Closed
Description
Code Sample, a copy-pastable example if possible
looking at code of pandas/tests/series/test_datetime_values.py which was introduced in c76ca44 I believe:
period_index = period_range('20150301', periods=5)
result = period_index.strftime("%Y/%m/%d")
expected = np.array(['2015/03/01', '2015/03/02', '2015/03/03',
'2015/03/04', '2015/03/05'], dtype='<U10')
self.assert_numpy_array_equal(result, expected)Problem description
above (and some other tests... see e.g. https://buildd.debian.org/status/fetch.php?pkg=pandas&arch=s390x&ver=0.19.1-2&stamp=1480348101) lead to failed tests... which sometimes look as informative as
numpy array values are different (0.0 %)
[left]: [2015/03/01, 2015/03/02, 2015/03/03, 2015/03/04, 2015/03/05]
[right]: [2015/03/01, 2015/03/02, 2015/03/03, 2015/03/04, 2015/03/05]
;-)
but the real reason is different endianness:
(Pdb) l
325
326 period_index = period_range('20150301', periods=5)
327 result = period_index.strftime("%Y/%m/%d")
328 expected = np.array(['2015/03/01', '2015/03/02', '2015/03/03',
329 '2015/03/04', '2015/03/05'], dtype='<U10')
330 -> self.assert_numpy_array_equal(result, expected)
331
332 s = Series([datetime(2013, 1, 1, 2, 32, 59), datetime(2013, 1, 2, 14,
333 32, 1)])
334 result = s.dt.strftime('%Y-%m-%d %H:%M:%S')
335 expected = Series(["2013-01-01 02:32:59", "2013-01-02 14:32:01"])
(Pdb) p expected
array([u'2015/03/01', u'2015/03/02', u'2015/03/03', u'2015/03/04',
u'2015/03/05'],
dtype='<U10')
(Pdb) p result
array([u'2015/03/01', u'2015/03/02', u'2015/03/03', u'2015/03/04',
u'2015/03/05'],
dtype='>U10')
tentative fix is easy -- remove '>' from type definition. But I wondered if that is desired -- does pandas assume to enforce little-endianness or not? if it doesn't force -- then actually a proper fix, to maintain the same check of consistent endianness, would be to prefix with = and not <.
Please advise!