TST: compat with numpy 1.14
I *think* this is a very recent change in numpy in how ndarrays are printed. So we would conditionally change the expected if ``not _np_version_under1p14``

https://travis-ci.org/pandas-dev/pandas/jobs/297507212

```
____________________ TestDataFrameDataTypes.test_astype_str ____________________
[gw0] linux -- Python 3.6.3 /home/travis/miniconda3/envs/pandas/bin/python
self = <pandas.tests.frame.test_dtypes.TestDataFrameDataTypes object at 0x7f31d2d6d748>
    def test_astype_str(self):
        # GH9757
        a = Series(date_range('2010-01-04', periods=5))
        b = Series(date_range('3/6/2012 00:00', periods=5, tz='US/Eastern'))
        c = Series([Timedelta(x, unit='d') for x in range(5)])
        d = Series(range(5))
        e = Series([0.0, 0.2, 0.4, 0.6, 0.8])
    
        df = DataFrame({'a': a, 'b': b, 'c': c, 'd': d, 'e': e})
    
        # datetimelike
        # Test str and unicode on python 2.x and just str on python 3.x
        for tt in set([str, compat.text_type]):
            result = df.astype(tt)
    
            expected = DataFrame({
                'a': list(map(tt, map(lambda x: Timestamp(x)._date_repr,
                                      a._values))),
                'b': list(map(tt, map(Timestamp, b._values))),
                'c': list(map(tt, map(lambda x: Timedelta(x)
                                      ._repr_base(format='all'), c._values))),
                'd': list(map(tt, d._values)),
                'e': list(map(tt, e._values)),
            })
    
            assert_frame_equal(result, expected)
    
        # float/nan
        # 11302
        # consistency in astype(str)
        for tt in set([str, compat.text_type]):
            result = DataFrame([np.NaN]).astype(tt)
            expected = DataFrame(['nan'])
            assert_frame_equal(result, expected)
    
            result = DataFrame([1.12345678901234567890]).astype(tt)
            expected = DataFrame(['1.12345678901'])
>           assert_frame_equal(result, expected)
pandas/tests/frame/test_dtypes.py:535: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/util/testing.py:1397: in assert_frame_equal
    obj='DataFrame.iloc[:, {idx}]'.format(idx=i))
pandas/util/testing.py:1276: in assert_series_equal
    obj='{obj}'.format(obj=obj))
pandas/_libs/testing.pyx:59: in pandas._libs.testing.assert_almost_equal
    cpdef assert_almost_equal(a, b,
pandas/_libs/testing.pyx:173: in pandas._libs.testing.assert_almost_equal
    raise_assert_detail(obj, msg, lobj, robj)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
obj = 'DataFrame.iloc[:, 0]'
message = 'DataFrame.iloc[:, 0] values are different (100.0 %)'
left = '[1.1234567890123457]', right = '[1.12345678901]', diff = None
    def raise_assert_detail(obj, message, left, right, diff=None):
        if isinstance(left, np.ndarray):
            left = pprint_thing(left)
        elif is_categorical_dtype(left):
            left = repr(left)
        if isinstance(right, np.ndarray):
            right = pprint_thing(right)
        elif is_categorical_dtype(right):
            right = repr(right)
    
        msg = """{obj} are different
    
    {message}
    [left]:  {left}
    [right]: {right}""".format(obj=obj, message=message, left=left, right=right)
    
        if diff is not None:
            msg += "\n[diff]: {diff}".format(diff=diff)
    
>       raise AssertionError(msg)
E       AssertionError: DataFrame.iloc[:, 0] are different
E       
E       DataFrame.iloc[:, 0] values are different (100.0 %)
E       [left]:  [1.1234567890123457]
E       [right]: [1.12345678901]
pandas/util/testing.py:1093: AssertionError
```