diff --git a/pandas/tests/dtypes/test_common.py b/pandas/tests/dtypes/test_common.py
index e0be34b14a97d..2146704fea95f 100644
--- a/pandas/tests/dtypes/test_common.py
+++ b/pandas/tests/dtypes/test_common.py
@@ -9,6 +9,7 @@
 
 import pandas.core.dtypes.common as com
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 
 
 class TestPandasDtype(object):
@@ -132,21 +133,22 @@ def test_is_object():
     assert not com.is_object_dtype([1, 2, 3])
 
 
-def test_is_sparse():
+@pytest.mark.parametrize("check_scipy", [
+    False, pytest.param(True, marks=td.skip_if_no_scipy)
+])
+def test_is_sparse(check_scipy):
     assert com.is_sparse(pd.SparseArray([1, 2, 3]))
     assert com.is_sparse(pd.SparseSeries([1, 2, 3]))
 
     assert not com.is_sparse(np.array([1, 2, 3]))
 
-    # This test will only skip if the previous assertions
-    # pass AND scipy is not installed.
-    sparse = pytest.importorskip("scipy.sparse")
-    assert not com.is_sparse(sparse.bsr_matrix([1, 2, 3]))
+    if check_scipy:
+        import scipy.sparse
+        assert not com.is_sparse(scipy.sparse.bsr_matrix([1, 2, 3]))
 
 
+@td.skip_if_no_scipy
 def test_is_scipy_sparse():
-    tm._skip_if_no_scipy()
-
     from scipy.sparse import bsr_matrix
     assert com.is_scipy_sparse(bsr_matrix([1, 2, 3]))
 
@@ -501,7 +503,10 @@ def test_is_bool_dtype():
     assert com.is_bool_dtype(pd.Index([True, False]))
 
 
-def test_is_extension_type():
+@pytest.mark.parametrize("check_scipy", [
+    False, pytest.param(True, marks=td.skip_if_no_scipy)
+])
+def test_is_extension_type(check_scipy):
     assert not com.is_extension_type([1, 2, 3])
     assert not com.is_extension_type(np.array([1, 2, 3]))
     assert not com.is_extension_type(pd.DatetimeIndex([1, 2, 3]))
@@ -517,10 +522,9 @@ def test_is_extension_type():
     s = pd.Series([], dtype=dtype)
     assert com.is_extension_type(s)
 
-    # This test will only skip if the previous assertions
-    # pass AND scipy is not installed.
-    sparse = pytest.importorskip("scipy.sparse")
-    assert not com.is_extension_type(sparse.bsr_matrix([1, 2, 3]))
+    if check_scipy:
+        import scipy.sparse
+        assert not com.is_extension_type(scipy.sparse.bsr_matrix([1, 2, 3]))
 
 
 def test_is_complex_dtype():
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index 577f4238c2328..e8bdd2a551a34 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -37,6 +37,7 @@
     _ensure_int32,
     _ensure_categorical)
 from pandas.util import testing as tm
+import pandas.util._test_decorators as td
 
 
 @pytest.fixture(params=[True, False], ids=str)
@@ -1190,8 +1191,8 @@ def test_nan_to_nat_conversions():
         assert (s[8].value == np.datetime64('NaT').astype(np.int64))
 
 
+@td.skip_if_no_scipy
 def test_is_scipy_sparse(spmatrix):  # noqa: F811
-    tm._skip_if_no_scipy()
     assert is_scipy_sparse(spmatrix([[0, 1]]))
     assert not is_scipy_sparse(np.array([1]))
 
diff --git a/pandas/tests/frame/test_analytics.py b/pandas/tests/frame/test_analytics.py
index 7014929db4c2d..17d711f937bf7 100644
--- a/pandas/tests/frame/test_analytics.py
+++ b/pandas/tests/frame/test_analytics.py
@@ -22,6 +22,7 @@
 import pandas.io.formats.printing as printing
 
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 from pandas.tests.frame.common import TestData
 
 
@@ -30,22 +31,22 @@ class TestDataFrameAnalytics(TestData):
     # ---------------------------------------------------------------------=
     # Correlation and covariance
 
+    @td.skip_if_no_scipy
     def test_corr_pearson(self):
-        tm._skip_if_no_scipy()
         self.frame['A'][:5] = nan
         self.frame['B'][5:10] = nan
 
         self._check_method('pearson')
 
+    @td.skip_if_no_scipy
     def test_corr_kendall(self):
-        tm._skip_if_no_scipy()
         self.frame['A'][:5] = nan
         self.frame['B'][5:10] = nan
 
         self._check_method('kendall')
 
+    @td.skip_if_no_scipy
     def test_corr_spearman(self):
-        tm._skip_if_no_scipy()
         self.frame['A'][:5] = nan
         self.frame['B'][5:10] = nan
 
@@ -62,8 +63,8 @@ def _check_method(self, method='pearson', check_minp=False):
             expected.loc['A', 'B'] = expected.loc['B', 'A'] = nan
             tm.assert_frame_equal(result, expected)
 
+    @td.skip_if_no_scipy
     def test_corr_non_numeric(self):
-        tm._skip_if_no_scipy()
         self.frame['A'][:5] = nan
         self.frame['B'][5:10] = nan
 
@@ -72,9 +73,8 @@ def test_corr_non_numeric(self):
         expected = self.mixed_frame.loc[:, ['A', 'B', 'C', 'D']].corr()
         tm.assert_frame_equal(result, expected)
 
+    @td.skip_if_no_scipy
     def test_corr_nooverlap(self):
-        tm._skip_if_no_scipy()
-
         # nothing in common
         for meth in ['pearson', 'kendall', 'spearman']:
             df = DataFrame({'A': [1, 1.5, 1, np.nan, np.nan, np.nan],
@@ -88,9 +88,8 @@ def test_corr_nooverlap(self):
             assert rs.loc['B', 'B'] == 1
             assert isna(rs.loc['C', 'C'])
 
+    @td.skip_if_no_scipy
     def test_corr_constant(self):
-        tm._skip_if_no_scipy()
-
         # constant --> all NA
 
         for meth in ['pearson', 'spearman']:
@@ -106,9 +105,8 @@ def test_corr_int(self):
         df3.cov()
         df3.corr()
 
+    @td.skip_if_no_scipy
     def test_corr_int_and_boolean(self):
-        tm._skip_if_no_scipy()
-
         # when dtypes of pandas series are different
         # then ndarray will have dtype=object,
         # so it need to be properly handled
@@ -719,8 +717,8 @@ def test_sem(self):
             result = nanops.nansem(arr, axis=0)
             assert not (result < 0).any()
 
+    @td.skip_if_no_scipy
     def test_skew(self):
-        tm._skip_if_no_scipy()
         from scipy.stats import skew
 
         def alt(x):
@@ -730,9 +728,8 @@ def alt(x):
 
         self._check_stat_op('skew', alt)
 
+    @td.skip_if_no_scipy
     def test_kurt(self):
-        tm._skip_if_no_scipy()
-
         from scipy.stats import kurtosis
 
         def alt(x):
diff --git a/pandas/tests/frame/test_missing.py b/pandas/tests/frame/test_missing.py
index 7e8869cbdeefb..2e4e8b9582cf6 100644
--- a/pandas/tests/frame/test_missing.py
+++ b/pandas/tests/frame/test_missing.py
@@ -16,6 +16,7 @@
 from pandas.util.testing import assert_series_equal, assert_frame_equal
 
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 from pandas.tests.frame.common import TestData, _check_mixed_float
 
 
@@ -646,9 +647,8 @@ def test_interp_nan_idx(self):
         with pytest.raises(NotImplementedError):
             df.interpolate(method='values')
 
+    @td.skip_if_no_scipy
     def test_interp_various(self):
-        tm._skip_if_no_scipy()
-
         df = DataFrame({'A': [1, 2, np.nan, 4, 5, np.nan, 7],
                         'C': [1, 2, 3, 5, 8, 13, 21]})
         df = df.set_index('C')
@@ -695,8 +695,8 @@ def test_interp_various(self):
         expected.A.loc[13] = 5
         assert_frame_equal(result, expected, check_dtype=False)
 
+    @td.skip_if_no_scipy
     def test_interp_alt_scipy(self):
-        tm._skip_if_no_scipy()
         df = DataFrame({'A': [1, 2, np.nan, 4, 5, np.nan, 7],
                         'C': [1, 2, 3, 5, 8, 13, 21]})
         result = df.interpolate(method='barycentric')
@@ -739,8 +739,6 @@ def test_interp_rowwise(self):
         expected[4] = expected[4].astype(np.float64)
         assert_frame_equal(result, expected)
 
-        # scipy route
-        tm._skip_if_no_scipy()
         result = df.interpolate(axis=1, method='values')
         assert_frame_equal(result, expected)
 
@@ -753,7 +751,10 @@ def test_rowwise_alt(self):
                         1: [1, 2, 3, 4, 3, 2, 1, 0, -1]})
         df.interpolate(axis=0)
 
-    def test_interp_leading_nans(self):
+    @pytest.mark.parametrize("check_scipy", [
+        False, pytest.param(True, marks=td.skip_if_no_scipy)
+    ])
+    def test_interp_leading_nans(self, check_scipy):
         df = DataFrame({"A": [np.nan, np.nan, .5, .25, 0],
                         "B": [np.nan, -3, -3.5, np.nan, -4]})
         result = df.interpolate()
@@ -761,9 +762,9 @@ def test_interp_leading_nans(self):
         expected['B'].loc[3] = -3.75
         assert_frame_equal(result, expected)
 
-        tm._skip_if_no_scipy()
-        result = df.interpolate(method='polynomial', order=1)
-        assert_frame_equal(result, expected)
+        if check_scipy:
+            result = df.interpolate(method='polynomial', order=1)
+            assert_frame_equal(result, expected)
 
     def test_interp_raise_on_only_mixed(self):
         df = DataFrame({'A': [1, 2, np.nan, 4],
diff --git a/pandas/tests/plotting/test_datetimelike.py b/pandas/tests/plotting/test_datetimelike.py
index e87c67a682d46..7f9ae7b8bb1da 100644
--- a/pandas/tests/plotting/test_datetimelike.py
+++ b/pandas/tests/plotting/test_datetimelike.py
@@ -643,10 +643,10 @@ def test_secondary_y_ts(self):
         assert ax.get_yaxis().get_visible()
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_secondary_kde(self):
         if not self.mpl_ge_1_5_0:
             pytest.skip("mpl is not supported")
-        tm._skip_if_no_scipy()
         _skip_if_no_scipy_gaussian_kde()
 
         ser = Series(np.random.randn(10))
diff --git a/pandas/tests/plotting/test_deprecated.py b/pandas/tests/plotting/test_deprecated.py
index d2f8e13a2444b..2c2d371921d2f 100644
--- a/pandas/tests/plotting/test_deprecated.py
+++ b/pandas/tests/plotting/test_deprecated.py
@@ -24,9 +24,8 @@
 class TestDeprecatedNameSpace(TestPlotBase):
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_scatter_plot_legacy(self):
-        tm._skip_if_no_scipy()
-
         df = pd.DataFrame(randn(100, 2))
 
         with tm.assert_produces_warning(FutureWarning):
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index 3b3f6666340b8..d61b0a40380f3 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -1398,8 +1398,8 @@ def test_boxplot_subplots_return_type(self):
                 check_ax_title=False)
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_kde_df(self):
-        tm._skip_if_no_scipy()
         _skip_if_no_scipy_gaussian_kde()
         if not self.mpl_ge_1_5_0:
             pytest.skip("mpl is not supported")
@@ -1422,8 +1422,8 @@ def test_kde_df(self):
         self._check_ax_scales(axes, yaxis='log')
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_kde_missing_vals(self):
-        tm._skip_if_no_scipy()
         _skip_if_no_scipy_gaussian_kde()
         if not self.mpl_ge_1_5_0:
             pytest.skip("mpl is not supported")
@@ -1949,8 +1949,8 @@ def test_hist_colors(self):
         tm.close()
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_kde_colors(self):
-        tm._skip_if_no_scipy()
         _skip_if_no_scipy_gaussian_kde()
         if not self.mpl_ge_1_5_0:
             pytest.skip("mpl is not supported")
@@ -1974,8 +1974,8 @@ def test_kde_colors(self):
         self._check_colors(ax.get_lines(), linecolors=rgba_colors)
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_kde_colors_and_styles_subplots(self):
-        tm._skip_if_no_scipy()
         _skip_if_no_scipy_gaussian_kde()
         if not self.mpl_ge_1_5_0:
             pytest.skip("mpl is not supported")
diff --git a/pandas/tests/plotting/test_misc.py b/pandas/tests/plotting/test_misc.py
index 1753bc6387d33..bb590d5232b62 100644
--- a/pandas/tests/plotting/test_misc.py
+++ b/pandas/tests/plotting/test_misc.py
@@ -52,8 +52,8 @@ def test_bootstrap_plot(self):
 @td.skip_if_no_mpl
 class TestDataFramePlots(TestPlotBase):
 
+    @td.skip_if_no_scipy
     def test_scatter_matrix_axis(self):
-        tm._skip_if_no_scipy()
         scatter_matrix = plotting.scatter_matrix
 
         with tm.RNGContext(42):
diff --git a/pandas/tests/plotting/test_series.py b/pandas/tests/plotting/test_series.py
index 6dd7e1e9882b2..2458fc0dc992c 100644
--- a/pandas/tests/plotting/test_series.py
+++ b/pandas/tests/plotting/test_series.py
@@ -589,6 +589,7 @@ def test_plot_fails_with_dupe_color_and_style(self):
             x.plot(style='k--', color='k', ax=ax)
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_hist_kde(self):
         if not self.mpl_ge_1_5_0:
             pytest.skip("mpl is not supported")
@@ -602,7 +603,6 @@ def test_hist_kde(self):
         ylabels = ax.get_yticklabels()
         self._check_text_labels(ylabels, [''] * len(ylabels))
 
-        tm._skip_if_no_scipy()
         _skip_if_no_scipy_gaussian_kde()
         _check_plot_works(self.ts.plot.kde)
         _check_plot_works(self.ts.plot.density)
@@ -615,8 +615,8 @@ def test_hist_kde(self):
         self._check_text_labels(ylabels, [''] * len(ylabels))
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_kde_kwargs(self):
-        tm._skip_if_no_scipy()
         _skip_if_no_scipy_gaussian_kde()
         if not self.mpl_ge_1_5_0:
             pytest.skip("mpl is not supported")
@@ -633,8 +633,8 @@ def test_kde_kwargs(self):
         self._check_text_labels(ax.yaxis.get_label(), 'Density')
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_kde_missing_vals(self):
-        tm._skip_if_no_scipy()
         _skip_if_no_scipy_gaussian_kde()
         if not self.mpl_ge_1_5_0:
             pytest.skip("mpl is not supported")
@@ -665,6 +665,7 @@ def test_hist_kwargs(self):
             tm.close()
 
     @pytest.mark.slow
+    @td.skip_if_no_scipy
     def test_hist_kde_color(self):
         if not self.mpl_ge_1_5_0:
             pytest.skip("mpl is not supported")
@@ -675,7 +676,6 @@ def test_hist_kde_color(self):
         assert len(ax.patches) == 10
         self._check_colors(ax.patches, facecolors=['b'] * 10)
 
-        tm._skip_if_no_scipy()
         _skip_if_no_scipy_gaussian_kde()
         _, ax = self.plt.subplots()
         ax = self.ts.plot.kde(logy=True, color='r', ax=ax)
diff --git a/pandas/tests/series/test_analytics.py b/pandas/tests/series/test_analytics.py
index 289b5c01c1263..b206d84c0d6f8 100644
--- a/pandas/tests/series/test_analytics.py
+++ b/pandas/tests/series/test_analytics.py
@@ -23,6 +23,7 @@
 from pandas.util.testing import (assert_series_equal, assert_almost_equal,
                                  assert_frame_equal, assert_index_equal)
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 from .common import TestData
 
 
@@ -282,9 +283,8 @@ def test_sem(self):
         result = s.sem(ddof=1)
         assert isna(result)
 
+    @td.skip_if_no_scipy
     def test_skew(self):
-        tm._skip_if_no_scipy()
-
         from scipy.stats import skew
         alt = lambda x: skew(x, bias=False)
         self._check_stat_op('skew', alt)
@@ -302,9 +302,8 @@ def test_skew(self):
                 assert 0 == s.skew()
                 assert (df.skew() == 0).all()
 
+    @td.skip_if_no_scipy
     def test_kurt(self):
-        tm._skip_if_no_scipy()
-
         from scipy.stats import kurtosis
         alt = lambda x: kurtosis(x, bias=False)
         self._check_stat_op('kurt', alt)
@@ -708,9 +707,8 @@ def test_modulo(self):
             expected = Series([nan, 0.0])
             assert_series_equal(result, expected)
 
+    @td.skip_if_no_scipy
     def test_corr(self):
-        tm._skip_if_no_scipy()
-
         import scipy.stats as stats
 
         # full overlap
@@ -739,9 +737,8 @@ def test_corr(self):
         expected, _ = stats.pearsonr(A, B)
         tm.assert_almost_equal(result, expected)
 
+    @td.skip_if_no_scipy
     def test_corr_rank(self):
-        tm._skip_if_no_scipy()
-
         import scipy
         import scipy.stats as stats
 
diff --git a/pandas/tests/series/test_missing.py b/pandas/tests/series/test_missing.py
index b23dc37016b69..04fdebad6165b 100644
--- a/pandas/tests/series/test_missing.py
+++ b/pandas/tests/series/test_missing.py
@@ -19,6 +19,7 @@
 from pandas.core.series import remove_na
 from pandas.util.testing import assert_series_equal, assert_frame_equal
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 
 from .common import TestData
 
@@ -853,8 +854,8 @@ def test_interpolate(self):
         non_ts[0] = np.NaN
         pytest.raises(ValueError, non_ts.interpolate, method='time')
 
+    @td.skip_if_no_scipy
     def test_interpolate_pchip(self):
-        tm._skip_if_no_scipy()
         _skip_if_no_pchip()
 
         ser = Series(np.sort(np.random.uniform(size=100)))
@@ -866,8 +867,8 @@ def test_interpolate_pchip(self):
         # does not blow up, GH5977
         interp_s[49:51]
 
+    @td.skip_if_no_scipy
     def test_interpolate_akima(self):
-        tm._skip_if_no_scipy()
         _skip_if_no_akima()
 
         ser = Series([10, 11, 12, 13])
@@ -881,9 +882,8 @@ def test_interpolate_akima(self):
         interp_s = ser.reindex(new_index).interpolate(method='akima')
         assert_series_equal(interp_s[1:3], expected)
 
+    @td.skip_if_no_scipy
     def test_interpolate_piecewise_polynomial(self):
-        tm._skip_if_no_scipy()
-
         ser = Series([10, 11, 12, 13])
 
         expected = Series([11.00, 11.25, 11.50, 11.75,
@@ -896,9 +896,8 @@ def test_interpolate_piecewise_polynomial(self):
             method='piecewise_polynomial')
         assert_series_equal(interp_s[1:3], expected)
 
+    @td.skip_if_no_scipy
     def test_interpolate_from_derivatives(self):
-        tm._skip_if_no_scipy()
-
         ser = Series([10, 11, 12, 13])
 
         expected = Series([11.00, 11.25, 11.50, 11.75,
@@ -911,19 +910,17 @@ def test_interpolate_from_derivatives(self):
             method='from_derivatives')
         assert_series_equal(interp_s[1:3], expected)
 
-    def test_interpolate_corners(self):
-        s = Series([np.nan, np.nan])
-        assert_series_equal(s.interpolate(), s)
-
-        s = Series([]).interpolate()
-        assert_series_equal(s.interpolate(), s)
-
-        tm._skip_if_no_scipy()
+    @pytest.mark.parametrize("kwargs", [
+        {},
+        pytest.param({'method': 'polynomial', 'order': 1},
+                     marks=td.skip_if_no_scipy)
+    ])
+    def test_interpolate_corners(self, kwargs):
         s = Series([np.nan, np.nan])
-        assert_series_equal(s.interpolate(method='polynomial', order=1), s)
+        assert_series_equal(s.interpolate(**kwargs), s)
 
         s = Series([]).interpolate()
-        assert_series_equal(s.interpolate(method='polynomial', order=1), s)
+        assert_series_equal(s.interpolate(**kwargs), s)
 
     def test_interpolate_index_values(self):
         s = Series(np.nan, index=np.sort(np.random.rand(30)))
@@ -953,17 +950,17 @@ def test_interpolate_non_ts(self):
         with pytest.raises(ValueError):
             s.interpolate(method='time')
 
-    # New interpolation tests
-    def test_nan_interpolate(self):
+    @pytest.mark.parametrize("kwargs", [
+        {},
+        pytest.param({'method': 'polynomial', 'order': 1},
+                     marks=td.skip_if_no_scipy)
+    ])
+    def test_nan_interpolate(self, kwargs):
         s = Series([0, 1, np.nan, 3])
-        result = s.interpolate()
+        result = s.interpolate(**kwargs)
         expected = Series([0., 1., 2., 3.])
         assert_series_equal(result, expected)
 
-        tm._skip_if_no_scipy()
-        result = s.interpolate(method='polynomial', order=1)
-        assert_series_equal(result, expected)
-
     def test_nan_irregular_index(self):
         s = Series([1, 2, np.nan, 4], index=[1, 3, 5, 9])
         result = s.interpolate()
@@ -976,16 +973,15 @@ def test_nan_str_index(self):
         expected = Series([0., 1., 2., 2.], index=list('abcd'))
         assert_series_equal(result, expected)
 
+    @td.skip_if_no_scipy
     def test_interp_quad(self):
-        tm._skip_if_no_scipy()
         sq = Series([1, 4, np.nan, 16], index=[1, 2, 3, 4])
         result = sq.interpolate(method='quadratic')
         expected = Series([1., 4., 9., 16.], index=[1, 2, 3, 4])
         assert_series_equal(result, expected)
 
+    @td.skip_if_no_scipy
     def test_interp_scipy_basic(self):
-        tm._skip_if_no_scipy()
-
         s = Series([1, 3, np.nan, 12, np.nan, 25])
         # slinear
         expected = Series([1., 3., 7.5, 12., 18.5, 25.])
@@ -1147,9 +1143,8 @@ def test_interp_limit_before_ends(self):
                                limit_direction='both')
         assert_series_equal(result, expected)
 
+    @td.skip_if_no_scipy
     def test_interp_all_good(self):
-        # scipy
-        tm._skip_if_no_scipy()
         s = Series([1, 2, 3])
         result = s.interpolate(method='polynomial', order=1)
         assert_series_equal(result, s)
@@ -1158,7 +1153,11 @@ def test_interp_all_good(self):
         result = s.interpolate()
         assert_series_equal(result, s)
 
-    def test_interp_multiIndex(self):
+    @pytest.mark.parametrize("check_scipy", [
+        False,
+        pytest.param(True, marks=td.skip_if_no_scipy)
+    ])
+    def test_interp_multiIndex(self, check_scipy):
         idx = MultiIndex.from_tuples([(0, 'a'), (1, 'b'), (2, 'c')])
         s = Series([1, 2, np.nan], index=idx)
 
@@ -1167,18 +1166,18 @@ def test_interp_multiIndex(self):
         result = s.interpolate()
         assert_series_equal(result, expected)
 
-        tm._skip_if_no_scipy()
-        with pytest.raises(ValueError):
-            s.interpolate(method='polynomial', order=1)
+        if check_scipy:
+            with pytest.raises(ValueError):
+                s.interpolate(method='polynomial', order=1)
 
+    @td.skip_if_no_scipy
     def test_interp_nonmono_raise(self):
-        tm._skip_if_no_scipy()
         s = Series([1, np.nan, 3], index=[0, 2, 1])
         with pytest.raises(ValueError):
             s.interpolate(method='krogh')
 
+    @td.skip_if_no_scipy
     def test_interp_datetime64(self):
-        tm._skip_if_no_scipy()
         df = Series([1, np.nan, 3], index=date_range('1/1/2000', periods=3))
         result = df.interpolate(method='nearest')
         expected = Series([1., 1., 3.],
@@ -1192,25 +1191,22 @@ def test_interp_limit_no_nans(self):
         expected = s
         assert_series_equal(result, expected)
 
-    def test_no_order(self):
-        tm._skip_if_no_scipy()
+    @td.skip_if_no_scipy
+    @pytest.mark.parametrize("method", ['polynomial', 'spline'])
+    def test_no_order(self, method):
         s = Series([0, 1, np.nan, 3])
         with pytest.raises(ValueError):
-            s.interpolate(method='polynomial')
-        with pytest.raises(ValueError):
-            s.interpolate(method='spline')
+            s.interpolate(method=method)
 
+    @td.skip_if_no_scipy
     def test_spline(self):
-        tm._skip_if_no_scipy()
         s = Series([1, 2, np.nan, 4, 5, np.nan, 7])
         result = s.interpolate(method='spline', order=1)
         expected = Series([1., 2., 3., 4., 5., 6., 7.])
         assert_series_equal(result, expected)
 
+    @td.skip_if_no('scipy', min_version='0.15')
     def test_spline_extrapolate(self):
-        tm.skip_if_no_package(
-            'scipy', min_version='0.15',
-            app='setting ext on scipy.interpolate.UnivariateSpline')
         s = Series([1, 2, 3, 4, np.nan, 6, np.nan])
         result3 = s.interpolate(method='spline', order=1, ext=3)
         expected3 = Series([1., 2., 3., 4., 5., 6., 6.])
@@ -1220,25 +1216,23 @@ def test_spline_extrapolate(self):
         expected1 = Series([1., 2., 3., 4., 5., 6., 7.])
         assert_series_equal(result1, expected1)
 
+    @td.skip_if_no_scipy
     def test_spline_smooth(self):
-        tm._skip_if_no_scipy()
         s = Series([1, 2, np.nan, 4, 5.1, np.nan, 7])
         assert (s.interpolate(method='spline', order=3, s=0)[5] !=
                 s.interpolate(method='spline', order=3)[5])
 
+    @td.skip_if_no_scipy
     def test_spline_interpolation(self):
-        tm._skip_if_no_scipy()
-
         s = Series(np.arange(10) ** 2)
         s[np.random.randint(0, 9, 3)] = np.nan
         result1 = s.interpolate(method='spline', order=1)
         expected1 = s.interpolate(method='spline', order=1)
         assert_series_equal(result1, expected1)
 
+    @td.skip_if_no_scipy
     def test_spline_error(self):
         # see gh-10633
-        tm._skip_if_no_scipy()
-
         s = pd.Series(np.arange(10) ** 2)
         s[np.random.randint(0, 9, 3)] = np.nan
         with pytest.raises(ValueError):
diff --git a/pandas/tests/sparse/test_series.py b/pandas/tests/sparse/test_series.py
index 1dc1c7f1575cc..7deeedacd1b23 100644
--- a/pandas/tests/sparse/test_series.py
+++ b/pandas/tests/sparse/test_series.py
@@ -13,6 +13,7 @@
                     isna, compat, _np_version_under1p12)
 from pandas.tseries.offsets import BDay
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 from pandas.compat import range
 from pandas.core.reshape.util import cartesian_product
 
@@ -997,11 +998,11 @@ def test_round_trip_preserve_multiindex_names(self):
                               check_names=True)
 
 
+@td.skip_if_no_scipy
 class TestSparseSeriesScipyInteraction(object):
     # Issue 8048: add SparseSeries coo methods
 
     def setup_method(self, method):
-        tm._skip_if_no_scipy()
         import scipy.sparse
         # SparseSeries inputs used in tests, the tests rely on the order
         self.sparse_series = []
@@ -1108,7 +1109,6 @@ def test_from_coo_nodense_index(self):
     def test_from_coo_long_repr(self):
         # GH 13114
         # test it doesn't raise error. Formatting is tested in test_format
-        tm._skip_if_no_scipy()
         import scipy.sparse
 
         sparse = SparseSeries.from_coo(scipy.sparse.rand(350, 18))
diff --git a/pandas/tests/test_algos.py b/pandas/tests/test_algos.py
index 7ef77e4c78e10..d7fc5033bab90 100644
--- a/pandas/tests/test_algos.py
+++ b/pandas/tests/test_algos.py
@@ -19,6 +19,7 @@
 import pandas.core.algorithms as algos
 from pandas.core.common import _asarray_tuplesafe
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 from pandas.core.dtypes.dtypes import CategoricalDtype as CDT
 from pandas.compat.numpy import np_array_datetime64_compat
 from pandas.util.testing import assert_almost_equal
@@ -1109,8 +1110,8 @@ def test_unique_label_indices():
 
 class TestRank(object):
 
+    @td.skip_if_no_scipy
     def test_scipy_compat(self):
-        tm._skip_if_no_scipy()
         from scipy.stats import rankdata
 
         def _check(arr):
diff --git a/pandas/tests/test_panel.py b/pandas/tests/test_panel.py
index f51bf0c4e476a..040c3adbcaf93 100644
--- a/pandas/tests/test_panel.py
+++ b/pandas/tests/test_panel.py
@@ -26,6 +26,7 @@
                                  makeCustomDataframe as mkdf)
 import pandas.core.panel as panelm
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 
 
 def make_test_panel():
@@ -104,11 +105,9 @@ def test_min(self):
     def test_max(self):
         self._check_stat_op('max', np.max)
 
+    @td.skip_if_no_scipy
     def test_skew(self):
-        try:
-            from scipy.stats import skew
-        except ImportError:
-            pytest.skip("no scipy.stats.skew")
+        from scipy.stats import skew
 
         def this_skew(x):
             if len(x) < 3:
diff --git a/pandas/tests/test_panel4d.py b/pandas/tests/test_panel4d.py
index c42bedebe2f23..b064e3c7012bc 100644
--- a/pandas/tests/test_panel4d.py
+++ b/pandas/tests/test_panel4d.py
@@ -16,6 +16,7 @@
 from pandas.util.testing import (assert_frame_equal, assert_series_equal,
                                  assert_almost_equal)
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 
 
 def add_nans(panel4d):
@@ -59,11 +60,9 @@ def test_min(self):
     def test_max(self):
         self._check_stat_op('max', np.max)
 
+    @td.skip_if_no_scipy
     def test_skew(self):
-        try:
-            from scipy.stats import skew
-        except ImportError:
-            pytest.skip("no scipy.stats.skew")
+        from scipy.stats import skew
 
         def this_skew(x):
             if len(x) < 3:
diff --git a/pandas/tests/test_window.py b/pandas/tests/test_window.py
index 661c7dfcc50fc..bee925823eebe 100644
--- a/pandas/tests/test_window.py
+++ b/pandas/tests/test_window.py
@@ -17,6 +17,7 @@
 from pandas.core.base import SpecificationError
 from pandas.errors import UnsupportedFunctionCall
 import pandas.util.testing as tm
+import pandas.util._test_decorators as td
 from pandas.compat import range, zip, PY3
 
 N, K = 100, 10
@@ -251,9 +252,8 @@ def test_count_nonnumeric_types(self):
         expected = df.notna().astype(float)
         tm.assert_frame_equal(result, expected)
 
+    @td.skip_if_no_scipy
     def test_window_with_args(self):
-        tm._skip_if_no_scipy()
-
         # make sure that we are aggregating window functions correctly with arg
         r = Series(np.random.randn(100)).rolling(window=10, min_periods=1,
                                                  win_type='gaussian')
@@ -289,9 +289,9 @@ class TestWindow(Base):
     def setup_method(self, method):
         self._create_data()
 
+    @td.skip_if_no_scipy
     def test_constructor(self):
         # GH 12669
-        tm._skip_if_no_scipy()
 
         for o in [self.series, self.frame]:
             c = o.rolling
@@ -367,9 +367,9 @@ def test_constructor(self):
                 with pytest.raises(ValueError):
                     c(window=2, min_periods=1, center=w)
 
+    @td.skip_if_no_scipy
     def test_constructor_with_win_type(self):
         # GH 13383
-        tm._skip_if_no_scipy()
         for o in [self.series, self.frame]:
             c = o.rolling
             c(0, win_type='boxcar')
@@ -839,10 +839,9 @@ def test_rolling_count(self):
     def test_rolling_mean(self):
         self._check_moment_func(mom.rolling_mean, np.mean, name='mean')
 
+    @td.skip_if_no_scipy
     def test_cmov_mean(self):
         # GH 8238
-        tm._skip_if_no_scipy()
-
         vals = np.array([6.95, 15.21, 4.72, 9.12, 13.81, 13.49, 16.68, 9.48,
                          10.63, 14.48])
         xp = np.array([np.nan, np.nan, 9.962, 11.27, 11.564, 12.516, 12.818,
@@ -856,10 +855,9 @@ def test_cmov_mean(self):
         rs = Series(vals).rolling(5, center=True).mean()
         tm.assert_series_equal(xp, rs)
 
+    @td.skip_if_no_scipy
     def test_cmov_window(self):
         # GH 8238
-        tm._skip_if_no_scipy()
-
         vals = np.array([6.95, 15.21, 4.72, 9.12, 13.81, 13.49, 16.68, 9.48,
                          10.63, 14.48])
         xp = np.array([np.nan, np.nan, 9.962, 11.27, 11.564, 12.516, 12.818,
@@ -873,10 +871,9 @@ def test_cmov_window(self):
         rs = Series(vals).rolling(5, win_type='boxcar', center=True).mean()
         tm.assert_series_equal(xp, rs)
 
+    @td.skip_if_no_scipy
     def test_cmov_window_corner(self):
         # GH 8238
-        tm._skip_if_no_scipy()
-
         # all nan
         vals = np.empty(10, dtype=float)
         vals.fill(np.nan)
@@ -897,10 +894,9 @@ def test_cmov_window_corner(self):
             assert np.isnan(rs).all()
             assert len(rs) == 5
 
+    @td.skip_if_no_scipy
     def test_cmov_window_frame(self):
         # Gh 8238
-        tm._skip_if_no_scipy()
-
         vals = np.array([[12.18, 3.64], [10.18, 9.16], [13.24, 14.61],
                          [4.51, 8.11], [6.15, 11.44], [9.14, 6.21],
                          [11.31, 10.67], [2.94, 6.51], [9.42, 8.39], [12.44,
@@ -929,9 +925,8 @@ def test_cmov_window_frame(self):
         rs = DataFrame(vals).rolling(5, win_type='boxcar', center=True).sum()
         tm.assert_frame_equal(DataFrame(xp), rs)
 
+    @td.skip_if_no_scipy
     def test_cmov_window_na_min_periods(self):
-        tm._skip_if_no_scipy()
-
         # min_periods
         vals = Series(np.random.randn(10))
         vals[4] = np.nan
@@ -942,10 +937,9 @@ def test_cmov_window_na_min_periods(self):
                           center=True).mean()
         tm.assert_series_equal(xp, rs)
 
+    @td.skip_if_no_scipy
     def test_cmov_window_regular(self):
         # GH 8238
-        tm._skip_if_no_scipy()
-
         win_types = ['triang', 'blackman', 'hamming', 'bartlett', 'bohman',
                      'blackmanharris', 'nuttall', 'barthann']
 
@@ -975,10 +969,9 @@ def test_cmov_window_regular(self):
             rs = Series(vals).rolling(5, win_type=wt, center=True).mean()
             tm.assert_series_equal(xp, rs)
 
+    @td.skip_if_no_scipy
     def test_cmov_window_regular_linear_range(self):
         # GH 8238
-        tm._skip_if_no_scipy()
-
         win_types = ['triang', 'blackman', 'hamming', 'bartlett', 'bohman',
                      'blackmanharris', 'nuttall', 'barthann']
 
@@ -992,10 +985,9 @@ def test_cmov_window_regular_linear_range(self):
             rs = Series(vals).rolling(5, win_type=wt, center=True).mean()
             tm.assert_series_equal(xp, rs)
 
+    @td.skip_if_no_scipy
     def test_cmov_window_regular_missing_data(self):
         # GH 8238
-        tm._skip_if_no_scipy()
-
         win_types = ['triang', 'blackman', 'hamming', 'bartlett', 'bohman',
                      'blackmanharris', 'nuttall', 'barthann']
 
@@ -1025,10 +1017,9 @@ def test_cmov_window_regular_missing_data(self):
             rs = Series(vals).rolling(5, win_type=wt, min_periods=3).mean()
             tm.assert_series_equal(xp, rs)
 
+    @td.skip_if_no_scipy
     def test_cmov_window_special(self):
         # GH 8238
-        tm._skip_if_no_scipy()
-
         win_types = ['kaiser', 'gaussian', 'general_gaussian', 'slepian']
         kwds = [{'beta': 1.}, {'std': 1.}, {'power': 2.,
                                             'width': 2.}, {'width': 0.5}]
@@ -1052,10 +1043,9 @@ def test_cmov_window_special(self):
             rs = Series(vals).rolling(5, win_type=wt, center=True).mean(**k)
             tm.assert_series_equal(xp, rs)
 
+    @td.skip_if_no_scipy
     def test_cmov_window_special_linear_range(self):
         # GH 8238
-        tm._skip_if_no_scipy()
-
         win_types = ['kaiser', 'gaussian', 'general_gaussian', 'slepian']
         kwds = [{'beta': 1.}, {'std': 1.}, {'power': 2.,
                                             'width': 2.}, {'width': 0.5}]
@@ -1259,19 +1249,15 @@ def test_rolling_var(self):
         self._check_moment_func(mom.rolling_var, lambda x: np.var(x, ddof=0),
                                 name='var', ddof=0)
 
+    @td.skip_if_no_scipy
     def test_rolling_skew(self):
-        try:
-            from scipy.stats import skew
-        except ImportError:
-            pytest.skip('no scipy')
+        from scipy.stats import skew
         self._check_moment_func(mom.rolling_skew,
                                 lambda x: skew(x, bias=False), name='skew')
 
+    @td.skip_if_no_scipy
     def test_rolling_kurt(self):
-        try:
-            from scipy.stats import kurtosis
-        except ImportError:
-            pytest.skip('no scipy')
+        from scipy.stats import kurtosis
         self._check_moment_func(mom.rolling_kurt,
                                 lambda x: kurtosis(x, bias=False), name='kurt')
 
diff --git a/pandas/util/_test_decorators.py b/pandas/util/_test_decorators.py
index 0b2d50d06a66c..95a9a8fed42f7 100644
--- a/pandas/util/_test_decorators.py
+++ b/pandas/util/_test_decorators.py
@@ -94,6 +94,11 @@ def _skip_if_not_us_locale():
         return True
 
 
+def _skip_if_no_scipy():
+    return not (safe_import('scipy.stats') and safe_import('scipy.sparse') and
+                safe_import('scipy.interpolate'))
+
+
 def skip_if_no(package, min_version=None):
     """
     Generic function to help skip test functions when required packages are not
@@ -119,9 +124,11 @@ def skip_if_no(package, min_version=None):
         The decorated function wrapped within a pytest ``skip_if`` mark
     """
     def decorated_func(func):
+        msg = "Could not import '{}'".format(package)
+        if min_version:
+            msg += " satisfying a min_version of {}".format(min_version)
         return pytest.mark.skipif(
-            not safe_import(package, min_version=min_version),
-            reason="Could not import '{}'".format(package)
+            not safe_import(package, min_version=min_version), reason=msg
         )(func)
     return decorated_func
 
@@ -144,3 +151,5 @@ def decorated_func(func):
                                            reason="Specific locale is set "
                                            "{lang}".format(
                                                lang=locale.getlocale()[0]))
+skip_if_no_scipy = pytest.mark.skipif(_skip_if_no_scipy(),
+                                      reason="Missing SciPy requirement")