Resampling — pandas 0.25.3 documentation (original) (raw)

Upsampling

Resampler.ffill(self[, limit]) Forward fill the values.
Resampler.backfill(self[, limit]) Backward fill the new missing values in the resampled data.
Resampler.bfill(self[, limit]) Backward fill the new missing values in the resampled data.
Resampler.pad(self[, limit]) Forward fill the values.
Resampler.nearest(self[, limit]) Resample by using the nearest value.
Resampler.fillna(self, method[, limit]) Fill missing values introduced by upsampling.
Resampler.asfreq(self[, fill_value]) Return the values at the new freq, essentially a reindex.
Resampler.interpolate(self[, method, axis, …]) Interpolate values according to different methods.

Computations / descriptive stats

Resampler.count(self[, _method]) Compute count of group, excluding missing values.
Resampler.nunique(self[, _method]) Return number of unique elements in the group.
Resampler.first(self[, _method]) Compute first of group values.
Resampler.last(self[, _method]) Compute last of group values.
Resampler.max(self[, _method]) Compute max of group values.
Resampler.mean(self[, _method]) Compute mean of groups, excluding missing values.
Resampler.median(self[, _method]) Compute median of groups, excluding missing values.
Resampler.min(self[, _method]) Compute min of group values.
Resampler.ohlc(self[, _method]) Compute sum of values, excluding missing values.
Resampler.prod(self[, _method, min_count]) Compute prod of group values.
Resampler.size(self) Compute group sizes.
Resampler.sem(self[, _method]) Compute standard error of the mean of groups, excluding missing values.
Resampler.std(self[, ddof]) Compute standard deviation of groups, excluding missing values.
Resampler.sum(self[, _method, min_count]) Compute sum of group values.
Resampler.var(self[, ddof]) Compute variance of groups, excluding missing values.
Resampler.quantile(self[, q]) Return value at the given quantile.