STY: Enable some passing rules (pandas-dev#57200)

* Enable B006

* Enable B011

* Enable B019

* Enable B020

* Enable B020

* Enable PYI and othe rule

* Enable PLC1901

* Use values instead of items

* Use union

* Ignore one case

Author: mroeschke

pandas/_libs/tslibs/vectorized.pyi

@@ -1,7 +1,5 @@
-"""
-For cython types that cannot be represented precisely, closest-available
-python equivalents are used, and the precise types kept as adjacent comments.
-"""
+# For cython types that cannot be represented precisely, closest-available
+# python equivalents are used, and the precise types kept as adjacent comments.
 from datetime import tzinfo
 
 import numpy as np

pandas/core/indexers/objects.py

@@ -399,7 +399,7 @@ def get_window_bounds(
         start_arrays = []
         end_arrays = []
         window_indices_start = 0
-        for key, indices in self.groupby_indices.items():
+        for indices in self.groupby_indices.values():
             index_array: np.ndarray | None
 
             if self.index_array is not None:

pandas/io/formats/style_render.py

@@ -1996,7 +1996,7 @@ class Tooltips:
 
     def __init__(
         self,
-        css_props: CSSProperties = [
+        css_props: CSSProperties = [  # noqa: B006
             ("visibility", "hidden"),
             ("position", "absolute"),
             ("z-index", 1),

pandas/io/json/_normalize.py

@@ -537,8 +537,8 @@ def _recursive_extract(data, path, seen_meta, level: int = 0) -> None:
         if values.ndim > 1:
             # GH 37782
             values = np.empty((len(v),), dtype=object)
-            for i, v in enumerate(v):
-                values[i] = v
+            for i, val in enumerate(v):
+                values[i] = val
 
         result[k] = values.repeat(lengths)
     return result

pandas/tests/arrays/masked/test_arithmetic.py

@@ -55,15 +55,15 @@ def test_array_scalar_like_equivalence(data, all_arithmetic_operators):
     scalar_array = pd.array([scalar] * len(data), dtype=data.dtype)
 
     # TODO also add len-1 array (np.array([scalar], dtype=data.dtype.numpy_dtype))
-    for scalar in [scalar, data.dtype.type(scalar)]:
+    for val in [scalar, data.dtype.type(scalar)]:
         if is_bool_not_implemented(data, all_arithmetic_operators):
             msg = "operator '.*' not implemented for bool dtypes"
             with pytest.raises(NotImplementedError, match=msg):
-                op(data, scalar)
+                op(data, val)
             with pytest.raises(NotImplementedError, match=msg):
                 op(data, scalar_array)
         else:
-            result = op(data, scalar)
+            result = op(data, val)
             expected = op(data, scalar_array)
             tm.assert_extension_array_equal(result, expected)
 
@@ -214,13 +214,13 @@ def test_error_len_mismatch(data, all_arithmetic_operators):
         msg = "operator '.*' not implemented for bool dtypes"
         err = NotImplementedError
 
-    for other in [other, np.array(other)]:
+    for val in [other, np.array(other)]:
         with pytest.raises(err, match=msg):
-            op(data, other)
+            op(data, val)
 
         s = pd.Series(data)
         with pytest.raises(err, match=msg):
-            op(s, other)
+            op(s, val)
 
 
 @pytest.mark.parametrize("op", ["__neg__", "__abs__", "__invert__"])

pandas/tests/copy_view/index/test_index.py

@@ -10,7 +10,7 @@
 from pandas.tests.copy_view.util import get_array
 
 
-def index_view(index_data=[1, 2]):
+def index_view(index_data):
     df = DataFrame({"a": index_data, "b": 1.5})
     view = df[:]
     df = df.set_index("a", drop=True)
@@ -142,7 +142,7 @@ def test_index_from_index(using_copy_on_write, warn_copy_on_write):
     ],
 )
 def test_index_ops(using_copy_on_write, func, request):
-    idx, view_ = index_view()
+    idx, view_ = index_view([1, 2])
     expected = idx.copy(deep=True)
     if "astype" in request.node.callspec.id:
         expected = expected.astype("Int64")

pandas/tests/frame/test_query_eval.py

@@ -949,8 +949,8 @@ def test_str_query_method(self, parser, engine):
             ops = 2 * ([eq] + [ne])
             msg = r"'(Not)?In' nodes are not implemented"
 
-            for lhs, op, rhs in zip(lhs, ops, rhs):
-                ex = f"{lhs} {op} {rhs}"
+            for lh, op_, rh in zip(lhs, ops, rhs):
+                ex = f"{lh} {op_} {rh}"
                 with pytest.raises(NotImplementedError, match=msg):
                     df.query(
                         ex,
@@ -990,8 +990,8 @@ def test_str_list_query_method(self, parser, engine):
             ops = 2 * ([eq] + [ne])
             msg = r"'(Not)?In' nodes are not implemented"
 
-            for lhs, op, rhs in zip(lhs, ops, rhs):
-                ex = f"{lhs} {op} {rhs}"
+            for lh, ops_, rh in zip(lhs, ops, rhs):
+                ex = f"{lh} {ops_} {rh}"
                 with pytest.raises(NotImplementedError, match=msg):
                     df.query(ex, engine=engine, parser=parser)
         else:

pandas/tests/io/test_feather.py

@@ -36,7 +36,9 @@ def check_external_error_on_write(self, df):
             with tm.ensure_clean() as path:
                 to_feather(df, path)
 
-    def check_round_trip(self, df, expected=None, write_kwargs={}, **read_kwargs):
+    def check_round_trip(self, df, expected=None, write_kwargs=None, **read_kwargs):
+        if write_kwargs is None:
+            write_kwargs = {}
         if expected is None:
             expected = df.copy()
 

pandas/tests/plotting/common.py

@@ -433,7 +433,7 @@ def _check_box_return_type(
                 raise AssertionError
 
 
-def _check_grid_settings(obj, kinds, kws={}):
+def _check_grid_settings(obj, kinds, kws=None):
     # Make sure plot defaults to rcParams['axes.grid'] setting, GH 9792
 
     import matplotlib as mpl
@@ -446,6 +446,8 @@ def is_grid_on():
 
         return not (xoff and yoff)
 
+    if kws is None:
+        kws = {}
     spndx = 1
     for kind in kinds:
         mpl.pyplot.subplot(1, 4 * len(kinds), spndx)

pandas/tests/reshape/test_pivot.py

@@ -890,10 +890,14 @@ def _check_output(
         result,
         values_col,
         data,
-        index=["A", "B"],
-        columns=["C"],
+        index=None,
+        columns=None,
         margins_col="All",
     ):
+        if index is None:
+            index = ["A", "B"]
+        if columns is None:
+            columns = ["C"]
         col_margins = result.loc[result.index[:-1], margins_col]
         expected_col_margins = data.groupby(index)[values_col].mean()
         tm.assert_series_equal(col_margins, expected_col_margins, check_names=False)