BUG: fix sort_index with one col and ascending list

now actually checks the first element of the list

doc/source/release.rst

@@ -424,6 +424,10 @@ Bug Fixes
  across different versions of matplotlib (:issue:`4789`)
  - Suppressed DeprecationWarning associated with internal calls issued by repr() (:issue:`4391`)
  - Fixed an issue with a duplicate index and duplicate selector with ``.loc`` (:issue:`4825`)
+ - Fixed an issue with ``DataFrame.sort_index`` where, when sorting by a
+ single column and passing a list for ``ascending``, the argument for
+ ``ascending`` was being interpreted as ``True`` (:issue:`4839`,
+ :issue:`4846`)
 
 pandas 0.12.0
 -------------

pandas/core/frame.py

@@ -2856,7 +2856,7 @@ def sort_index(self, axis=0, by=None, ascending=True, inplace=False,
 
  Examples
  --------
- >>> result = df.sort_index(by=['A', 'B'], ascending=[1, 0])
+ >>> result = df.sort_index(by=['A', 'B'], ascending=[True, False])
 
  Returns
  -------
@@ -2875,6 +2875,9 @@ def sort_index(self, axis=0, by=None, ascending=True, inplace=False,
  raise ValueError('When sorting by column, axis must be 0 (rows)')
  if not isinstance(by, (tuple, list)):
  by = [by]
+ if com._is_sequence(ascending) and len(by) != len(ascending):
+ raise ValueError('Length of ascending (%d) != length of by'
+ ' (%d)' % (len(ascending), len(by)))
 
  if len(by) > 1:
  keys = []
@@ -2900,6 +2903,8 @@ def trans(v):
  raise ValueError('Cannot sort by duplicate column %s'
  % str(by))
  indexer = k.argsort(kind=kind)
+ if isinstance(ascending, (tuple, list)):
+ ascending = ascending[0]
  if not ascending:
  indexer = indexer[::-1]
  elif isinstance(labels, MultiIndex):

pandas/tests/test_frame.py

@@ -8796,24 +8796,37 @@ def test_sort_index(self):
  expected = frame.ix[frame.index[indexer]]
  assert_frame_equal(sorted_df, expected)
 
+ sorted_df = frame.sort(columns='A', ascending=False)
+ assert_frame_equal(sorted_df, expected)
+
+ # GH4839
+ sorted_df = frame.sort(columns=['A'], ascending=[False])
+ assert_frame_equal(sorted_df, expected)
+
  # check for now
  sorted_df = frame.sort(columns='A')
+ assert_frame_equal(sorted_df, expected[::-1])
  expected = frame.sort_index(by='A')
  assert_frame_equal(sorted_df, expected)
 
- sorted_df = frame.sort(columns='A', ascending=False)
- expected = frame.sort_index(by='A', ascending=False)
- assert_frame_equal(sorted_df, expected)
 
  sorted_df = frame.sort(columns=['A', 'B'], ascending=False)
  expected = frame.sort_index(by=['A', 'B'], ascending=False)
  assert_frame_equal(sorted_df, expected)
 
+ sorted_df = frame.sort(columns=['A', 'B'])
+ assert_frame_equal(sorted_df, expected[::-1])
+
  self.assertRaises(ValueError, frame.sort_index, axis=2, inplace=True)
+
  msg = 'When sorting by column, axis must be 0'
  with assertRaisesRegexp(ValueError, msg):
  frame.sort_index(by='A', axis=1)
 
+ msg = r'Length of ascending \(5\) != length of by \(2\)'
+ with assertRaisesRegexp(ValueError, msg):
+ frame.sort_index(by=['A', 'B'], axis=0, ascending=[True] * 5)
+
  def test_sort_index_multicolumn(self):
  import random
  A = np.arange(5).repeat(20)