DataFrame.
sort_index
Sort object by labels (along an axis)
if not None, sort on values in specified index level(s)
Sort ascending vs. descending
if True, perform operation in-place
Koalas does not allow specifying the sorting algorithm at the moment, default None
first puts NaNs at the beginning, last puts NaNs at the end. Not implemented for MultiIndex.
Examples
>>> df = ks.DataFrame({'A': [2, 1, np.nan]}, index=['b', 'a', np.nan])
>>> df.sort_index() A a 1.0 b 2.0 NaN NaN
>>> df.sort_index(ascending=False) A b 2.0 a 1.0 NaN NaN
>>> df.sort_index(na_position='first') A NaN NaN a 1.0 b 2.0
>>> df.sort_index(inplace=True) >>> df A a 1.0 b 2.0 NaN NaN
>>> df = ks.DataFrame({'A': range(4), 'B': range(4)[::-1]}, ... index=[['b', 'b', 'a', 'a'], [1, 0, 1, 0]], ... columns=['A', 'B'])
>>> df.sort_index() A B a 0 3 0 1 2 1 b 0 1 2 1 0 3
>>> df.sort_index(level=1) A B a 0 3 0 b 0 1 2 a 1 2 1 b 1 0 3
>>> df.sort_index(level=[1, 0]) A B a 0 3 0 b 0 1 2 a 1 2 1 b 1 0 3