upgrade version of 'black'

Author: MarcoGorelli

asv_bench/benchmarks/arithmetic.py

@@ -125,7 +125,7 @@ def setup(self, op):
         arr1 = np.random.randn(n_rows, int(n_cols / 2)).astype("f8")
         arr2 = np.random.randn(n_rows, int(n_cols / 2)).astype("f4")
         df = pd.concat(
-            [pd.DataFrame(arr1), pd.DataFrame(arr2)], axis=1, ignore_index=True,
+            [pd.DataFrame(arr1), pd.DataFrame(arr2)], axis=1, ignore_index=True
         )
         # should already be the case, but just to be sure
         df._consolidate_inplace()

doc/make.py

@@ -286,7 +286,7 @@ def main():
 
     joined = ",".join(cmds)
     argparser = argparse.ArgumentParser(
-        description="pandas documentation builder", epilog=f"Commands: {joined}",
+        description="pandas documentation builder", epilog=f"Commands: {joined}"
     )
 
     joined = ", ".join(cmds)

doc/source/conf.py

@@ -308,7 +308,7 @@
 
     for method in methods:
         # ... and each of its public methods
-        moved_api_pages.append((f"{old}.{method}", f"{new}.{method}",))
+        moved_api_pages.append((f"{old}.{method}", f"{new}.{method}"))
 
 if pattern is None:
     html_additional_pages = {

pandas/_vendored/typing_extensions.py

@@ -2116,8 +2116,7 @@ def __init_subclass__(cls, *args, **kwargs):
             raise TypeError(f"Cannot subclass {cls.__module__}.Annotated")
 
     def _strip_annotations(t):
-        """Strips the annotations from a given type.
-        """
+        """Strips the annotations from a given type."""
         if isinstance(t, _AnnotatedAlias):
             return _strip_annotations(t.__origin__)
         if isinstance(t, typing._GenericAlias):

pandas/core/aggregation.py

@@ -387,7 +387,7 @@ def validate_func_kwargs(
 
 
 def transform(
-    obj: FrameOrSeries, func: AggFuncType, axis: Axis, *args, **kwargs,
+    obj: FrameOrSeries, func: AggFuncType, axis: Axis, *args, **kwargs
 ) -> FrameOrSeries:
     """
     Transform a DataFrame or Series

pandas/core/algorithms.py

@@ -1023,11 +1023,10 @@ def checked_add_with_arr(arr, b, arr_mask=None, b_mask=None):
         to_raise = ((np.iinfo(np.int64).max - b2 < arr) & not_nan).any()
     else:
         to_raise = (
-            ((np.iinfo(np.int64).max - b2[mask1] < arr[mask1]) & not_nan[mask1]).any()
-            or (
-                (np.iinfo(np.int64).min - b2[mask2] > arr[mask2]) & not_nan[mask2]
-            ).any()
-        )
+            (np.iinfo(np.int64).max - b2[mask1] < arr[mask1]) & not_nan[mask1]
+        ).any() or (
+            (np.iinfo(np.int64).min - b2[mask2] > arr[mask2]) & not_nan[mask2]
+        ).any()
 
     if to_raise:
         raise OverflowError("Overflow in int64 addition")

pandas/core/array_algos/replace.py

@@ -17,7 +17,7 @@
 
 
 def compare_or_regex_search(
-    a: ArrayLike, b: Union[Scalar, Pattern], regex: bool, mask: ArrayLike,
+    a: ArrayLike, b: Union[Scalar, Pattern], regex: bool, mask: ArrayLike
 ) -> Union[ArrayLike, bool]:
     """
     Compare two array_like inputs of the same shape or two scalar values

pandas/core/frame.py

@@ -449,9 +449,7 @@ def __init__(
         if isinstance(data, BlockManager):
             if index is None and columns is None and dtype is None and copy is False:
                 # GH#33357 fastpath
-                NDFrame.__init__(
-                    self, data,
-                )
+                NDFrame.__init__(self, data)
                 return
 
             mgr = self._init_mgr(
@@ -5747,7 +5745,7 @@ def nsmallest(self, n, columns, keep="first") -> DataFrame:
                   population    GDP alpha-2
         Tuvalu         11300     38      TV
         Anguilla       11300    311      AI
-        Iceland       337000  17036	     IS
+        Iceland       337000  17036      IS
 
         When using ``keep='last'``, ties are resolved in reverse order:
 
@@ -7142,7 +7140,7 @@ def unstack(self, level=-1, fill_value=None):
 
         return unstack(self, level, fill_value)
 
-    @Appender(_shared_docs["melt"] % dict(caller="df.melt(", other="melt",))
+    @Appender(_shared_docs["melt"] % dict(caller="df.melt(", other="melt"))
     def melt(
         self,
         id_vars=None,
@@ -8624,7 +8622,7 @@ def blk_func(values):
             # After possibly _get_data and transposing, we are now in the
             #  simple case where we can use BlockManager.reduce
             res = df._mgr.reduce(blk_func)
-            out = df._constructor(res,).iloc[0].rename(None)
+            out = df._constructor(res).iloc[0].rename(None)
             if out_dtype is not None:
                 out = out.astype(out_dtype)
             if axis == 0 and is_object_dtype(out.dtype):

pandas/core/series.py

@@ -199,7 +199,7 @@ class Series(base.IndexOpsMixin, generic.NDFrame):
     # Constructors
 
     def __init__(
-        self, data=None, index=None, dtype=None, name=None, copy=False, fastpath=False,
+        self, data=None, index=None, dtype=None, name=None, copy=False, fastpath=False
     ):
 
         if (
@@ -209,9 +209,7 @@ def __init__(
             and copy is False
         ):
             # GH#33357 called with just the SingleBlockManager
-            NDFrame.__init__(
-                self, data,
-            )
+            NDFrame.__init__(self, data)
             self.name = name
             return
 
@@ -331,7 +329,8 @@ def __init__(
                 data = SingleBlockManager.from_array(data, index)
 
         generic.NDFrame.__init__(
-            self, data,
+            self,
+            data,
         )
         self.name = name
         self._set_axis(0, index, fastpath=True)

pandas/core/sorting.py

@@ -72,7 +72,7 @@ def get_indexer_indexer(
         )
     elif isinstance(target, ABCMultiIndex):
         indexer = lexsort_indexer(
-            target._get_codes_for_sorting(), orders=ascending, na_position=na_position,
+            target._get_codes_for_sorting(), orders=ascending, na_position=na_position
         )
     else:
         # Check monotonic-ness before sort an index (GH 11080)