GroupBy

GroupBy objects are returned by groupby calls: xorbits.pandas.DataFrame.groupby(), xorbits.pandas.Series.groupby(), etc.

Indexing, iteration

DataFrameGroupBy.__iter__()
SeriesGroupBy.__iter__()

Function application helper

NamedAgg(column, aggfunc)

Helper for column specific aggregation with control over output column names.

Function application

SeriesGroupBy.apply(func, *args[, ...])	Apply function func group-wise and combine the results together.
DataFrameGroupBy.apply(func, *args[, ...])	Apply function func group-wise and combine the results together.
SeriesGroupBy.agg([func, method, combine_size])	Aggregate using one or more operations over the specified axis.
DataFrameGroupBy.agg([func, method, ...])	Aggregate using one or more operations over the specified axis.
SeriesGroupBy.aggregate([func, method, ...])	Aggregate using one or more operations over the specified axis.
DataFrameGroupBy.aggregate([func, method, ...])	Aggregate using one or more operations over the specified axis.
SeriesGroupBy.transform(f, *args[, dtypes, ...])	Call function producing a same-indexed Series on each group.
DataFrameGroupBy.transform(f, *args[, ...])	Call function producing a same-indexed DataFrame on each group.

DataFrameGroupBy computations / descriptive stats

DataFrameGroupBy.all(**kw)	Return True if all values in the group are truthful, else False.
DataFrameGroupBy.any(**kw)	Return True if any value in the group is truthful, else False.
DataFrameGroupBy.backfill([limit])
DataFrameGroupBy.bfill([limit])	Backward fill the values.
DataFrameGroupBy.count(**kw)	Compute count of group, excluding missing values.
DataFrameGroupBy.cumcount([ascending])	Number each item in each group from 0 to the length of that group - 1.
DataFrameGroupBy.cummax([axis])	Cumulative max for each group.
DataFrameGroupBy.cummin([axis])	Cumulative min for each group.
DataFrameGroupBy.cumprod([axis])	Cumulative product for each group.
DataFrameGroupBy.cumsum([axis])	Cumulative sum for each group.
DataFrameGroupBy.ffill([limit])	Forward fill the values.
DataFrameGroupBy.fillna([value, method, limit])	Fill NA/NaN values using the specified method within groups.
DataFrameGroupBy.head([n])	Return first n rows of each group.
DataFrameGroupBy.max(**kw)	Compute max of group values.
DataFrameGroupBy.mean(**kw)	Compute mean of groups, excluding missing values.
DataFrameGroupBy.min(**kw)	Compute min of group values.
DataFrameGroupBy.nth(n[, dropna])	Take the nth row from each group if n is an int, otherwise a subset of rows.
DataFrameGroupBy.nunique(**kw)	Return DataFrame with counts of unique elements in each position.
DataFrameGroupBy.prod(**kw)	Compute prod of group values.
DataFrameGroupBy.sample([n, frac, replace, ...])	Return a random sample of items from each group.
DataFrameGroupBy.sem(**kw)	Compute standard error of the mean of groups, excluding missing values.
DataFrameGroupBy.size(**kw)	Compute group sizes.
DataFrameGroupBy.skew(**kw)	Return unbiased skew within groups.
DataFrameGroupBy.std(**kw)	Compute standard deviation of groups, excluding missing values.
DataFrameGroupBy.sum(**kw)	Compute sum of group values.
DataFrameGroupBy.var(**kw)	Compute variance of groups, excluding missing values.

SeriesGroupBy computations / descriptive stats

SeriesGroupBy.all(**kw)	Return True if all values in the group are truthful, else False.
SeriesGroupBy.any(**kw)	Return True if any value in the group is truthful, else False.
SeriesGroupBy.backfill([limit])
SeriesGroupBy.bfill([limit])	Backward fill the values.
SeriesGroupBy.count(**kw)	Compute count of group, excluding missing values.
SeriesGroupBy.cumcount([ascending])	Number each item in each group from 0 to the length of that group - 1.
SeriesGroupBy.cummax([axis])	Cumulative max for each group.
SeriesGroupBy.cummin([axis])	Cumulative min for each group.
SeriesGroupBy.cumprod([axis])	Cumulative product for each group.
SeriesGroupBy.cumsum([axis])	Cumulative sum for each group.
SeriesGroupBy.ffill([limit])	Forward fill the values.
SeriesGroupBy.fillna([value, method, limit])	Fill NA/NaN values using the specified method within groups.
SeriesGroupBy.head([n])	Return first n rows of each group.
SeriesGroupBy.max(**kw)	Compute max of group values.
SeriesGroupBy.mean(**kw)	Compute mean of groups, excluding missing values.
SeriesGroupBy.min(**kw)	Compute min of group values.
SeriesGroupBy.nth(n[, dropna])	Take the nth row from each group if n is an int, otherwise a subset of rows.
SeriesGroupBy.nunique(**kw)	Return number of unique elements in the group.
SeriesGroupBy.prod(**kw)	Compute prod of group values.
SeriesGroupBy.sample([n, frac, replace, ...])	Return a random sample of items from each group.
SeriesGroupBy.sem(**kw)	Compute standard error of the mean of groups, excluding missing values.
SeriesGroupBy.size(**kw)	Compute group sizes.
SeriesGroupBy.skew(**kw)	Return unbiased skew within groups.
SeriesGroupBy.std(**kw)	Compute standard deviation of groups, excluding missing values.
SeriesGroupBy.sum(**kw)	Compute sum of group values.
SeriesGroupBy.var(**kw)	Compute variance of groups, excluding missing values.

Plotting and visualization