Classe « DataFrame »
Signature de la méthode sort_index
def sort_index(self, axis=0, level=None, ascending: 'Union[Union[bool, int], Sequence[Union[bool, int]]]' = True, inplace: 'bool' = False, kind: 'str' = 'quicksort', na_position: 'str' = 'last', sort_remaining: 'bool' = True, ignore_index: 'bool' = False, key: 'IndexKeyFunc' = None)
Description
sort_index.__doc__
Sort object by labels (along an axis).
Returns a new DataFrame sorted by label if `inplace` argument is
``False``, otherwise updates the original DataFrame and returns None.
Parameters
----------
axis : {0 or 'index', 1 or 'columns'}, default 0
The axis along which to sort. The value 0 identifies the rows,
and 1 identifies the columns.
level : int or level name or list of ints or list of level names
If not None, sort on values in specified index level(s).
ascending : bool or list-like of bools, default True
Sort ascending vs. descending. When the index is a MultiIndex the
sort direction can be controlled for each level individually.
inplace : bool, default False
If True, perform operation in-place.
kind : {'quicksort', 'mergesort', 'heapsort'}, default 'quicksort'
Choice of sorting algorithm. See also ndarray.np.sort for more
information. `mergesort` is the only stable algorithm. For
DataFrames, this option is only applied when sorting on a single
column or label.
na_position : {'first', 'last'}, default 'last'
Puts NaNs at the beginning if `first`; `last` puts NaNs at the end.
Not implemented for MultiIndex.
sort_remaining : bool, default True
If True and sorting by level and index is multilevel, sort by other
levels too (in order) after sorting by specified level.
ignore_index : bool, default False
If True, the resulting axis will be labeled 0, 1, ..., n - 1.
.. versionadded:: 1.0.0
key : callable, optional
If not None, apply the key function to the index values
before sorting. This is similar to the `key` argument in the
builtin :meth:`sorted` function, with the notable difference that
this `key` function should be *vectorized*. It should expect an
``Index`` and return an ``Index`` of the same shape. For MultiIndex
inputs, the key is applied *per level*.
.. versionadded:: 1.1.0
Returns
-------
DataFrame or None
The original DataFrame sorted by the labels or None if ``inplace=True``.
See Also
--------
Series.sort_index : Sort Series by the index.
DataFrame.sort_values : Sort DataFrame by the value.
Series.sort_values : Sort Series by the value.
Examples
--------
>>> df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150],
... columns=['A'])
>>> df.sort_index()
A
1 4
29 2
100 1
150 5
234 3
By default, it sorts in ascending order, to sort in descending order,
use ``ascending=False``
>>> df.sort_index(ascending=False)
A
234 3
150 5
100 1
29 2
1 4
A key function can be specified which is applied to the index before
sorting. For a ``MultiIndex`` this is applied to each level separately.
>>> df = pd.DataFrame({"a": [1, 2, 3, 4]}, index=['A', 'b', 'C', 'd'])
>>> df.sort_index(key=lambda x: x.str.lower())
a
A 1
b 2
C 3
d 4
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