GroupBy.nth(n, dropna=None)

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

GroupBy.head(n=5)

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

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

GroupBy.size()

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

GroupBy.sem(ddof=1)

DataFrameGroupBy.cov(min_periods=None) Compute pairwise covariance of columns, excluding NA/null values

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