[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -24,7 +24,7 @@ repos:
     hooks:
       - id: black
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.0.285
+    rev: v0.0.287
     hooks:
     -   id: ruff
         args: [--exit-non-zero-on-fix]
@@ -34,7 +34,7 @@ repos:
         alias: ruff-selected-autofixes
         args: [--select, "ANN001,ANN204", --fix-only, --exit-non-zero-on-fix]
 -   repo: https://github.com/jendrikseipp/vulture
-    rev: 'v2.7'
+    rev: 'v2.9.1'
     hooks:
       - id: vulture
         entry: python scripts/run_vulture.py
@@ -84,7 +84,7 @@ repos:
             '--filter=-readability/casting,-runtime/int,-build/include_subdir,-readability/fn_size'
         ]
 -   repo: https://github.com/pylint-dev/pylint
-    rev: v3.0.0a6
+    rev: v3.0.0a7
     hooks:
     -   id: pylint
         stages: [manual]
@@ -124,7 +124,7 @@ repos:
         types: [text]  # overwrite types: [rst]
         types_or: [python, rst]
 -   repo: https://github.com/sphinx-contrib/sphinx-lint
-    rev: v0.6.7
+    rev: v0.6.8
     hooks:
     - id: sphinx-lint
 -   repo: local

asv_bench/benchmarks/array.py

@@ -90,7 +90,7 @@ def time_setitem(self, multiple_chunks):
             self.array[i] = "foo"
 
     def time_setitem_list(self, multiple_chunks):
-        indexer = list(range(0, 50)) + list(range(-1000, 0, 50))
+        indexer = list(range(50)) + list(range(-1000, 0, 50))
         self.array[indexer] = ["foo"] * len(indexer)
 
     def time_setitem_slice(self, multiple_chunks):

asv_bench/benchmarks/join_merge.py

@@ -360,14 +360,14 @@ class MergeCategoricals:
     def setup(self):
         self.left_object = DataFrame(
             {
-                "X": np.random.choice(range(0, 10), size=(10000,)),
+                "X": np.random.choice(range(10), size=(10000,)),
                 "Y": np.random.choice(["one", "two", "three"], size=(10000,)),
             }
         )
 
         self.right_object = DataFrame(
             {
-                "X": np.random.choice(range(0, 10), size=(10000,)),
+                "X": np.random.choice(range(10), size=(10000,)),
                 "Z": np.random.choice(["jjj", "kkk", "sss"], size=(10000,)),
             }
         )

pandas/core/dtypes/dtypes.py

@@ -70,7 +70,7 @@
     from collections.abc import MutableMapping
     from datetime import tzinfo
 
-    import pyarrow as pa  # noqa: F811, TCH004
+    import pyarrow as pa  # noqa: TCH004
 
     from pandas._typing import (
         Dtype,

pandas/core/indexes/api.py

@@ -377,5 +377,5 @@ def all_indexes_same(indexes) -> bool:
 
 
 def default_index(n: int) -> RangeIndex:
-    rng = range(0, n)
+    rng = range(n)
     return RangeIndex._simple_new(rng, name=None)

pandas/tests/frame/methods/test_copy.py

@@ -56,7 +56,7 @@ def test_copy_consolidates(self):
             }
         )
 
-        for i in range(0, 10):
+        for i in range(10):
             df.loc[:, f"n_{i}"] = np.random.default_rng(2).integers(0, 100, size=55)
 
         assert len(df._mgr.blocks) == 11

pandas/tests/frame/methods/test_reset_index.py

@@ -788,15 +788,15 @@ def test_errorreset_index_rename(float_frame):
 
 
 def test_reset_index_false_index_name():
-    result_series = Series(data=range(5, 10), index=range(0, 5))
+    result_series = Series(data=range(5, 10), index=range(5))
     result_series.index.name = False
     result_series.reset_index()
-    expected_series = Series(range(5, 10), RangeIndex(range(0, 5), name=False))
+    expected_series = Series(range(5, 10), RangeIndex(range(5), name=False))
     tm.assert_series_equal(result_series, expected_series)
 
     # GH 38147
-    result_frame = DataFrame(data=range(5, 10), index=range(0, 5))
+    result_frame = DataFrame(data=range(5, 10), index=range(5))
     result_frame.index.name = False
     result_frame.reset_index()
-    expected_frame = DataFrame(range(5, 10), RangeIndex(range(0, 5), name=False))
+    expected_frame = DataFrame(range(5, 10), RangeIndex(range(5), name=False))
     tm.assert_frame_equal(result_frame, expected_frame)

pandas/tests/frame/methods/test_sort_index.py

@@ -911,7 +911,7 @@ def test_sort_index_multiindex_sparse_column(self):
         expected = DataFrame(
             {
                 i: pd.array([0.0, 0.0, 0.0, 0.0], dtype=pd.SparseDtype("float64", 0.0))
-                for i in range(0, 4)
+                for i in range(4)
             },
             index=MultiIndex.from_product([[1, 2], [1, 2]]),
         )

pandas/tests/frame/test_constructors.py

@@ -692,12 +692,12 @@ def test_constructor_error_msgs(self):
         arr = np.array([[4, 5, 6]])
         msg = r"Shape of passed values is \(1, 3\), indices imply \(1, 4\)"
         with pytest.raises(ValueError, match=msg):
-            DataFrame(index=[0], columns=range(0, 4), data=arr)
+            DataFrame(index=[0], columns=range(4), data=arr)
 
         arr = np.array([4, 5, 6])
         msg = r"Shape of passed values is \(3, 1\), indices imply \(1, 4\)"
         with pytest.raises(ValueError, match=msg):
-            DataFrame(index=[0], columns=range(0, 4), data=arr)
+            DataFrame(index=[0], columns=range(4), data=arr)
 
         # higher dim raise exception
         with pytest.raises(ValueError, match="Must pass 2-d input"):
@@ -2391,7 +2391,7 @@ def test_construct_with_two_categoricalindex_series(self):
 
     def test_constructor_series_nonexact_categoricalindex(self):
         # GH 42424
-        ser = Series(range(0, 100))
+        ser = Series(range(100))
         ser1 = cut(ser, 10).value_counts().head(5)
         ser2 = cut(ser, 10).value_counts().tail(5)
         result = DataFrame({"1": ser1, "2": ser2})

pandas/tests/groupby/test_groupby.py

@@ -1928,7 +1928,7 @@ def test_pivot_table_values_key_error():
     df = DataFrame(
         {
             "eventDate": date_range(datetime.today(), periods=20, freq="M").tolist(),
-            "thename": range(0, 20),
+            "thename": range(20),
         }
     )
 

pandas/tests/groupby/test_timegrouper.py

@@ -842,7 +842,7 @@ def test_grouper_period_index(self):
         result = period_series.groupby(period_series.index.month).sum()
 
         expected = Series(
-            range(0, periods), index=Index(range(1, periods + 1), name=index.name)
+            range(periods), index=Index(range(1, periods + 1), name=index.name)
         )
         tm.assert_series_equal(result, expected)
 

pandas/tests/indexes/multi/test_partial_indexing.py

@@ -31,7 +31,7 @@ def df():
     dr = date_range("2016-01-01", "2016-01-03", freq="12H")
     abc = ["a", "b", "c"]
     mi = MultiIndex.from_product([dr, abc])
-    frame = DataFrame({"c1": range(0, 15)}, index=mi)
+    frame = DataFrame({"c1": range(15)}, index=mi)
     return frame
 
 

pandas/tests/indexing/multiindex/test_getitem.py

@@ -148,7 +148,7 @@ def test_frame_getitem_simple_key_error(
 def test_tuple_string_column_names():
     # GH#50372
     mi = MultiIndex.from_tuples([("a", "aa"), ("a", "ab"), ("b", "ba"), ("b", "bb")])
-    df = DataFrame([range(0, 4), range(1, 5), range(2, 6)], columns=mi)
+    df = DataFrame([range(4), range(1, 5), range(2, 6)], columns=mi)
     df["single_index"] = 0
 
     df_flat = df.copy()

pandas/tests/io/json/test_pandas.py

@@ -2044,7 +2044,7 @@ def test_read_json_dtype_backend(self, string_storage, dtype_backend, orient):
             )
 
         if orient == "values":
-            expected.columns = list(range(0, 8))
+            expected.columns = list(range(8))
 
         tm.assert_frame_equal(result, expected)
 

pandas/tests/io/json/test_ujson.py

@@ -1033,7 +1033,7 @@ def test_decode_floating_point(self, sign, float_number):
     def test_encode_big_set(self):
         s = set()
 
-        for x in range(0, 100000):
+        for x in range(100000):
             s.add(x)
 
         # Make sure no Exception is raised.

pandas/tests/io/test_parquet.py

@@ -1012,7 +1012,7 @@ def test_timezone_aware_index(self, request, pa, timezone_aware_date_list):
     def test_filter_row_groups(self, pa):
         # https://github.com/pandas-dev/pandas/issues/26551
         pytest.importorskip("pyarrow")
-        df = pd.DataFrame({"a": list(range(0, 3))})
+        df = pd.DataFrame({"a": list(range(3))})
         with tm.ensure_clean() as path:
             df.to_parquet(path, engine=pa)
             result = read_parquet(
@@ -1219,7 +1219,7 @@ def test_categorical(self, fp):
         check_round_trip(df, fp)
 
     def test_filter_row_groups(self, fp):
-        d = {"a": list(range(0, 3))}
+        d = {"a": list(range(3))}
         df = pd.DataFrame(d)
         with tm.ensure_clean() as path:
             df.to_parquet(path, engine=fp, compression=None, row_group_offsets=1)

pandas/tests/io/test_stata.py

@@ -798,7 +798,7 @@ def test_missing_value_generator(self):
         expected_values.insert(0, ".")
         for t in types:
             offset = valid_range[t][1]
-            for i in range(0, 27):
+            for i in range(27):
                 val = StataMissingValue(offset + 1 + i)
                 assert val.string == expected_values[i]
 

pandas/tests/reshape/test_cut.py

@@ -700,7 +700,7 @@ def test_cut_with_duplicated_index_lowest_included():
 def test_cut_with_nonexact_categorical_indices():
     # GH 42424
 
-    ser = Series(range(0, 100))
+    ser = Series(range(100))
     ser1 = cut(ser, 10).value_counts().head(5)
     ser2 = cut(ser, 10).value_counts().tail(5)
     result = DataFrame({"1": ser1, "2": ser2})

pandas/tests/reshape/test_pivot.py

@@ -33,7 +33,7 @@ def dropna(request):
     return request.param
 
 
-@pytest.fixture(params=[([0] * 4, [1] * 4), (range(0, 3), range(1, 4))])
+@pytest.fixture(params=[([0] * 4, [1] * 4), (range(3), range(1, 4))])
 def interval_values(request, closed):
     left, right = request.param
     return Categorical(pd.IntervalIndex.from_arrays(left, right, closed))
@@ -215,7 +215,7 @@ def test_pivot_table_dropna_categoricals(self, dropna):
             {
                 "A": ["a", "a", "a", "b", "b", "b", "c", "c", "c"],
                 "B": [1, 2, 3, 1, 2, 3, 1, 2, 3],
-                "C": range(0, 9),
+                "C": range(9),
             }
         )
 

pandas/tests/series/methods/test_reindex.py

@@ -159,9 +159,9 @@ def test_reindex_inference():
 
 def test_reindex_downcasting():
     # GH4618 shifted series downcasting
-    s = Series(False, index=range(0, 5))
+    s = Series(False, index=range(5))
     result = s.shift(1).bfill()
-    expected = Series(False, index=range(0, 5))
+    expected = Series(False, index=range(5))
     tm.assert_series_equal(result, expected)
 
 

pandas/tests/window/test_rolling_functions.py

@@ -388,7 +388,7 @@ def test_rolling_max_resample(step):
     # So that we can have 3 datapoints on last day (4, 10, and 20)
     indices.append(datetime(1975, 1, 5, 1))
     indices.append(datetime(1975, 1, 5, 2))
-    series = Series(list(range(0, 5)) + [10, 20], index=indices)
+    series = Series(list(range(5)) + [10, 20], index=indices)
     # Use floats instead of ints as values
     series = series.map(lambda x: float(x))
     # Sort chronologically
@@ -425,7 +425,7 @@ def test_rolling_min_resample(step):
     # So that we can have 3 datapoints on last day (4, 10, and 20)
     indices.append(datetime(1975, 1, 5, 1))
     indices.append(datetime(1975, 1, 5, 2))
-    series = Series(list(range(0, 5)) + [10, 20], index=indices)
+    series = Series(list(range(5)) + [10, 20], index=indices)
     # Use floats instead of ints as values
     series = series.map(lambda x: float(x))
     # Sort chronologically
@@ -445,7 +445,7 @@ def test_rolling_median_resample():
     # So that we can have 3 datapoints on last day (4, 10, and 20)
     indices.append(datetime(1975, 1, 5, 1))
     indices.append(datetime(1975, 1, 5, 2))
-    series = Series(list(range(0, 5)) + [10, 20], index=indices)
+    series = Series(list(range(5)) + [10, 20], index=indices)
     # Use floats instead of ints as values
     series = series.map(lambda x: float(x))
     # Sort chronologically