Fix E501: format long lines in series.py and test_subtraction_nanindex.py

Author: rit4rosa

pandas/core/series.py

@@ -5904,9 +5904,12 @@ def _align_for_op(self, right, align_asobject=False, fill_value=np.nan):
         if not (hasattr(left.index, "levels") or hasattr(right.index, "levels")):
             if align_asobject:
                 if left.empty or right.empty:
-                    if left.dtype not in (object, np.bool_) or right.dtype not in (object, np.bool_):
+                    if left.dtype not in (object, np.bool_) or right.dtype not in (
+                        object,
+                        np.bool_,
+                    ):
                         return left.iloc[0:0], right.iloc[0:0]
-            return left.align(right, join='outer', fill_value=fill_value)
+            return left.align(right, join="outer", fill_value=fill_value)
 
         if hasattr(left.index, "levels") and not hasattr(right.index, "levels"):
             if left.empty or right.empty:
@@ -5918,8 +5921,8 @@ def _align_for_op(self, right, align_asobject=False, fill_value=np.nan):
                 right_aligned = right.reindex(first_level, fill_value=fill_value)
                 return left, right_aligned
 
-        return left.align(right, join='outer', fill_value=fill_value)
-        
+        return left.align(right, join="outer", fill_value=fill_value)
+
     def _binop(self, other: Series, func, level=None, fill_value=None) -> Series:
         """
         Perform generic binary operation with optional fill value.

pandas/tests/series/test_subtraction_nanindex.py

@@ -1,38 +1,34 @@
-import pytest
-import pandas as pd
 import numpy as np
+
+import pandas as pd
 import pandas.testing as tm
 
+
 def test_series_subtraction_with_nan_and_levels():
     ix1 = pd.MultiIndex.from_arrays(
         [
             [np.nan, 81, 81, 82, 82],
             [np.nan] * 5,
-            pd.to_datetime([np.nan, '2018-06-01', '2018-07-01', '2018-07-01', '2018-08-01'])
+            pd.to_datetime(
+                [np.nan, "2018-06-01", "2018-07-01", "2018-07-01", "2018-08-01"]
+            ),
         ],
-        names=['foo', 'bar', 'date']
+        names=["foo", "bar", "date"],
     )
 
-    s1 = pd.Series(
-        [np.nan, 25.058969, 22.519751, 20.847981, 21.625236],
-        index=ix1
-    )
+    s1 = pd.Series([np.nan, 25.058969, 22.519751, 20.847981, 21.625236], index=ix1)
 
-    ix2 = pd.Index([81, 82, 83, 84, 85, 86, 87], name='foo')
+    ix2 = pd.Index([81, 82, 83, 84, 85, 86, 87], name="foo")
     s2 = pd.Series(
-        [28.2800, 25.2500, 22.2200, 16.7660, 14.0087, 14.9480, 29.2900],
-        index=ix2
+        [28.2800, 25.2500, 22.2200, 16.7660, 14.0087, 14.9480, 29.2900], index=ix2
     )
 
     expected = pd.Series(
-        [np.nan, -3.221031, -5.760249, -4.402019, -3.624764],
-        index=ix1,
-        dtype='float64'
+        [np.nan, -3.221031, -5.760249, -4.402019, -3.624764], index=ix1, dtype="float64"
     )
 
     result = s1 - s2
 
-    result = result.astype('float64')
+    result = result.astype("float64")
 
     tm.assert_series_equal(result, expected)
-