fix pep8 issues

Author: simonariddell

pandas/tests/groupby/test_transform.py

@@ -729,20 +729,22 @@ def interweave(list_obj):
     (-1, 'ffill', None), (-1, 'ffill', 1),
     (-1, 'bfill', None), (-1, 'bfill', 1)])
 def test_pct_change(test_series, shuffle, periods, fill_method, limit):
-    # Groupby pct change uses an apply if monotonic and a vectorized operation if non-monotonic
+    # Groupby pct change uses an apply if monotonic
+    # and a vectorized operation if non-monotonic
     # Shuffle parameter tests each
     vals = [np.nan, np.nan, 1, 2, 4, 10, np.nan, np.nan]
     keys = ['a', 'b']
-    df = DataFrame({'key': [k for j in list(map(lambda x: [x] * len(vals), keys)) for k in j],
-                    'vals': vals * 2})
+    key_v = [k for j in list(map(lambda x: [x] * len(vals), keys)) for k in j]
+    df = DataFrame({'key': key_v, 'vals': vals * 2})
     if shuffle:
         df = df.reindex(np.random.permutation(len(df))).reset_index(drop=True)
 
     manual_apply = []
     for k in keys:
-        manual_apply.append(Series(df.loc[df.key == k, 'vals'].values).pct_change(periods=periods,
-                                                                                  fill_method=fill_method,
-                                                                                  limit=limit))
+        subgroup = Series(df.loc[df.key == k, 'vals'].values)
+        manual_apply.append(subgroup.pct_change(periods=periods,
+                                                fill_method=fill_method,
+                                                limit=limit))
     exp_vals = pd.concat(manual_apply).reset_index(drop=True)
     exp = pd.DataFrame(exp_vals, columns=['_pct_change'])
     grp = df.groupby('key')