BUG: DatetimeIndex cannot parse string ndarray with dayfirst

doc/source/release.rst

@@ -484,6 +484,7 @@ Bug Fixes
  or until the end of the line when ``colspec`` contains a ``None`` (previously raised a ``TypeError``)
 - Bug in cache coherence with chained indexing and slicing; add ``_is_view`` property to ``NDFrame`` to correctly predict
  views; mark ``is_copy`` on ``xs` only if its an actual copy (and not a view) (:issue:`7084`)
+- Bug in DatetimeIndex creation from string ndarray with ``dayfirst=True`` (:issue:`5917`)
 
 pandas 0.13.1
 -------------

pandas/tseries/index.py

@@ -250,20 +250,29 @@ def __new__(cls, data=None,
  else:
  subarr = data.view(_NS_DTYPE)
  else:
- try:
- subarr = tools.to_datetime(data, box=False)
+ if isinstance(data, ABCSeries):
+ values = data.values
+ else:
+ values = data
 
- # make sure that we have a index/ndarray like (and not a Series)
- if isinstance(subarr, ABCSeries):
- subarr = subarr.values
+ if lib.is_string_array(values):
+ subarr = _str_to_dt_array(values, freq, dayfirst=dayfirst,
+ yearfirst=yearfirst) 
+ else:
+ try:
+ subarr = tools.to_datetime(data, box=False)
 
- except ValueError:
- # tz aware
- subarr = tools.to_datetime(data, box=False, utc=True)
+ # make sure that we have a index/ndarray like (and not a Series)
+ if isinstance(subarr, ABCSeries):
+ subarr = subarr.values
+
+ except ValueError:
+ # tz aware
+ subarr = tools.to_datetime(data, box=False, utc=True)
 
- if not np.issubdtype(subarr.dtype, np.datetime64):
- raise ValueError('Unable to convert %s to datetime dtype'
- % str(data))
+  if not np.issubdtype(subarr.dtype, np.datetime64):
+  raise ValueError('Unable to convert %s to datetime dtype'
+  % str(data))
 
  if isinstance(subarr, DatetimeIndex):
  if tz is None:

pandas/tseries/tests/test_timeseries.py

@@ -2415,6 +2415,25 @@ def test_datetimeindex_constructor(self):
  self.assertEquals(len(idx1), len(idx2))
  self.assertEquals(idx1.offset, idx2.offset)
 
+ def test_dayfirst(self):
+ # GH 5917
+ arr = ['10/02/2014', '11/02/2014', '12/02/2014']
+ expected = DatetimeIndex([datetime(2014, 2, 10),
+ datetime(2014, 2, 11),
+ datetime(2014, 2, 12)])
+ idx1 = DatetimeIndex(arr, dayfirst=True)
+ idx2 = DatetimeIndex(np.array(arr), dayfirst=True)
+ idx3 = to_datetime(arr, dayfirst=True)
+ idx4 = to_datetime(np.array(arr), dayfirst=True)
+ idx5 = DatetimeIndex(Index(arr), dayfirst=True)
+ idx6 = DatetimeIndex(Series(arr), dayfirst=True) 
+ self.assert_(expected.equals(idx1))
+ self.assert_(expected.equals(idx2))
+ self.assert_(expected.equals(idx3))
+ self.assert_(expected.equals(idx4))
+ self.assert_(expected.equals(idx5))
+ self.assert_(expected.equals(idx6))
+
  def test_dti_snap(self):
  dti = DatetimeIndex(['1/1/2002', '1/2/2002', '1/3/2002', '1/4/2002',
  '1/5/2002', '1/6/2002', '1/7/2002'], freq='D')