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.

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pandas.core.resample.Resampler.__iter__