BUG: GH25871 -- fix PEP 8 issues on test source

Author: kpflugshaupt

pandas/tests/groupby/test_categorical.py

@@ -453,28 +453,32 @@ def test_dataframe_categorical_with_nan(observed):
     tm.assert_frame_equal(result, expected)
 
 
-@pytest.mark.parametrize("ordered",  [True, False])
+@pytest.mark.parametrize("ordered", [True, False])
 @pytest.mark.parametrize("observed", [True, False])
-@pytest.mark.parametrize("sort",     [True, False])
+@pytest.mark.parametrize("sort", [True, False])
 def test_dataframe_categorical_ordered_observed_sort(ordered, observed, sort):
-    # GH 25871: Fix groupby sorting on ordered Categoricals 
-    # Build a dataframe with a Categorical having one unobserved category ('AWOL'), and a Series with identical values
-    cat = pd.Categorical(['d', 'a', 'b', 'a', 'd', 'b'], categories=['a', 'b', 'AWOL', 'd'], ordered=ordered)
-    val = pd.Series     (['d', 'a', 'b', 'a', 'd', 'b'])
-    df  = pd.DataFrame({'cat': cat, 'val': val})
+    # GH 25871: Fix groupby sorting on ordered Categoricals
+    # Build a dataframe with a Categorical having one unobserved category ('AWOL'), 
+    # and a Series with identical values
+    cat = pd.Categorical(['d', 'a', 'b', 'a', 'd', 'b'], 
+                         categories=['a', 'b', 'AWOL', 'd'], 
+                         ordered=ordered)
+    val = pd.Series(['d', 'a', 'b', 'a', 'd', 'b'])
+    df = pd.DataFrame({'cat': cat, 'val': val})
 
     # aggregate on the Categorical
-    result = df.groupby('cat', observed=observed, sort=sort)['val'].agg('first')
+    result = (df.groupby('cat', observed=observed, sort=sort)['val']
+                .aggregate('first'))
 
-    # If ordering is correct, we expect index labels equal to aggregation results,
-    # except for 'observed=False', when index contains 'AWOL' and aggregation None
+    # If ordering works, we expect index labels equal to aggregation results,
+    # except for 'observed=False': index contains 'AWOL' and aggregation None
     label = pd.Series(result.index.array, dtype='object')
-    aggr  = pd.Series(result.array)
+    aggr = pd.Series(result.array)
     if not observed:
         aggr[aggr.isna()] = 'AWOL'
-    tm.assert_equal(label, aggr)    
+    tm.assert_equal(label, aggr)
+
 
-    
 def test_datetime():
     # GH9049: ensure backward compatibility
     levels = pd.date_range('2014-01-01', periods=4)