Struct DataFrameResample 

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

Time-based resampling view over a DataFrame’s numeric columns.

Created by DataFrame::resample(freq). Groups by time buckets and aggregates.

Implementations

impl DataFrameResample<'_>

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

Resample sum across all numeric columns.

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

Resample mean across all numeric columns.

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

Resample count across all numeric columns.

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

Resample min across all numeric columns.

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

Resample max across all numeric columns.

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

Resample product across all numeric columns.

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

Resample first across all numeric columns.

Matches df.resample(freq).first(). README line 494 lists first in the Resample row; fd90.200 brings the DataFrameResample direct- method surface up to parity with Series Resample.

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

Resample last across all numeric columns.

Matches df.resample(freq).last(). fd90.200 sibling of first.

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

Resample standard deviation (ddof=1) across all numeric columns.

Matches df.resample(freq).std(). Closes parity gap — pandas exposes std/var/median/skew/kurt on DataFrame.resample(); the fp-frame impl only had sum/mean/min/max/first/last/sem before.

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

Resample variance (ddof=1) across all numeric columns.

Matches df.resample(freq).var().

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

Resample median across all numeric columns.

Matches df.resample(freq).median().

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

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

Matches df.resample(freq).skew().

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

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

Matches df.resample(freq).kurt().

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

Alias for kurt() — pandas exposes both spellings.

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

Aggregate with multiple functions, producing prefixed column names.

Matches df.resample(freq).agg(['sum', 'mean']). Each numeric column gets one output column per function, named {col}_{func}.

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

DataFrame resampler dimensionality.

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

Labels excluded from the resample operation.

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

Return all source rows for one resample bucket.

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

Resample to bucket frequency without reduction.

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

Forward-fill each resample bucket.

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

Backward-fill each resample bucket.

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

Fill missing values after bucket materialization.

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

Interpolate missing values after bucket materialization.

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

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

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

Resample quantile across numeric columns.

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

Resample standard error of the mean across numeric columns.

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

Count source rows in each resample bucket.

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

Count unique non-missing values per bucket for every column.

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

Open-high-low-close per bucket for each numeric column.

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

Broadcast a named bucket reduction back to the original DataFrame 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.