fixed pep8 style

Author: DataInformer

doc/source/whatsnew/v1.0.3.rst

@@ -23,7 +23,8 @@ Fixed regressions
 Bug fixes
 ~~~~~~~~~
 Fixed Series.value_counts so that normalize excludes NA values when dropna=False. (:issue:`25970`)
-Fixed Dataframe Groupby value_counts with bins (:issue:`32471')
+Fixed Dataframe Groupby value_counts with bins (:issue:`32471`)
+
 Contributors
 ~~~~~~~~~~~~
 

pandas/core/base.py

@@ -1258,6 +1258,7 @@ def value_counts(
         1.0    1
         dtype: int64
         """
+
         result = value_counts(
             self,
             sort=sort,

pandas/tests/base/test_value_counts.py

@@ -192,12 +192,18 @@ def test_value_counts_bins(index_or_series):
 
     # handle normalizing bins with NA's properly
     # see GH25970
-    s2 = Series([1,2,2,3,3,3, np.nan, np.nan, 4, 5])
+    s2 = Series([1, 2, 2, 3, 3, 3, np.nan, np.nan, 4, 5])
     intervals = IntervalIndex.from_breaks([0.995, 2.333, 3.667, 5.0])
-    expected_dropna = Series([0.375, 0.375, 0.25], intervals.take([1,0,2]))
+    expected_dropna = Series([0.375, 0.375, 0.25], intervals.take([1, 0, 2]))
     expected_keepna_vals = np.array([0.3, 0.3, 0.2, 0.2])
-    tm.assert_series_equal(s2.value_counts(dropna=True, normalize=True, bins=3), expected_dropna)
-    tm.assert_numpy_array_equal(s2.value_counts(dropna=False, normalize=True, bins=3).values, expected_keepna_vals)
+    tm.assert_series_equal(
+        s2.value_counts(dropna=True, normalize=True, bins=3), expected_dropna
+    )
+    tm.assert_numpy_array_equal(
+        s2.value_counts(dropna=False, normalize=True, bins=3).values,
+        expected_keepna_vals,
+    )
+
 
 def test_value_counts_datetime64(index_or_series):
     klass = index_or_series