GroupBy.nth(n, dropna=None)

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

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

DataFrameGroupBy.shift(periods=1, freq=None, axis=0)

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

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

GroupBy.sem(ddof=1)

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

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

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