TST: add test for numpy ops, esp. nanmin/max bug for np<1.13

pandas/tests/test_nanops.py

@@ -13,6 +13,7 @@
 import pandas.core.nanops as nanops
 import pandas.util.testing as tm
 import pandas.util._test_decorators as td
+from pandas.compat.numpy import _np_version_under1p13
 
 use_bn = nanops._USE_BOTTLENECK
 
@@ -1015,3 +1016,34 @@ def test_use_bottleneck():
         assert not pd.get_option('use_bottleneck')
 
         pd.set_option('use_bottleneck', use_bn)
+
+
+@pytest.mark.parametrize("numpy_op, expected", [
+    (np.sum, 10),
+    (np.nansum, 10),
+    (np.mean, 2.5),
+    (np.nanmean, 2.5),
+    (np.median, 2.5),
+    (np.nanmedian, 2.5),
+    (np.min, 1),
+    (np.max, 4),
+])
+def test_numpy_ops(numpy_op, expected):
+    # GH8383
+    result = numpy_op(pd.Series([1, 2, 3, 4]))
+    assert result == expected
+
+
+@pytest.mark.parametrize("numpy_op, expected", [
+    (np.nanmin, 1),
+    (np.nanmax, 4),
+])
+def test_numpy_ops_np_version_under1p13(numpy_op, expected):
+    # GH8383
+    result = numpy_op(pd.Series([1, 2, 3, 4]))
+    if _np_version_under1p13:
+        # bug for numpy < 1.13, where result is a series, should be a scalar
+        with pytest.raises(ValueError):
+            assert result == expected
+    else:
+        assert result == expected