COMPAT: Avoid td.skip decorator

It wasn't backported, so we use pytest directly.

Author: TomAugspurger

pandas/tests/test_nanops.py

@@ -1,6 +1,7 @@
 # -*- coding: utf-8 -*-
 from __future__ import division, print_function
 
+from distutils.version import LooseVersion
 from functools import partial
 
 import pytest
@@ -468,8 +469,10 @@ def test_nankurt(self):
                             allow_str=False, allow_date=False,
                             allow_tdelta=False)
 
-    @td.skip_if_no("numpy", min_version="1.10.0")
     def test_nanprod(self):
+        if LooseVersion(np.__version__) < LooseVersion("1.10.0"):
+            raise pytest.skip("np.nanprod added in 1.10.0")
+
         self.check_funs(nanops.nanprod, np.prod, allow_str=False,
                         allow_date=False, allow_tdelta=False,
                         empty_targfunc=np.nanprod)

pandas/tests/test_panel.py

@@ -3,6 +3,7 @@
 
 from warnings import catch_warnings
 from datetime import datetime
+from distutils.version import LooseVersion
 import operator
 import pytest
 
@@ -87,8 +88,10 @@ def test_sum(self):
     def test_mean(self):
         self._check_stat_op('mean', np.mean)
 
-    @td.skip_if_no("numpy", min_version="1.10.0")
     def test_prod(self):
+        if LooseVersion(np.__version__) < LooseVersion("1.10.0"):
+            raise pytest.skip("np.nanprod added in 1.10.0")
+
         self._check_stat_op('prod', np.prod, skipna_alternative=np.nanprod)
 
     def test_median(self):

pandas/tests/test_panel4d.py

@@ -4,6 +4,7 @@
 import operator
 import pytest
 from warnings import catch_warnings
+from distutils.version import LooseVersion
 import numpy as np
 
 from pandas import Series, Index, isna, notna
@@ -41,8 +42,10 @@ def test_sum(self):
     def test_mean(self):
         self._check_stat_op('mean', np.mean)
 
-    @td.skip_if_no("numpy", min_version="1.10.0")
     def test_prod(self):
+        if LooseVersion(np.__version__) < LooseVersion("1.10.0"):
+            raise pytest.skip("np.nanprod added in 1.10.0")
+
         self._check_stat_op('prod', np.prod, skipna_alternative=np.nanprod)
 
     def test_median(self):