Lint fixes

Author: WillAyd

pandas/core/groupby.py

@@ -1002,7 +1002,8 @@ def _cython_transform(self, how, numeric_only=True, **kwargs):
                 continue
 
             try:
-                result, names = self.grouper.transform(obj.values, how, **kwargs)
+                result, names = self.grouper.transform(obj.values, how,
+                                                       **kwargs)
             except NotImplementedError:
                 continue
             except AssertionError as e:
@@ -1776,9 +1777,9 @@ def cumcount(self, ascending=True):
     def rank(self, method='average', ascending=True, na_option='keep',
              pct=False, axis=0):
         """Rank within each group"""
-        return self._cython_transform('rank', numeric_only=False, ties_method=method,
-                                      ascending=ascending, na_option=na_option,
-                                      pct=pct, axis=axis)
+        return self._cython_transform('rank', numeric_only=False,
+                                      ties_method=method, ascending=ascending,
+                                      na_option=na_option, pct=pct, axis=axis)
 
     @Substitution(name='groupby')
     @Appender(_doc_template)

pandas/tests/groupby/test_groupby.py

@@ -1930,8 +1930,8 @@ def test_rank_args(self, grps, vals, ties_method, ascending, pct, exp):
         key = np.repeat(grps, len(vals))
         vals = vals * len(grps)
         df = DataFrame({'key': key, 'val': vals})
-        result = df.groupby('key').rank(method=ties_method, ascending=ascending,
-                                        pct=pct)
+        result = df.groupby('key').rank(method=ties_method,
+                                        ascending=ascending, pct=pct)
 
         exp_df = DataFrame(exp * len(grps), columns=['val'])
         assert_frame_equal(result, exp_df)
@@ -2024,7 +2024,8 @@ def test_rank_args_missing(self, grps, vals, ties_method, ascending,
         key = np.repeat(grps, len(vals))
         vals = vals * len(grps)
         df = DataFrame({'key': key, 'val': vals})
-        result = df.groupby('key').rank(method=ties_method, ascending=ascending,
+        result = df.groupby('key').rank(method=ties_method,
+                                        ascending=ascending,
                                         na_option=na_option, pct=pct)
 
         exp_df = DataFrame(exp * len(grps), columns=['val'])