Resampling#

Resampler objects are returned by resample calls: pandas.DataFrame.resample(), pandas.Series.resample().

Indexing, iteration#

Resampler.__iter__()

Groupby iterator.

Resampler.groups

Dict {group name -> group labels}.

Resampler.indices

Dict {group name -> group indices}.

Resampler.get_group(name[, obj])

Construct DataFrame from group with provided name.

Function application#

Resampler.apply([func])

Aggregate using one or more operations over the specified axis.

Resampler.aggregate([func])

Aggregate using one or more operations over the specified axis.

Resampler.transform(arg, *args, **kwargs)

Call function producing a like-indexed Series on each group.

Resampler.pipe(func, *args, **kwargs)

Apply a func with arguments to this Resampler object and return its result.

Upsampling#

Resampler.ffill([limit])

Forward fill the values.

Resampler.backfill([limit])

Backward fill the new missing values in the resampled data.

Resampler.bfill([limit])

Backward fill the new missing values in the resampled data.

Resampler.pad([limit])

Forward fill the values.

Resampler.nearest([limit])

Resample by using the nearest value.

Resampler.fillna(method[, limit])

Fill missing values introduced by upsampling.

Resampler.asfreq([fill_value])

Return the values at the new freq, essentially a reindex.

Resampler.interpolate([method, axis, limit, ...])

Interpolate values according to different methods.

Computations / descriptive stats#

Resampler.count()

Compute count of group, excluding missing values.

Resampler.nunique(*args, **kwargs)

Return number of unique elements in the group.

Resampler.first([numeric_only, min_count])

Compute the first non-null entry of each column.

Resampler.last([numeric_only, min_count])

Compute the last non-null entry of each column.

Resampler.max([numeric_only, min_count])

Compute max of group values.

Resampler.mean([numeric_only])

Compute mean of groups, excluding missing values.

Resampler.median([numeric_only])

Compute median of groups, excluding missing values.

Resampler.min([numeric_only, min_count])

Compute min of group values.

Resampler.ohlc(*args, **kwargs)

Compute open, high, low and close values of a group, excluding missing values.

Resampler.prod([numeric_only, min_count])

Compute prod of group values.

Resampler.size()

Compute group sizes.

Resampler.sem([ddof, numeric_only])

Compute standard error of the mean of groups, excluding missing values.

Resampler.std([ddof, numeric_only])

Compute standard deviation of groups, excluding missing values.

Resampler.sum([numeric_only, min_count])

Compute sum of group values.

Resampler.var([ddof, numeric_only])

Compute variance of groups, excluding missing values.

Resampler.quantile([q])

Return value at the given quantile.