GroupBy

GroupBy objects are returned by groupby calls: mars.dataframe.DataFrame.groupby(), mars.dataframe.Series.groupby(), etc.

Indexing, iteration

Function application

GroupBy.apply(func, *args[, output_type, ...])	Apply function func group-wise and combine the results together.
GroupBy.agg([func, method])	Aggregate using one or more operations on grouped data.
GroupBy.aggregate([func, method])	Aggregate using one or more operations on grouped data.
GroupBy.transform(f, *args[, dtypes, dtype, ...])	Call function producing a like-indexed DataFrame on each group and return a DataFrame having the same indexes as the original object filled with the transformed values

Computations / descriptive stats

GroupBy.all(**kw)
GroupBy.any(**kw)
GroupBy.count(**kw)
GroupBy.cumcount([ascending])
GroupBy.cummax([axis])
GroupBy.cummin([axis])
GroupBy.cumprod([axis])
GroupBy.cumsum([axis])
GroupBy.head([n])	Return first n rows of each group.
GroupBy.kurt(**kw)
GroupBy.kurtosis(**kw)
GroupBy.max(**kw)
GroupBy.mean(**kw)
GroupBy.min(**kw)
GroupBy.size(**kw)
GroupBy.sem(**kw)
GroupBy.skew(**kw)
GroupBy.std(**kw)
GroupBy.sum(**kw)
GroupBy.var(**kw)

The following methods are available in both SeriesGroupBy and DataFrameGroupBy objects, but may differ slightly, usually in that the DataFrameGroupBy version usually permits the specification of an axis argument, and often an argument indicating whether to restrict application to columns of a specific data type.

DataFrameGroupBy.count(**kw)
DataFrameGroupBy.cummax([axis])
DataFrameGroupBy.cummin([axis])
DataFrameGroupBy.cumprod([axis])
DataFrameGroupBy.cumsum([axis])
DataFrameGroupBy.sample([n, frac, replace, ...])	Return a random sample of items from each group.

The following methods are available only for SeriesGroupBy objects.

The following methods are available only for DataFrameGroupBy objects.

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mars.dataframe.groupby.GroupBy.apply