GroupBy

GroupBy objects are returned by groupby calls: maxframe.dataframe.DataFrame.groupby(), maxframe.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.cumcount([ascending])	Number each item in each group from 0 to the length of that group - 1.
GroupBy.cummax()	Cumulative max for each group.
GroupBy.cummin()	Cumulative min for each group.
GroupBy.cumprod()	Cumulative prod for each group.
GroupBy.cumsum()	Cumulative sum for each group.
GroupBy.count(**kw)
GroupBy.expanding([min_periods, shift, ...])	Return an expanding grouper, providing expanding functionality per group.
GroupBy.max(**kw)
GroupBy.mean(**kw)
GroupBy.median(**kw)
GroupBy.min(**kw)
GroupBy.rolling(window[, min_periods, ...])	Return a rolling grouper, providing rolling functionality per group.
GroupBy.size(**kw)
GroupBy.sem(**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.nunique(**kw)
DataFrameGroupBy.cummax()	Cumulative max for each group.
DataFrameGroupBy.cummin()	Cumulative min for each group.
DataFrameGroupBy.cumprod()	Cumulative prod for each group.
DataFrameGroupBy.cumsum()	Cumulative sum for each group.
DataFrameGroupBy.fillna([value, method, ...])	Fill NA/NaN values using the specified method
DataFrameGroupBy.idxmax(**kw)
DataFrameGroupBy.idxmin(**kw)
DataFrameGroupBy.nunique(**kw)
DataFrameGroupBy.rank([method, ascending, ...])	Provide the rank of values within each group.
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.

DataFrameGroupBy.mf.apply_chunk(func[, ...])

Apply function func group-wise and combine the results together.