doc and PEP8

doc/source/whatsnew/v0.20.0.txt

@@ -308,6 +308,7 @@ Other enhancements
 - ``pd.types.concat.union_categoricals`` gained the ``ignore_ordered`` argument to allow ignoring the ordered attribute of unioned categoricals (:issue:`13410`). See the :ref:`categorical union docs <categorical.union>` for more information.
 - ``pandas.io.json.json_normalize()`` with an empty ``list`` will return an empty ``DataFrame`` (:issue:`15534`)
 - ``pd.DataFrame.to_latex`` and ``pd.DataFrame.to_string`` now allow optional header aliases. (:issue:`15536`)
+- ``pd.test()`` will now pass with SciPy 0.19.0. (:issue:`15662`)
 
 .. _ISO 8601 duration: https://en.wikipedia.org/wiki/ISO_8601#Durations
 

pandas/core/window.py

@@ -544,9 +544,8 @@ def _pop_args(win_type, arg_names, kwargs):
                 return all_args
 
             win_type = _validate_win_type(self.win_type, kwargs)
-            # GH #15662.
-            # fftbins should be False; previously it was a mistake on pandas' side.
-            return sig.get_window(win_type, window, fftbins=False).astype(float)
+            # GH #15662. `False` makes symmetric window, rather than periodic.
+            return sig.get_window(win_type, window, False).astype(float)
 
     def _apply_window(self, mean=True, how=None, **kwargs):
         """

pandas/tests/frame/test_missing.py

@@ -19,6 +19,13 @@
 from pandas.tests.frame.common import TestData, _check_mixed_float
 
 
+try:
+    import scipy
+    _is_scipy_ge_0190 = scipy.__version__ >= LooseVersion('0.19.0')
+except:
+    _is_scipy_ge_0190 = False
+
+
 def _skip_if_no_pchip():
     try:
         from scipy.interpolate import pchip_interpolate  # noqa
@@ -561,8 +568,10 @@ def test_interp_various(self):
         assert_frame_equal(result, expected)
 
         result = df.interpolate(method='cubic')
-        import scipy
-        if scipy.__version__ >= LooseVersion('0.19.0'):
+        # GH #15662.
+        # new cubic and quadratic interpolation algorithms from scipy 0.19.0.
+        # previously `splmake` was used. See scipy/scipy#6710
+        if _is_scipy_ge_0190:
             expected.A.loc[3] = 2.81547781
             expected.A.loc[13] = 5.52964175
         else:
@@ -576,7 +585,7 @@ def test_interp_various(self):
         assert_frame_equal(result, expected, check_dtype=False)
 
         result = df.interpolate(method='quadratic')
-        if scipy.__version__ >= LooseVersion('0.19.0'):
+        if _is_scipy_ge_0190:
             expected.A.loc[3] = 2.82150771
             expected.A.loc[13] = 6.12648668
         else:
@@ -594,7 +603,6 @@ def test_interp_various(self):
         expected.A.loc[13] = 5
         assert_frame_equal(result, expected, check_dtype=False)
 
-
     def test_interp_alt_scipy(self):
         tm._skip_if_no_scipy()
         df = DataFrame({'A': [1, 2, np.nan, 4, 5, np.nan, 7],

pandas/tests/series/test_missing.py

@@ -18,6 +18,12 @@
 
 from .common import TestData
 
+try:
+    import scipy
+    _is_scipy_ge_0190 = scipy.__version__ >= LooseVersion('0.19.0')
+except:
+    _is_scipy_ge_0190 = False
+
 
 def _skip_if_no_pchip():
     try:
@@ -853,8 +859,10 @@ def test_interp_scipy_basic(self):
         result = s.interpolate(method='zero', downcast='infer')
         assert_series_equal(result, expected)
         # quadratic
-        import scipy
-        if scipy.__version__ >= LooseVersion('0.19.0'):
+        # GH #15662.
+        # new cubic and quadratic interpolation algorithms from scipy 0.19.0.
+        # previously `splmake` was used. See scipy/scipy#6710
+        if _is_scipy_ge_0190:
             expected = Series([1, 3., 6.823529, 12., 18.058824, 25.])
         else:
             expected = Series([1, 3., 6.769231, 12., 18.230769, 25.])