DataFrameGroupBy.rank(axis=0, method='average', numeric_only=None, na_option='keep', ascending=True, pct=False)

GroupBy.groups dict {group name -> group labels}

DataFrameGroupBy.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None, **kwargs)

SeriesGroupBy.unique() Return np.ndarray of unique values in the object. Significantly faster than numpy

GroupBy.median()

GroupBy.size()

GroupBy.sem(ddof=1)

GroupBy.head(n=5)

DataFrameGroupBy.any(axis=None, bool_only=None, skipna=None, level=None, **kwargs) Return whether any

SeriesGroupBy.value_counts(normalize=False, sort=True, ascending=False, bins=None, dropna=True)