blackify

pandas/core/groupby/groupby.py

@@ -1774,8 +1774,7 @@ def nth(self, n: Union[int, List[int]], dropna: Optional[str] = None) -> DataFra
  result_index = self.grouper.result_index
  out.index = result_index[ids[mask]]
 
- if not self.observed and isinstance(
- result_index, CategoricalIndex):
+ if not self.observed and isinstance(result_index, CategoricalIndex):
  out = out.reindex(result_index)
 
  return out.sort_index() if self.sort else out

pandas/tests/groupby/test_categorical.py

@@ -433,15 +433,15 @@ def test_observed_groups_with_nan(observed):
 
 def test_observed_nth():
  # GH 26385
- cat = pd.Categorical(['a', np.nan, np.nan], categories=['a', 'b', 'c'])
+ cat = pd.Categorical(["a", np.nan, np.nan], categories=["a", "b", "c"])
  ser = pd.Series([1, 2, 3])
- df = pd.DataFrame({'cat': cat, 'ser': ser})
+ df = pd.DataFrame({"cat": cat, "ser": ser})
 
- result = df.groupby('cat', observed=False)['ser'].nth(0)
+ result = df.groupby("cat", observed=False)["ser"].nth(0)
 
- index = pd.Categorical(['a', 'b', 'c'], categories=['a', 'b', 'c'])
- expected = pd.Series([1, np.nan, np.nan], index=index, name='ser')
- expected.index.name = 'cat'
+ index = pd.Categorical(["a", "b", "c"], categories=["a", "b", "c"])
+ expected = pd.Series([1, np.nan, np.nan], index=index, name="ser")
+ expected.index.name = "cat"
 
  tm.assert_series_equal(result, expected)