BUG: Accept kwargs kind and na_position in Series.sort_index (GH13589)

Add tests for testing na_position and kind kwargs in Series.sort_index Fix minor issues with tests for Series.sort_index Update whatsnew entry; fix tests Update Series doc-string to mention new additions Remove update from Series doc-string Mention versionadded in Series.sort_index() doc-string Revert: Remove version tag from docstring Add test for invalid arguments

doc/source/whatsnew/v0.19.0.txt

@@ -513,6 +513,7 @@ Other enhancements
 - ``Timestamp``, ``Period``, ``DatetimeIndex``, ``PeriodIndex`` and ``.dt`` accessor have gained a ``.is_leap_year`` property to check whether the date belongs to a leap year. (:issue:`13727`)
 - ``astype()`` will now accept a dict of column name to data types mapping as the ``dtype`` argument. (:issue:`12086`)
 - The ``pd.read_json`` and ``DataFrame.to_json`` has gained support for reading and writing json lines with ``lines`` option see :ref:`Line delimited json <io.jsonl>` (:issue:`9180`)
+- `Series.sort_index`` will now accept kwargs ``kind`` and ``na_position`` (:issue:`13589`)
 
 .. _whatsnew_0190.api:
 

pandas/core/generic.py

@@ -2022,16 +2022,16 @@ def sort_values(self, by, axis=0, ascending=True, inplace=False,
  Sort ascending vs. descending
  inplace : bool, default False
  if True, perform operation in-place
+ 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
  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'
  `first` puts NaNs at the beginning, `last` puts NaNs at the end
- 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
 
  Returns
  -------

pandas/core/series.py

@@ -1773,7 +1773,7 @@ def _try_kind_sort(arr):
 
  @Appender(generic._shared_docs['sort_index'] % _shared_doc_kwargs)
  def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
- sort_remaining=True):
+ kind='quicksort', na_position='last', sort_remaining=True):
 
  axis = self._get_axis_number(axis)
  index = self.index
@@ -1782,12 +1782,15 @@ def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
  sort_remaining=sort_remaining)
  elif isinstance(index, MultiIndex):
  from pandas.core.groupby import _lexsort_indexer
- indexer = _lexsort_indexer(index.labels, orders=ascending)
+ indexer = _lexsort_indexer(index.labels, orders=ascending,
+ na_position=na_position)
  indexer = _ensure_platform_int(indexer)
  new_index = index.take(indexer)
  else:
  new_index, indexer = index.sort_values(return_indexer=True,
- ascending=ascending)
+ ascending=ascending,
+ kind=kind,
+ na_position=na_position)
 
  new_values = self._values.take(indexer)
  result = self._constructor(new_values, index=new_index)

pandas/tests/series/test_sorting.py

@@ -5,7 +5,7 @@
 
 from pandas import (DataFrame, Series, MultiIndex)
 
-from pandas.util.testing import (assert_series_equal, assert_almost_equal)
+from pandas.util.testing import (assert_series_equal, assert_almost_equal, assertRaisesRegexp)
 import pandas.util.testing as tm
 
 from .common import TestData
@@ -144,3 +144,22 @@ def test_sort_index_multiindex(self):
  # rows share same level='A': sort has no effect without remaining lvls
  res = s.sort_index(level='A', sort_remaining=False)
  assert_series_equal(s, res)
+
+ def test_sort_index_nan(self):
+
+ # GH13729
+ ser = Series(['A', np.nan, 'C', 'D'], [1, 2, 0, np.nan])
+
+ # na_position='last', kind='quicksort'
+ result = ser.sort_index(kind='quicksort', na_position='last')
+ expected = Series(['C', 'A', np.nan, 'D'], [0, 1, 2, np.nan])
+ assert_series_equal(result, expected)
+
+ # na_position='first'
+ result = ser.sort_index(na_position='first')
+ expected = Series(['D', 'C', 'A', np.nan], [np.nan, 0, 1, 2])
+ assert_series_equal(result, expected)
+
+ # invalid argument
+ assertRaisesRegexp(TypeError, 'got an unexpected keyword argument',
+ ser.sort_index, arg='first')