> Vec<u64>

Compute the hash for all values in the array.

fn vec_hash_combine(&self, random_state: RandomState, hashes: &mut [u64])

impl ZipOuterJoinColumn for Float32Chunked

fn zip_outer_join_column(
    &self,
    right_column: &Series,
    opt_join_tuples: &[(Option<IdxSize>, Option<IdxSize>)]
) -> Series