CLN: Parametrize tests over min,max

pandas/tests/arrays/categorical/test_analytics.py

@@ -11,14 +11,15 @@
 
 
 class TestCategoricalAnalytics:
- def test_min_max_not_ordered(self):
+ @pytest.mark.parametrize("aggregation", ["min", "max"])
+ def test_min_max_not_ordered_raises(self, aggregation):
  # unordered cats have no min/max
  cat = Categorical(["a", "b", "c", "d"], ordered=False)
  msg = "Categorical is not ordered for operation {}"
- with pytest.raises(TypeError, match=msg.format("min")):
- cat.min()
- with pytest.raises(TypeError, match=msg.format("max")):
- cat.max()
+ agg_func = getattr(cat, aggregation)
+
+ with pytest.raises(TypeError, match=msg.format(aggregation)):
+ agg_func()
 
  def test_min_max_ordered(self):
  cat = Categorical(["a", "b", "c", "d"], ordered=True)
@@ -43,14 +44,13 @@ def test_min_max_ordered(self):
  (Series(date_range("2020-01-01", periods=3), dtype="category"), np.NaN),
  ],
  )
- def test_min_max_ordered_empty(self, categories, expected):
+ @pytest.mark.parametrize("aggregation", ["min", "max"])
+ def test_min_max_ordered_empty(self, categories, expected, aggregation):
  # GH 30227
  cat = Categorical([], categories=list("ABC"), ordered=True)
 
- result = cat.min()
- assert result is expected
-
- result = cat.max()
+ agg_func = getattr(cat, aggregation)
+ result = agg_func()
  assert result is expected
 
  @pytest.mark.parametrize("skipna", [True, False])