GroupBy.nth(n, dropna=None)

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

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

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

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

GroupBy.head(n=5)

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

GroupBy.sem(ddof=1)

GroupBy.var(ddof=1, *args, **kwargs)

GroupBy.median()