Struct Resample 

pub struct Resample<'a> { /* private fields */ }

Time-based resampling view over a Series.

Created by Series::resample(freq). Groups values by time buckets defined by the frequency string.

Implementations

impl Resample<'_>

pub fn sum(&self) -> Result<Series, FrameError>

Resample sum.

pub fn mean(&self) -> Result<Series, FrameError>

Resample mean.

pub fn count(&self) -> Result<Series, FrameError>

Resample count.

pub fn min(&self) -> Result<Series, FrameError>

Resample min.

pub fn max(&self) -> Result<Series, FrameError>

Resample max.

pub fn first(&self) -> Result<Series, FrameError>

Resample first non-null value.

pub fn last(&self) -> Result<Series, FrameError>

Resample last non-null value.

pub fn apply<F>(&self, func: F) -> Result<Series, FrameError>

where F: Fn(&[Scalar]) -> Scalar,

Apply a custom aggregation function to each time bucket.

Matches pd.Series.resample(freq).apply(func). The function receives a slice of Scalar values for each bucket and must return a single Scalar result.

pub fn apply_fn<F>(&self, func: F) -> Result<Series, FrameError>

where F: Fn(&[Scalar]) -> Result<Scalar, FrameError>,

Apply a custom aggregation function (failable) to each time bucket.

Like apply but the closure can return Result.

pub fn std(&self) -> Result<Series, FrameError>

Resample standard deviation (ddof=1).

pub fn var(&self) -> Result<Series, FrameError>

Resample variance.

pub fn median(&self) -> Result<Series, FrameError>

Resample median.

pub fn prod(&self) -> Result<Series, FrameError>

Resample product.

pub fn agg(&self, funcs: &[&str]) -> Result<DataFrame, FrameError>

Aggregate each bucket with one or more named reducers.

Matches series.resample(freq).agg([...]).

pub fn aggregate(&self, funcs: &[&str]) -> Result<DataFrame, FrameError>

pandas spelling alias for Self::agg.

pub fn keys(&self) -> Vec<IndexLabel>

Bucket labels in first-observed order.

pub fn indices(&self) -> HashMap<IndexLabel, Vec<usize>>

Mapping from bucket labels to source row positions.

pub fn groups(&self) -> HashMap<IndexLabel, Vec<usize>>

Alias for Self::indices.

pub fn grouper(&self) -> String

Resample frequency descriptor used as the grouper.

pub fn level(&self) -> String

Resample grouping level descriptor.

pub fn ngroups(&self) -> usize

Number of non-empty resample buckets.

pub fn ndim(&self) -> usize

Series resampler dimensionality.

pub fn exclusions(&self) -> Vec<String>

Labels excluded from the resample operation.

pub fn get_group(&self, name: &str) -> Result<Series, FrameError>

Return the source rows for one resample bucket.

pub fn asfreq(&self) -> Result<Series, FrameError>

Resample to bucket frequency without reduction.

Current bucketed storage has no explicit empty bucket generation, so this selects the first observed value in each bucket.

pub fn ffill(&self, _limit: Option<usize>) -> Result<Series, FrameError>

Forward-fill each resample bucket.

pub fn bfill(&self, _limit: Option<usize>) -> Result<Series, FrameError>

Backward-fill each resample bucket.

pub fn fillna(&self, value: &Scalar) -> Result<Series, FrameError>

Fill missing resampled values with a scalar.

pub fn interpolate(&self) -> Result<Series, FrameError>

Interpolate missing values after bucket materialization.

pub fn nearest(&self) -> Result<Series, FrameError>

Select nearest observed value for each current non-empty bucket.

pub fn quantile(&self, q: f64) -> Result<Series, FrameError>

Resample quantile using linear interpolation inside each bucket.

pub fn sem(&self) -> Result<Series, FrameError>

Resample standard error of the mean.

pub fn skew(&self) -> Result<Series, FrameError>

Resample skewness (Fisher’s definition, bias=False).

Matches pd.Series.resample(freq).skew(). Mirrors fp_types::nanskew which returns Null(NaN) for buckets with fewer than 3 non-missing values or zero sample variance.

pub fn kurt(&self) -> Result<Series, FrameError>

Resample excess kurtosis (Fisher’s definition, bias=False).

Matches pd.Series.resample(freq).kurt() / .kurtosis(). Mirrors fp_types::nankurt which returns Null(NaN) for buckets with fewer than 4 non-missing values or zero sample variance.

pub fn kurtosis(&self) -> Result<Series, FrameError>

Alias for kurt() — pandas exposes both spellings on resampled aggregations.

pub fn size(&self) -> Result<Series, FrameError>

Resample bucket sizes including missing values.

pub fn nunique(&self) -> Result<Series, FrameError>

Count unique non-missing values in each bucket.

pub fn ohlc(&self) -> Result<DataFrame, FrameError>

Open-high-low-close per resample bucket.

pub fn transform(&self, func: &str) -> Result<Series, FrameError>

Broadcast a named bucket reduction back to the original Series shape.

pub fn pipe<T, F>(&self, func: F) -> Result<T, FrameError>

where F: Fn(&Self) -> Result<T, FrameError>,

Pipe this resampler through a caller-provided function.