use pytest mark parametrize to fix input and expected values

pandas/tests/reductions/test_describe_ndframe.py

@@ -4,25 +4,22 @@
 We test the describe_ndframe function.
 """
 
-import pytest
 import numpy as np
+import pytest
 
 from pandas.core.methods.describe import _refine_percentiles
 
-def test_refine_percentiles():
+@pytest.mark.parametrize(
+    "percentiles_, expected", [
+        (None, np.array([0.25, 0.5, 0.75])),
+        ([], np.array([0.5])),
+        ([0.3, 0.6], np.array([0.3, 0.6])),
+    ]
+)
+def test_refine_percentiles(percentiles_, expected):
     """
     Check the performance of the _refine_percentiles when multiple
     values are passed.
     """
 
-    # by default 0.25, 0.50, 0.75 is returned
-    # or, when None is passed return behavior is the same
-    assert _refine_percentiles() == np.array([0.25, 0.5, 0.75])
-    assert _refine_percentiles(percentiles = None) == np.array([0.25, 0.5, 0.75])
-
-    # when any value is passed, then the function should return
-    percentiles_ = [0.3, 0.6]
-    assert _refine_percentiles(percentiles_) == np.array(percentiles_)
-
-    # when a blank list is passed, then should return only 0.5
-    assert _refine_percentiles(percentiles = []) == np.array([0.5])
+    assert np.array_equal(_refine_percentiles(percentiles_), expected)