pandas.Index.sort_values#
- Index.sort_values(return_indexer=False, ascending=True, na_position='last', key=None)[source]#
Return a sorted copy of the index.
Return a sorted copy of the index, and optionally return the indices that sorted the index itself.
- Parameters
- return_indexerbool, default False
Should the indices that would sort the index be returned.
- ascendingbool, default True
Should the index values be sorted in an ascending order.
- na_position{‘first’ or ‘last’}, default ‘last’
Argument ‘first’ puts NaNs at the beginning, ‘last’ puts NaNs at the end.
New in version 1.2.0.
- keycallable, optional
If not None, apply the key function to the index values before sorting. This is similar to the key argument in the builtin
sorted()
function, with the notable difference that this key function should be vectorized. It should expect anIndex
and return anIndex
of the same shape.New in version 1.1.0.
- Returns
- sorted_indexpandas.Index
Sorted copy of the index.
- indexernumpy.ndarray, optional
The indices that the index itself was sorted by.
See also
Series.sort_values
Sort values of a Series.
DataFrame.sort_values
Sort values in a DataFrame.
Examples
>>> idx = pd.Index([10, 100, 1, 1000]) >>> idx Int64Index([10, 100, 1, 1000], dtype='int64')
Sort values in ascending order (default behavior).
>>> idx.sort_values() Int64Index([1, 10, 100, 1000], dtype='int64')
Sort values in descending order, and also get the indices idx was sorted by.
>>> idx.sort_values(ascending=False, return_indexer=True) (Int64Index([1000, 100, 10, 1], dtype='int64'), array([3, 1, 0, 2]))