diff --git a/pandas/conftest.py b/pandas/conftest.py
index fb281cb9def81..b24606f8007d2 100644
--- a/pandas/conftest.py
+++ b/pandas/conftest.py
@@ -30,7 +30,6 @@
 from decimal import Decimal
 import operator
 import os
-from pathlib import Path
 from typing import (
     TYPE_CHECKING,
     Callable,
@@ -775,23 +774,6 @@ def series_with_simple_index(index) -> Series:
     return _create_series(index)
 
 
-@pytest.fixture
-def series_with_multilevel_index() -> Series:
-    """
-    Fixture with a Series with a 2-level MultiIndex.
-    """
-    arrays = [
-        ["bar", "bar", "baz", "baz", "qux", "qux", "foo", "foo"],
-        ["one", "two", "one", "two", "one", "two", "one", "two"],
-    ]
-    tuples = zip(*arrays)
-    index = MultiIndex.from_tuples(tuples)
-    data = np.random.default_rng(2).standard_normal(8)
-    ser = Series(data, index=index)
-    ser.iloc[3] = np.nan
-    return ser
-
-
 _narrow_series = {
     f"{dtype.__name__}-series": tm.make_rand_series(name="a", dtype=dtype)
     for dtype in tm.NARROW_NP_DTYPES
@@ -865,35 +847,6 @@ def int_frame() -> DataFrame:
     return DataFrame(tm.getSeriesData()).astype("int64")
 
 
-@pytest.fixture
-def datetime_frame() -> DataFrame:
-    """
-    Fixture for DataFrame of floats with DatetimeIndex
-
-    Columns are ['A', 'B', 'C', 'D']
-
-                       A         B         C         D
-    2000-01-03 -1.122153  0.468535  0.122226  1.693711
-    2000-01-04  0.189378  0.486100  0.007864 -1.216052
-    2000-01-05  0.041401 -0.835752 -0.035279 -0.414357
-    2000-01-06  0.430050  0.894352  0.090719  0.036939
-    2000-01-07 -0.620982 -0.668211 -0.706153  1.466335
-    2000-01-10 -0.752633  0.328434 -0.815325  0.699674
-    2000-01-11 -2.236969  0.615737 -0.829076 -1.196106
-    ...              ...       ...       ...       ...
-    2000-02-03  1.642618 -0.579288  0.046005  1.385249
-    2000-02-04 -0.544873 -1.160962 -0.284071 -1.418351
-    2000-02-07 -2.656149 -0.601387  1.410148  0.444150
-    2000-02-08 -1.201881 -1.289040  0.772992 -1.445300
-    2000-02-09  1.377373  0.398619  1.008453 -0.928207
-    2000-02-10  0.473194 -0.636677  0.984058  0.511519
-    2000-02-11 -0.965556  0.408313 -1.312844 -0.381948
-
-    [30 rows x 4 columns]
-    """
-    return DataFrame(tm.getTimeSeriesData())
-
-
 @pytest.fixture
 def float_frame() -> DataFrame:
     """
@@ -923,24 +876,6 @@ def float_frame() -> DataFrame:
     return DataFrame(tm.getSeriesData())
 
 
-@pytest.fixture
-def mixed_type_frame() -> DataFrame:
-    """
-    Fixture for DataFrame of float/int/string columns with RangeIndex
-    Columns are ['a', 'b', 'c', 'float32', 'int32'].
-    """
-    return DataFrame(
-        {
-            "a": 1.0,
-            "b": 2,
-            "c": "foo",
-            "float32": np.array([1.0] * 10, dtype="float32"),
-            "int32": np.array([1] * 10, dtype="int32"),
-        },
-        index=np.arange(10),
-    )
-
-
 @pytest.fixture
 def rand_series_with_duplicate_datetimeindex() -> Series:
     """
@@ -1174,16 +1109,6 @@ def strict_data_files(pytestconfig):
     return pytestconfig.getoption("--no-strict-data-files")
 
 
-@pytest.fixture
-def tests_path() -> Path:
-    return Path(__file__).parent / "tests"
-
-
-@pytest.fixture
-def tests_io_data_path(tests_path) -> Path:
-    return tests_path / "io" / "data"
-
-
 @pytest.fixture
 def datapath(strict_data_files: str) -> Callable[..., str]:
     """
@@ -1218,14 +1143,6 @@ def deco(*args):
     return deco
 
 
-@pytest.fixture
-def iris(datapath) -> DataFrame:
-    """
-    The iris dataset as a DataFrame.
-    """
-    return pd.read_csv(datapath("io", "data", "csv", "iris.csv"))
-
-
 # ----------------------------------------------------------------
 # Time zones
 # ----------------------------------------------------------------
@@ -1905,28 +1822,6 @@ def sort_by_key(request):
     return request.param
 
 
-@pytest.fixture()
-def fsspectest():
-    pytest.importorskip("fsspec")
-    from fsspec import register_implementation
-    from fsspec.implementations.memory import MemoryFileSystem
-    from fsspec.registry import _registry as registry
-
-    class TestMemoryFS(MemoryFileSystem):
-        protocol = "testmem"
-        test = [None]
-
-        def __init__(self, **kwargs) -> None:
-            self.test[0] = kwargs.pop("test", None)
-            super().__init__(**kwargs)
-
-    register_implementation("testmem", TestMemoryFS, clobber=True)
-    yield TestMemoryFS()
-    registry.pop("testmem", None)
-    TestMemoryFS.test[0] = None
-    TestMemoryFS.store.clear()
-
-
 @pytest.fixture(
     params=[
         ("foo", None, None),
diff --git a/pandas/tests/apply/conftest.py b/pandas/tests/apply/conftest.py
deleted file mode 100644
index acccdd845b53c..0000000000000
--- a/pandas/tests/apply/conftest.py
+++ /dev/null
@@ -1,30 +0,0 @@
-import numpy as np
-import pytest
-
-from pandas import DataFrame
-
-
-@pytest.fixture
-def int_frame_const_col():
-    """
-    Fixture for DataFrame of ints which are constant per column
-
-    Columns are ['A', 'B', 'C'], with values (per column): [1, 2, 3]
-    """
-    df = DataFrame(
-        np.tile(np.arange(3, dtype="int64"), 6).reshape(6, -1) + 1,
-        columns=["A", "B", "C"],
-    )
-    return df
-
-
-@pytest.fixture(params=["python", pytest.param("numba", marks=pytest.mark.single_cpu)])
-def engine(request):
-    if request.param == "numba":
-        pytest.importorskip("numba")
-    return request.param
-
-
-@pytest.fixture(params=[0, 1])
-def apply_axis(request):
-    return request.param
diff --git a/pandas/tests/apply/test_frame_apply.py b/pandas/tests/apply/test_frame_apply.py
index 24f8a99235b70..2d7549e09a986 100644
--- a/pandas/tests/apply/test_frame_apply.py
+++ b/pandas/tests/apply/test_frame_apply.py
@@ -18,6 +18,27 @@
 from pandas.tests.frame.common import zip_frames
 
 
+@pytest.fixture
+def int_frame_const_col():
+    """
+    Fixture for DataFrame of ints which are constant per column
+
+    Columns are ['A', 'B', 'C'], with values (per column): [1, 2, 3]
+    """
+    df = DataFrame(
+        np.tile(np.arange(3, dtype="int64"), 6).reshape(6, -1) + 1,
+        columns=["A", "B", "C"],
+    )
+    return df
+
+
+@pytest.fixture(params=["python", pytest.param("numba", marks=pytest.mark.single_cpu)])
+def engine(request):
+    if request.param == "numba":
+        pytest.importorskip("numba")
+    return request.param
+
+
 def test_apply(float_frame, engine, request):
     if engine == "numba":
         mark = pytest.mark.xfail(reason="numba engine not supporting numpy ufunc yet")
@@ -269,7 +290,7 @@ def test_apply_raw_float_frame_no_reduction(float_frame, engine):
 
 
 @pytest.mark.parametrize("axis", [0, 1])
-def test_apply_raw_mixed_type_frame(mixed_type_frame, axis, engine):
+def test_apply_raw_mixed_type_frame(axis, engine):
     if engine == "numba":
         pytest.skip("isinstance check doesn't work with numba")
 
@@ -278,7 +299,17 @@ def _assert_raw(x):
         assert x.ndim == 1
 
     # Mixed dtype (GH-32423)
-    mixed_type_frame.apply(_assert_raw, axis=axis, engine=engine, raw=True)
+    df = DataFrame(
+        {
+            "a": 1.0,
+            "b": 2,
+            "c": "foo",
+            "float32": np.array([1.0] * 10, dtype="float32"),
+            "int32": np.array([1] * 10, dtype="int32"),
+        },
+        index=np.arange(10),
+    )
+    df.apply(_assert_raw, axis=axis, engine=engine, raw=True)
 
 
 def test_apply_axis1(float_frame):
diff --git a/pandas/tests/apply/test_invalid_arg.py b/pandas/tests/apply/test_invalid_arg.py
index 44829c598253d..9f5157181843e 100644
--- a/pandas/tests/apply/test_invalid_arg.py
+++ b/pandas/tests/apply/test_invalid_arg.py
@@ -24,9 +24,12 @@
 
 
 @pytest.mark.parametrize("result_type", ["foo", 1])
-def test_result_type_error(result_type, int_frame_const_col):
+def test_result_type_error(result_type):
     # allowed result_type
-    df = int_frame_const_col
+    df = DataFrame(
+        np.tile(np.arange(3, dtype="int64"), 6).reshape(6, -1) + 1,
+        columns=["A", "B", "C"],
+    )
 
     msg = (
         "invalid value for result_type, must be one of "
@@ -282,8 +285,11 @@ def test_transform_none_to_type():
         lambda x: Series([1, 2]),
     ],
 )
-def test_apply_broadcast_error(int_frame_const_col, func):
-    df = int_frame_const_col
+def test_apply_broadcast_error(func):
+    df = DataFrame(
+        np.tile(np.arange(3, dtype="int64"), 6).reshape(6, -1) + 1,
+        columns=["A", "B", "C"],
+    )
 
     # > 1 ndim
     msg = "too many dims to broadcast|cannot broadcast result"
diff --git a/pandas/tests/apply/test_numba.py b/pandas/tests/apply/test_numba.py
index 3924d8e74e156..ee239568d057d 100644
--- a/pandas/tests/apply/test_numba.py
+++ b/pandas/tests/apply/test_numba.py
@@ -12,6 +12,11 @@
 pytestmark = [td.skip_if_no("numba"), pytest.mark.single_cpu]
 
 
+@pytest.fixture(params=[0, 1])
+def apply_axis(request):
+    return request.param
+
+
 def test_numba_vs_python_noop(float_frame, apply_axis):
     func = lambda x: x
     result = float_frame.apply(func, engine="numba", axis=apply_axis)
diff --git a/pandas/tests/arithmetic/conftest.py b/pandas/tests/arithmetic/conftest.py
index f77b81574e1c1..c7703b34a5e38 100644
--- a/pandas/tests/arithmetic/conftest.py
+++ b/pandas/tests/arithmetic/conftest.py
@@ -2,11 +2,7 @@
 import pytest
 
 import pandas as pd
-from pandas import (
-    Index,
-    RangeIndex,
-)
-import pandas._testing as tm
+from pandas import Index
 
 
 @pytest.fixture(params=[1, np.array(1, dtype=np.int64)])
@@ -63,27 +59,6 @@ def zero(request):
     return request.param
 
 
-# ------------------------------------------------------------------
-# Vector Fixtures
-
-
-@pytest.fixture(
-    params=[
-        # TODO: add more  dtypes here
-        Index(np.arange(5, dtype="float64")),
-        Index(np.arange(5, dtype="int64")),
-        Index(np.arange(5, dtype="uint64")),
-        RangeIndex(5),
-    ],
-    ids=lambda x: type(x).__name__,
-)
-def numeric_idx(request):
-    """
-    Several types of numeric-dtypes Index objects
-    """
-    return request.param
-
-
 # ------------------------------------------------------------------
 # Scalar Fixtures
 
@@ -148,22 +123,6 @@ def two_hours(request):
 ]
 
 
-@pytest.fixture(
-    params=[
-        pd.Timedelta(minutes=30).to_pytimedelta(),
-        np.timedelta64(30, "s"),
-        pd.Timedelta(seconds=30),
-    ]
-    + _common_mismatch
-)
-def not_hourly(request):
-    """
-    Several timedelta-like and DateOffset instances that are _not_
-    compatible with Hourly frequencies.
-    """
-    return request.param
-
-
 @pytest.fixture(
     params=[
         np.timedelta64(4, "h"),
@@ -178,33 +137,3 @@ def not_daily(request):
     compatible with Daily frequencies.
     """
     return request.param
-
-
-@pytest.fixture(
-    params=[
-        np.timedelta64(365, "D"),
-        pd.Timedelta(days=365).to_pytimedelta(),
-        pd.Timedelta(days=365),
-    ]
-    + _common_mismatch
-)
-def mismatched_freq(request):
-    """
-    Several timedelta-like and DateOffset instances that are _not_
-    compatible with Monthly or Annual frequencies.
-    """
-    return request.param
-
-
-# ------------------------------------------------------------------
-
-
-@pytest.fixture(
-    params=[Index, pd.Series, tm.to_array, np.array, list], ids=lambda x: x.__name__
-)
-def box_1d_array(request):
-    """
-    Fixture to test behavior for Index, Series, tm.to_array, numpy Array and list
-    classes
-    """
-    return request.param
diff --git a/pandas/tests/arithmetic/test_numeric.py b/pandas/tests/arithmetic/test_numeric.py
index c2fba3c775de9..f89711c0edee7 100644
--- a/pandas/tests/arithmetic/test_numeric.py
+++ b/pandas/tests/arithmetic/test_numeric.py
@@ -44,6 +44,34 @@ def box_pandas_1d_array(request):
     return request.param
 
 
+@pytest.fixture(
+    params=[
+        # TODO: add more  dtypes here
+        Index(np.arange(5, dtype="float64")),
+        Index(np.arange(5, dtype="int64")),
+        Index(np.arange(5, dtype="uint64")),
+        RangeIndex(5),
+    ],
+    ids=lambda x: type(x).__name__,
+)
+def numeric_idx(request):
+    """
+    Several types of numeric-dtypes Index objects
+    """
+    return request.param
+
+
+@pytest.fixture(
+    params=[Index, Series, tm.to_array, np.array, list], ids=lambda x: x.__name__
+)
+def box_1d_array(request):
+    """
+    Fixture to test behavior for Index, Series, tm.to_array, numpy Array and list
+    classes
+    """
+    return request.param
+
+
 def adjust_negative_zero(zero, expected):
     """
     Helper to adjust the expected result if we are dividing by -0.0
diff --git a/pandas/tests/arithmetic/test_period.py b/pandas/tests/arithmetic/test_period.py
index 68d245bcffce2..88c633f5e747f 100644
--- a/pandas/tests/arithmetic/test_period.py
+++ b/pandas/tests/arithmetic/test_period.py
@@ -31,6 +31,45 @@
     get_upcast_box,
 )
 
+_common_mismatch = [
+    pd.offsets.YearBegin(2),
+    pd.offsets.MonthBegin(1),
+    pd.offsets.Minute(),
+]
+
+
+@pytest.fixture(
+    params=[
+        Timedelta(minutes=30).to_pytimedelta(),
+        np.timedelta64(30, "s"),
+        Timedelta(seconds=30),
+    ]
+    + _common_mismatch
+)
+def not_hourly(request):
+    """
+    Several timedelta-like and DateOffset instances that are _not_
+    compatible with Hourly frequencies.
+    """
+    return request.param
+
+
+@pytest.fixture(
+    params=[
+        np.timedelta64(365, "D"),
+        Timedelta(days=365).to_pytimedelta(),
+        Timedelta(days=365),
+    ]
+    + _common_mismatch
+)
+def mismatched_freq(request):
+    """
+    Several timedelta-like and DateOffset instances that are _not_
+    compatible with Monthly or Annual frequencies.
+    """
+    return request.param
+
+
 # ------------------------------------------------------------------
 # Comparisons
 
diff --git a/pandas/tests/arrays/categorical/conftest.py b/pandas/tests/arrays/categorical/conftest.py
index d5b49e3e5e8c8..37249210f28f4 100644
--- a/pandas/tests/arrays/categorical/conftest.py
+++ b/pandas/tests/arrays/categorical/conftest.py
@@ -3,12 +3,6 @@
 from pandas import Categorical
 
 
-@pytest.fixture(params=[True, False])
-def allow_fill(request):
-    """Boolean 'allow_fill' parameter for Categorical.take"""
-    return request.param
-
-
 @pytest.fixture
 def factor():
     """Fixture returning  a Categorical object"""
diff --git a/pandas/tests/arrays/categorical/test_take.py b/pandas/tests/arrays/categorical/test_take.py
index fb79fe4923522..373f1b30a13c2 100644
--- a/pandas/tests/arrays/categorical/test_take.py
+++ b/pandas/tests/arrays/categorical/test_take.py
@@ -5,6 +5,12 @@
 import pandas._testing as tm
 
 
+@pytest.fixture(params=[True, False])
+def allow_fill(request):
+    """Boolean 'allow_fill' parameter for Categorical.take"""
+    return request.param
+
+
 class TestTake:
     # https://github.com/pandas-dev/pandas/issues/20664
 
diff --git a/pandas/tests/frame/conftest.py b/pandas/tests/frame/conftest.py
index fb2df0b82e5f4..f7ed5180b46d9 100644
--- a/pandas/tests/frame/conftest.py
+++ b/pandas/tests/frame/conftest.py
@@ -10,75 +10,32 @@
 
 
 @pytest.fixture
-def float_frame_with_na():
+def datetime_frame() -> DataFrame:
     """
-    Fixture for DataFrame of floats with index of unique strings
+    Fixture for DataFrame of floats with DatetimeIndex
 
-    Columns are ['A', 'B', 'C', 'D']; some entries are missing
+    Columns are ['A', 'B', 'C', 'D']
 
                        A         B         C         D
-    ABwBzA0ljw -1.128865 -0.897161  0.046603  0.274997
-    DJiRzmbyQF  0.728869  0.233502  0.722431 -0.890872
-    neMgPD5UBF  0.486072 -1.027393 -0.031553  1.449522
-    0yWA4n8VeX -1.937191 -1.142531  0.805215 -0.462018
-    3slYUbbqU1  0.153260  1.164691  1.489795 -0.545826
-    soujjZ0A08       NaN       NaN       NaN       NaN
-    7W6NLGsjB9       NaN       NaN       NaN       NaN
+    2000-01-03 -1.122153  0.468535  0.122226  1.693711
+    2000-01-04  0.189378  0.486100  0.007864 -1.216052
+    2000-01-05  0.041401 -0.835752 -0.035279 -0.414357
+    2000-01-06  0.430050  0.894352  0.090719  0.036939
+    2000-01-07 -0.620982 -0.668211 -0.706153  1.466335
+    2000-01-10 -0.752633  0.328434 -0.815325  0.699674
+    2000-01-11 -2.236969  0.615737 -0.829076 -1.196106
     ...              ...       ...       ...       ...
-    uhfeaNkCR1 -0.231210 -0.340472  0.244717 -0.901590
-    n6p7GYuBIV -0.419052  1.922721 -0.125361 -0.727717
-    ZhzAeY6p1y  1.234374 -1.425359 -0.827038 -0.633189
-    uWdPsORyUh  0.046738 -0.980445 -1.102965  0.605503
-    3DJA6aN590 -0.091018 -1.684734 -1.100900  0.215947
-    2GBPAzdbMk -2.883405 -1.021071  1.209877  1.633083
-    sHadBoyVHw -2.223032 -0.326384  0.258931  0.245517
+    2000-02-03  1.642618 -0.579288  0.046005  1.385249
+    2000-02-04 -0.544873 -1.160962 -0.284071 -1.418351
+    2000-02-07 -2.656149 -0.601387  1.410148  0.444150
+    2000-02-08 -1.201881 -1.289040  0.772992 -1.445300
+    2000-02-09  1.377373  0.398619  1.008453 -0.928207
+    2000-02-10  0.473194 -0.636677  0.984058  0.511519
+    2000-02-11 -0.965556  0.408313 -1.312844 -0.381948
 
     [30 rows x 4 columns]
     """
-    df = DataFrame(tm.getSeriesData())
-    # set some NAs
-    df.iloc[5:10] = np.nan
-    df.iloc[15:20, -2:] = np.nan
-    return df
-
-
-@pytest.fixture
-def bool_frame_with_na():
-    """
-    Fixture for DataFrame of booleans with index of unique strings
-
-    Columns are ['A', 'B', 'C', 'D']; some entries are missing
-
-                    A      B      C      D
-    zBZxY2IDGd  False  False  False  False
-    IhBWBMWllt  False   True   True   True
-    ctjdvZSR6R   True  False   True   True
-    AVTujptmxb  False   True  False   True
-    G9lrImrSWq  False  False  False   True
-    sFFwdIUfz2    NaN    NaN    NaN    NaN
-    s15ptEJnRb    NaN    NaN    NaN    NaN
-    ...           ...    ...    ...    ...
-    UW41KkDyZ4   True   True  False  False
-    l9l6XkOdqV   True  False  False  False
-    X2MeZfzDYA  False   True  False  False
-    xWkIKU7vfX  False   True  False   True
-    QOhL6VmpGU  False  False  False   True
-    22PwkRJdat  False   True  False  False
-    kfboQ3VeIK   True  False   True  False
-
-    [30 rows x 4 columns]
-    """
-    df = DataFrame(tm.getSeriesData()) > 0
-    df = df.astype(object)
-    # set some NAs
-    df.iloc[5:10] = np.nan
-    df.iloc[15:20, -2:] = np.nan
-
-    # For `any` tests we need to have at least one True before the first NaN
-    #  in each column
-    for i in range(4):
-        df.iloc[i, i] = True
-    return df
+    return DataFrame(tm.getTimeSeriesData())
 
 
 @pytest.fixture
@@ -202,60 +159,3 @@ def timezone_frame():
     df.iloc[1, 1] = NaT
     df.iloc[1, 2] = NaT
     return df
-
-
-@pytest.fixture
-def uint64_frame():
-    """
-    Fixture for DataFrame with uint64 values
-
-    Columns are ['A', 'B']
-    """
-    return DataFrame(
-        {"A": np.arange(3), "B": [2**63, 2**63 + 5, 2**63 + 10]}, dtype=np.uint64
-    )
-
-
-@pytest.fixture
-def simple_frame():
-    """
-    Fixture for simple 3x3 DataFrame
-
-    Columns are ['one', 'two', 'three'], index is ['a', 'b', 'c'].
-
-       one  two  three
-    a  1.0  2.0    3.0
-    b  4.0  5.0    6.0
-    c  7.0  8.0    9.0
-    """
-    arr = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]])
-
-    return DataFrame(arr, columns=["one", "two", "three"], index=["a", "b", "c"])
-
-
-@pytest.fixture
-def frame_of_index_cols():
-    """
-    Fixture for DataFrame of columns that can be used for indexing
-
-    Columns are ['A', 'B', 'C', 'D', 'E', ('tuple', 'as', 'label')];
-    'A' & 'B' contain duplicates (but are jointly unique), the rest are unique.
-
-         A      B  C         D         E  (tuple, as, label)
-    0  foo    one  a  0.608477 -0.012500           -1.664297
-    1  foo    two  b -0.633460  0.249614           -0.364411
-    2  foo  three  c  0.615256  2.154968           -0.834666
-    3  bar    one  d  0.234246  1.085675            0.718445
-    4  bar    two  e  0.533841 -0.005702           -3.533912
-    """
-    df = DataFrame(
-        {
-            "A": ["foo", "foo", "foo", "bar", "bar"],
-            "B": ["one", "two", "three", "one", "two"],
-            "C": ["a", "b", "c", "d", "e"],
-            "D": np.random.default_rng(2).standard_normal(5),
-            "E": np.random.default_rng(2).standard_normal(5),
-            ("tuple", "as", "label"): np.random.default_rng(2).standard_normal(5),
-        }
-    )
-    return df
diff --git a/pandas/tests/frame/indexing/test_indexing.py b/pandas/tests/frame/indexing/test_indexing.py
index 10068b504b1b7..3cad2e73d3d9d 100644
--- a/pandas/tests/frame/indexing/test_indexing.py
+++ b/pandas/tests/frame/indexing/test_indexing.py
@@ -1569,8 +1569,11 @@ def test_setitem_value_coercing_dtypes(self, indexer, idx):
 
 
 class TestDataFrameIndexingUInt64:
-    def test_setitem(self, uint64_frame):
-        df = uint64_frame
+    def test_setitem(self):
+        df = DataFrame(
+            {"A": np.arange(3), "B": [2**63, 2**63 + 5, 2**63 + 10]},
+            dtype=np.uint64,
+        )
         idx = df["A"].rename("foo")
 
         # setitem
diff --git a/pandas/tests/frame/methods/test_astype.py b/pandas/tests/frame/methods/test_astype.py
index eac10d307c61c..2578dfb622fbf 100644
--- a/pandas/tests/frame/methods/test_astype.py
+++ b/pandas/tests/frame/methods/test_astype.py
@@ -67,9 +67,19 @@ def test_astype_mixed_float(self, mixed_float_frame):
         casted = mixed_float_frame.reindex(columns=["A", "B"]).astype("float16")
         _check_cast(casted, "float16")
 
-    def test_astype_mixed_type(self, mixed_type_frame):
+    def test_astype_mixed_type(self):
         # mixed casting
-        mn = mixed_type_frame._get_numeric_data().copy()
+        df = DataFrame(
+            {
+                "a": 1.0,
+                "b": 2,
+                "c": "foo",
+                "float32": np.array([1.0] * 10, dtype="float32"),
+                "int32": np.array([1] * 10, dtype="int32"),
+            },
+            index=np.arange(10),
+        )
+        mn = df._get_numeric_data().copy()
         mn["little_float"] = np.array(12345.0, dtype="float16")
         mn["big_float"] = np.array(123456789101112.0, dtype="float64")
 
diff --git a/pandas/tests/frame/methods/test_clip.py b/pandas/tests/frame/methods/test_clip.py
index ed8ccaea92c58..f783a388d7517 100644
--- a/pandas/tests/frame/methods/test_clip.py
+++ b/pandas/tests/frame/methods/test_clip.py
@@ -94,9 +94,13 @@ def test_clip_against_series(self, inplace):
             (1, [[2.0, 3.0, 4.0], [4.0, 5.0, 6.0], [5.0, 6.0, 7.0]]),
         ],
     )
-    def test_clip_against_list_like(self, simple_frame, inplace, lower, axis, res):
+    def test_clip_against_list_like(self, inplace, lower, axis, res):
         # GH#15390
-        original = simple_frame.copy(deep=True)
+        arr = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]])
+
+        original = DataFrame(
+            arr, columns=["one", "two", "three"], index=["a", "b", "c"]
+        )
 
         result = original.clip(lower=lower, upper=[5, 6, 7], axis=axis, inplace=inplace)
 
diff --git a/pandas/tests/frame/methods/test_set_index.py b/pandas/tests/frame/methods/test_set_index.py
index 9b87ffb0241ef..98113b6c41821 100644
--- a/pandas/tests/frame/methods/test_set_index.py
+++ b/pandas/tests/frame/methods/test_set_index.py
@@ -24,6 +24,34 @@
 import pandas._testing as tm
 
 
+@pytest.fixture
+def frame_of_index_cols():
+    """
+    Fixture for DataFrame of columns that can be used for indexing
+
+    Columns are ['A', 'B', 'C', 'D', 'E', ('tuple', 'as', 'label')];
+    'A' & 'B' contain duplicates (but are jointly unique), the rest are unique.
+
+         A      B  C         D         E  (tuple, as, label)
+    0  foo    one  a  0.608477 -0.012500           -1.664297
+    1  foo    two  b -0.633460  0.249614           -0.364411
+    2  foo  three  c  0.615256  2.154968           -0.834666
+    3  bar    one  d  0.234246  1.085675            0.718445
+    4  bar    two  e  0.533841 -0.005702           -3.533912
+    """
+    df = DataFrame(
+        {
+            "A": ["foo", "foo", "foo", "bar", "bar"],
+            "B": ["one", "two", "three", "one", "two"],
+            "C": ["a", "b", "c", "d", "e"],
+            "D": np.random.default_rng(2).standard_normal(5),
+            "E": np.random.default_rng(2).standard_normal(5),
+            ("tuple", "as", "label"): np.random.default_rng(2).standard_normal(5),
+        }
+    )
+    return df
+
+
 class TestSetIndex:
     def test_set_index_multiindex(self):
         # segfault in GH#3308
diff --git a/pandas/tests/frame/methods/test_transpose.py b/pandas/tests/frame/methods/test_transpose.py
index 50fc6fe6984e7..f96f4e0558fa6 100644
--- a/pandas/tests/frame/methods/test_transpose.py
+++ b/pandas/tests/frame/methods/test_transpose.py
@@ -87,9 +87,13 @@ def test_transpose_object_to_tzaware_mixed_tz(self):
         res2 = df2.T
         assert (res2.dtypes == object).all()
 
-    def test_transpose_uint64(self, uint64_frame):
-        result = uint64_frame.T
-        expected = DataFrame(uint64_frame.values.T)
+    def test_transpose_uint64(self):
+        df = DataFrame(
+            {"A": np.arange(3), "B": [2**63, 2**63 + 5, 2**63 + 10]},
+            dtype=np.uint64,
+        )
+        result = df.T
+        expected = DataFrame(df.values.T)
         expected.index = ["A", "B"]
         tm.assert_frame_equal(result, expected)
 
diff --git a/pandas/tests/frame/test_arithmetic.py b/pandas/tests/frame/test_arithmetic.py
index 9e3ee7c69b637..8083795a69413 100644
--- a/pandas/tests/frame/test_arithmetic.py
+++ b/pandas/tests/frame/test_arithmetic.py
@@ -28,6 +28,23 @@
 )
 
 
+@pytest.fixture
+def simple_frame():
+    """
+    Fixture for simple 3x3 DataFrame
+
+    Columns are ['one', 'two', 'three'], index is ['a', 'b', 'c'].
+
+       one  two  three
+    a  1.0  2.0    3.0
+    b  4.0  5.0    6.0
+    c  7.0  8.0    9.0
+    """
+    arr = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]])
+
+    return DataFrame(arr, columns=["one", "two", "three"], index=["a", "b", "c"])
+
+
 @pytest.fixture(autouse=True, params=[0, 100], ids=["numexpr", "python"])
 def switch_numexpr_min_elements(request, monkeypatch):
     with monkeypatch.context() as m:
diff --git a/pandas/tests/frame/test_reductions.py b/pandas/tests/frame/test_reductions.py
index fc7c1b0f01fed..20ad93e6dce4d 100644
--- a/pandas/tests/frame/test_reductions.py
+++ b/pandas/tests/frame/test_reductions.py
@@ -147,6 +147,78 @@ def wrapper(x):
             tm.assert_series_equal(r1, expected)
 
 
+@pytest.fixture
+def bool_frame_with_na():
+    """
+    Fixture for DataFrame of booleans with index of unique strings
+
+    Columns are ['A', 'B', 'C', 'D']; some entries are missing
+
+                    A      B      C      D
+    zBZxY2IDGd  False  False  False  False
+    IhBWBMWllt  False   True   True   True
+    ctjdvZSR6R   True  False   True   True
+    AVTujptmxb  False   True  False   True
+    G9lrImrSWq  False  False  False   True
+    sFFwdIUfz2    NaN    NaN    NaN    NaN
+    s15ptEJnRb    NaN    NaN    NaN    NaN
+    ...           ...    ...    ...    ...
+    UW41KkDyZ4   True   True  False  False
+    l9l6XkOdqV   True  False  False  False
+    X2MeZfzDYA  False   True  False  False
+    xWkIKU7vfX  False   True  False   True
+    QOhL6VmpGU  False  False  False   True
+    22PwkRJdat  False   True  False  False
+    kfboQ3VeIK   True  False   True  False
+
+    [30 rows x 4 columns]
+    """
+    df = DataFrame(tm.getSeriesData()) > 0
+    df = df.astype(object)
+    # set some NAs
+    df.iloc[5:10] = np.nan
+    df.iloc[15:20, -2:] = np.nan
+
+    # For `any` tests we need to have at least one True before the first NaN
+    #  in each column
+    for i in range(4):
+        df.iloc[i, i] = True
+    return df
+
+
+@pytest.fixture
+def float_frame_with_na():
+    """
+    Fixture for DataFrame of floats with index of unique strings
+
+    Columns are ['A', 'B', 'C', 'D']; some entries are missing
+
+                       A         B         C         D
+    ABwBzA0ljw -1.128865 -0.897161  0.046603  0.274997
+    DJiRzmbyQF  0.728869  0.233502  0.722431 -0.890872
+    neMgPD5UBF  0.486072 -1.027393 -0.031553  1.449522
+    0yWA4n8VeX -1.937191 -1.142531  0.805215 -0.462018
+    3slYUbbqU1  0.153260  1.164691  1.489795 -0.545826
+    soujjZ0A08       NaN       NaN       NaN       NaN
+    7W6NLGsjB9       NaN       NaN       NaN       NaN
+    ...              ...       ...       ...       ...
+    uhfeaNkCR1 -0.231210 -0.340472  0.244717 -0.901590
+    n6p7GYuBIV -0.419052  1.922721 -0.125361 -0.727717
+    ZhzAeY6p1y  1.234374 -1.425359 -0.827038 -0.633189
+    uWdPsORyUh  0.046738 -0.980445 -1.102965  0.605503
+    3DJA6aN590 -0.091018 -1.684734 -1.100900  0.215947
+    2GBPAzdbMk -2.883405 -1.021071  1.209877  1.633083
+    sHadBoyVHw -2.223032 -0.326384  0.258931  0.245517
+
+    [30 rows x 4 columns]
+    """
+    df = DataFrame(tm.getSeriesData())
+    # set some NAs
+    df.iloc[5:10] = np.nan
+    df.iloc[15:20, -2:] = np.nan
+    return df
+
+
 class TestDataFrameAnalytics:
     # ---------------------------------------------------------------------
     # Reductions
diff --git a/pandas/tests/groupby/aggregate/test_aggregate.py b/pandas/tests/groupby/aggregate/test_aggregate.py
index 78b99a00d43ce..45884a4b3c20f 100644
--- a/pandas/tests/groupby/aggregate/test_aggregate.py
+++ b/pandas/tests/groupby/aggregate/test_aggregate.py
@@ -178,8 +178,8 @@ def test_agg_grouping_is_list_tuple(ts):
     tm.assert_frame_equal(result, expected)
 
 
-def test_agg_python_multiindex(mframe):
-    grouped = mframe.groupby(["A", "B"])
+def test_agg_python_multiindex(multiindex_dataframe_random_data):
+    grouped = multiindex_dataframe_random_data.groupby(["A", "B"])
 
     result = grouped.agg("mean")
     expected = grouped.mean()
diff --git a/pandas/tests/groupby/conftest.py b/pandas/tests/groupby/conftest.py
index 49fa9dc51f0d3..b8fb3b7fff676 100644
--- a/pandas/tests/groupby/conftest.py
+++ b/pandas/tests/groupby/conftest.py
@@ -24,21 +24,11 @@ def dropna(request):
     return request.param
 
 
-@pytest.fixture(params=[True, False])
-def skipna(request):
-    return request.param
-
-
 @pytest.fixture(params=[True, False])
 def observed(request):
     return request.param
 
 
-@pytest.fixture
-def mframe(multiindex_dataframe_random_data):
-    return multiindex_dataframe_random_data
-
-
 @pytest.fixture
 def df():
     return DataFrame(
@@ -57,25 +47,8 @@ def ts():
 
 
 @pytest.fixture
-def tsd():
-    return tm.getTimeSeriesData()
-
-
-@pytest.fixture
-def tsframe(tsd):
-    return DataFrame(tsd)
-
-
-@pytest.fixture
-def df_mixed_floats():
-    return DataFrame(
-        {
-            "A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
-            "B": ["one", "one", "two", "three", "two", "two", "one", "three"],
-            "C": np.random.default_rng(2).standard_normal(8),
-            "D": np.array(np.random.default_rng(2).standard_normal(8), dtype="float32"),
-        }
-    )
+def tsframe():
+    return DataFrame(tm.getTimeSeriesData())
 
 
 @pytest.fixture
diff --git a/pandas/tests/groupby/methods/test_describe.py b/pandas/tests/groupby/methods/test_describe.py
index c2ffcb04caa60..ee8f93bf3b549 100644
--- a/pandas/tests/groupby/methods/test_describe.py
+++ b/pandas/tests/groupby/methods/test_describe.py
@@ -11,8 +11,8 @@
 import pandas._testing as tm
 
 
-def test_apply_describe_bug(mframe):
-    grouped = mframe.groupby(level="first")
+def test_apply_describe_bug(multiindex_dataframe_random_data):
+    grouped = multiindex_dataframe_random_data.groupby(level="first")
     grouped.describe()  # it works!
 
 
diff --git a/pandas/tests/groupby/methods/test_nth.py b/pandas/tests/groupby/methods/test_nth.py
index 4a5571d0daa42..e39cfd520ba1a 100644
--- a/pandas/tests/groupby/methods/test_nth.py
+++ b/pandas/tests/groupby/methods/test_nth.py
@@ -122,8 +122,15 @@ def test_first_last_with_None_expanded(method, df, expected):
     tm.assert_frame_equal(result, expected)
 
 
-def test_first_last_nth_dtypes(df_mixed_floats):
-    df = df_mixed_floats.copy()
+def test_first_last_nth_dtypes():
+    df = DataFrame(
+        {
+            "A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
+            "B": ["one", "one", "two", "three", "two", "two", "one", "three"],
+            "C": np.random.default_rng(2).standard_normal(8),
+            "D": np.array(np.random.default_rng(2).standard_normal(8), dtype="float32"),
+        }
+    )
     df["E"] = True
     df["F"] = 1
 
diff --git a/pandas/tests/groupby/test_api.py b/pandas/tests/groupby/test_api.py
index 1a030841ba3ab..3066825352fa7 100644
--- a/pandas/tests/groupby/test_api.py
+++ b/pandas/tests/groupby/test_api.py
@@ -24,8 +24,8 @@
 )
 
 
-def test_tab_completion(mframe):
-    grp = mframe.groupby(level="second")
+def test_tab_completion(multiindex_dataframe_random_data):
+    grp = multiindex_dataframe_random_data.groupby(level="second")
     results = {v for v in dir(grp) if not v.startswith("_")}
     expected = {
         "A",
@@ -98,9 +98,13 @@ def test_tab_completion(mframe):
     assert results == expected
 
 
-def test_all_methods_categorized(mframe):
-    grp = mframe.groupby(mframe.iloc[:, 0])
-    names = {_ for _ in dir(grp) if not _.startswith("_")} - set(mframe.columns)
+def test_all_methods_categorized(multiindex_dataframe_random_data):
+    grp = multiindex_dataframe_random_data.groupby(
+        multiindex_dataframe_random_data.iloc[:, 0]
+    )
+    names = {_ for _ in dir(grp) if not _.startswith("_")} - set(
+        multiindex_dataframe_random_data.columns
+    )
     new_names = set(names)
     new_names -= reduction_kernels
     new_names -= transformation_kernels
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 693650274cd23..c61d9fab0435e 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -136,18 +136,27 @@ def test_basic_aggregations(dtype):
         grouped.aggregate(lambda x: x * 2)
 
 
-def test_groupby_nonobject_dtype(mframe, df_mixed_floats):
-    key = mframe.index.codes[0]
-    grouped = mframe.groupby(key)
+def test_groupby_nonobject_dtype(multiindex_dataframe_random_data):
+    key = multiindex_dataframe_random_data.index.codes[0]
+    grouped = multiindex_dataframe_random_data.groupby(key)
     result = grouped.sum()
 
-    expected = mframe.groupby(key.astype("O")).sum()
+    expected = multiindex_dataframe_random_data.groupby(key.astype("O")).sum()
     assert result.index.dtype == np.int8
     assert expected.index.dtype == np.int64
     tm.assert_frame_equal(result, expected, check_index_type=False)
 
+
+def test_groupby_nonobject_dtype_mixed():
     # GH 3911, mixed frame non-conversion
-    df = df_mixed_floats.copy()
+    df = DataFrame(
+        {
+            "A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
+            "B": ["one", "one", "two", "three", "two", "two", "one", "three"],
+            "C": np.random.default_rng(2).standard_normal(8),
+            "D": np.array(np.random.default_rng(2).standard_normal(8), dtype="float32"),
+        }
+    )
     df["value"] = range(len(df))
 
     def max_value(group):
@@ -1052,7 +1061,7 @@ def test_raise_on_nuisance_python_multiple(three_group):
         grouped.mean()
 
 
-def test_empty_groups_corner(mframe):
+def test_empty_groups_corner(multiindex_dataframe_random_data):
     # handle empty groups
     df = DataFrame(
         {
@@ -1069,7 +1078,7 @@ def test_empty_groups_corner(mframe):
     expected = grouped.mean(numeric_only=True)
     tm.assert_frame_equal(result, expected)
 
-    grouped = mframe[3:5].groupby(level=0)
+    grouped = multiindex_dataframe_random_data[3:5].groupby(level=0)
     agged = grouped.apply(lambda x: x.mean())
     agged_A = grouped["A"].apply("mean")
     tm.assert_series_equal(agged["A"], agged_A)
@@ -1083,8 +1092,8 @@ def test_nonsense_func():
         df.groupby(lambda x: x + "foo")
 
 
-def test_wrap_aggregated_output_multindex(mframe):
-    df = mframe.T
+def test_wrap_aggregated_output_multindex(multiindex_dataframe_random_data):
+    df = multiindex_dataframe_random_data.T
     df["baz", "two"] = "peekaboo"
 
     keys = [np.array([0, 0, 1]), np.array([0, 0, 1])]
@@ -1103,24 +1112,24 @@ def aggfun(ser):
         df.groupby(keys).aggregate(aggfun)
 
 
-def test_groupby_level_apply(mframe):
-    result = mframe.groupby(level=0).count()
+def test_groupby_level_apply(multiindex_dataframe_random_data):
+    result = multiindex_dataframe_random_data.groupby(level=0).count()
     assert result.index.name == "first"
-    result = mframe.groupby(level=1).count()
+    result = multiindex_dataframe_random_data.groupby(level=1).count()
     assert result.index.name == "second"
 
-    result = mframe["A"].groupby(level=0).count()
+    result = multiindex_dataframe_random_data["A"].groupby(level=0).count()
     assert result.index.name == "first"
 
 
-def test_groupby_level_mapper(mframe):
-    deleveled = mframe.reset_index()
+def test_groupby_level_mapper(multiindex_dataframe_random_data):
+    deleveled = multiindex_dataframe_random_data.reset_index()
 
     mapper0 = {"foo": 0, "bar": 0, "baz": 1, "qux": 1}
     mapper1 = {"one": 0, "two": 0, "three": 1}
 
-    result0 = mframe.groupby(mapper0, level=0).sum()
-    result1 = mframe.groupby(mapper1, level=1).sum()
+    result0 = multiindex_dataframe_random_data.groupby(mapper0, level=0).sum()
+    result1 = multiindex_dataframe_random_data.groupby(mapper1, level=1).sum()
 
     mapped_level0 = np.array(
         [mapper0.get(x) for x in deleveled["first"]], dtype=np.int64
@@ -1128,8 +1137,8 @@ def test_groupby_level_mapper(mframe):
     mapped_level1 = np.array(
         [mapper1.get(x) for x in deleveled["second"]], dtype=np.int64
     )
-    expected0 = mframe.groupby(mapped_level0).sum()
-    expected1 = mframe.groupby(mapped_level1).sum()
+    expected0 = multiindex_dataframe_random_data.groupby(mapped_level0).sum()
+    expected1 = multiindex_dataframe_random_data.groupby(mapped_level1).sum()
     expected0.index.name, expected1.index.name = "first", "second"
 
     tm.assert_frame_equal(result0, expected0)
diff --git a/pandas/tests/groupby/test_grouping.py b/pandas/tests/groupby/test_grouping.py
index 3e52476be9dbd..e3cc41afa4679 100644
--- a/pandas/tests/groupby/test_grouping.py
+++ b/pandas/tests/groupby/test_grouping.py
@@ -534,22 +534,24 @@ def test_multiindex_passthru(self):
         result = gb.first()
         tm.assert_frame_equal(result, df)
 
-    def test_multiindex_negative_level(self, mframe):
+    def test_multiindex_negative_level(self, multiindex_dataframe_random_data):
         # GH 13901
-        result = mframe.groupby(level=-1).sum()
-        expected = mframe.groupby(level="second").sum()
+        result = multiindex_dataframe_random_data.groupby(level=-1).sum()
+        expected = multiindex_dataframe_random_data.groupby(level="second").sum()
         tm.assert_frame_equal(result, expected)
 
-        result = mframe.groupby(level=-2).sum()
-        expected = mframe.groupby(level="first").sum()
+        result = multiindex_dataframe_random_data.groupby(level=-2).sum()
+        expected = multiindex_dataframe_random_data.groupby(level="first").sum()
         tm.assert_frame_equal(result, expected)
 
-        result = mframe.groupby(level=[-2, -1]).sum()
-        expected = mframe.sort_index()
+        result = multiindex_dataframe_random_data.groupby(level=[-2, -1]).sum()
+        expected = multiindex_dataframe_random_data.sort_index()
         tm.assert_frame_equal(result, expected)
 
-        result = mframe.groupby(level=[-1, "first"]).sum()
-        expected = mframe.groupby(level=["second", "first"]).sum()
+        result = multiindex_dataframe_random_data.groupby(level=[-1, "first"]).sum()
+        expected = multiindex_dataframe_random_data.groupby(
+            level=["second", "first"]
+        ).sum()
         tm.assert_frame_equal(result, expected)
 
     def test_multifunc_select_col_integer_cols(self, df):
@@ -641,9 +643,9 @@ def test_groupby_multiindex_partial_indexing_equivalence(self):
         tm.assert_dict_equal(expected_groups, result_groups)
 
     @pytest.mark.parametrize("sort", [True, False])
-    def test_groupby_level(self, sort, mframe, df):
+    def test_groupby_level(self, sort, multiindex_dataframe_random_data, df):
         # GH 17537
-        frame = mframe
+        frame = multiindex_dataframe_random_data
         deleveled = frame.reset_index()
 
         result0 = frame.groupby(level=0, sort=sort).sum()
@@ -724,9 +726,9 @@ def test_groupby_level_with_nas(self, sort):
         expected = Series([6.0, 18.0], index=[0.0, 1.0])
         tm.assert_series_equal(result, expected)
 
-    def test_groupby_args(self, mframe):
+    def test_groupby_args(self, multiindex_dataframe_random_data):
         # PR8618 and issue 8015
-        frame = mframe
+        frame = multiindex_dataframe_random_data
 
         msg = "You have to supply one of 'by' and 'level'"
         with pytest.raises(TypeError, match=msg):
@@ -743,14 +745,16 @@ def test_groupby_args(self, mframe):
             [False, [0, 0, 0, 1, 1, 2, 2, 3, 3, 3]],
         ],
     )
-    def test_level_preserve_order(self, sort, labels, mframe):
+    def test_level_preserve_order(self, sort, labels, multiindex_dataframe_random_data):
         # GH 17537
-        grouped = mframe.groupby(level=0, sort=sort)
+        grouped = multiindex_dataframe_random_data.groupby(level=0, sort=sort)
         exp_labels = np.array(labels, np.intp)
         tm.assert_almost_equal(grouped.grouper.codes[0], exp_labels)
 
-    def test_grouping_labels(self, mframe):
-        grouped = mframe.groupby(mframe.index.get_level_values(0))
+    def test_grouping_labels(self, multiindex_dataframe_random_data):
+        grouped = multiindex_dataframe_random_data.groupby(
+            multiindex_dataframe_random_data.index.get_level_values(0)
+        )
         exp_labels = np.array([2, 2, 2, 0, 0, 1, 1, 3, 3, 3], dtype=np.intp)
         tm.assert_almost_equal(grouped.grouper.codes[0], exp_labels)
 
diff --git a/pandas/tests/indexes/conftest.py b/pandas/tests/indexes/conftest.py
index 808a1687390ff..bfb7acdcf4812 100644
--- a/pandas/tests/indexes/conftest.py
+++ b/pandas/tests/indexes/conftest.py
@@ -5,7 +5,6 @@
     Series,
     array,
 )
-import pandas._testing as tm
 
 
 @pytest.fixture(params=[None, False])
@@ -40,22 +39,3 @@ def listlike_box(request):
     Types that may be passed as the indexer to searchsorted.
     """
     return request.param
-
-
-@pytest.fixture(
-    params=tm.ALL_REAL_NUMPY_DTYPES
-    + [
-        "object",
-        "category",
-        "datetime64[ns]",
-        "timedelta64[ns]",
-    ]
-)
-def any_dtype_for_small_pos_integer_indexes(request):
-    """
-    Dtypes that can be given to an Index with small positive integers.
-
-    This means that for any dtype `x` in the params list, `Index([1, 2, 3], dtype=x)` is
-    valid and gives the correct Index (sub-)class.
-    """
-    return request.param
diff --git a/pandas/tests/indexes/multi/conftest.py b/pandas/tests/indexes/multi/conftest.py
index 3cc4fa4713831..15062aee56e3a 100644
--- a/pandas/tests/indexes/multi/conftest.py
+++ b/pandas/tests/indexes/multi/conftest.py
@@ -1,7 +1,6 @@
 import numpy as np
 import pytest
 
-import pandas as pd
 from pandas import (
     Index,
     MultiIndex,
@@ -26,52 +25,3 @@ def idx():
         verify_integrity=False,
     )
     return mi
-
-
-@pytest.fixture
-def idx_dup():
-    # compare tests/indexes/multi/conftest.py
-    major_axis = Index(["foo", "bar", "baz", "qux"])
-    minor_axis = Index(["one", "two"])
-
-    major_codes = np.array([0, 0, 1, 0, 1, 1])
-    minor_codes = np.array([0, 1, 0, 1, 0, 1])
-    index_names = ["first", "second"]
-    mi = MultiIndex(
-        levels=[major_axis, minor_axis],
-        codes=[major_codes, minor_codes],
-        names=index_names,
-        verify_integrity=False,
-    )
-    return mi
-
-
-@pytest.fixture
-def index_names():
-    # names that match those in the idx fixture for testing equality of
-    # names assigned to the idx
-    return ["first", "second"]
-
-
-@pytest.fixture
-def narrow_multi_index():
-    """
-    Return a MultiIndex that is narrower than the display (<80 characters).
-    """
-    n = 1000
-    ci = pd.CategoricalIndex(list("a" * n) + (["abc"] * n))
-    dti = pd.date_range("2000-01-01", freq="s", periods=n * 2)
-    return MultiIndex.from_arrays([ci, ci.codes + 9, dti], names=["a", "b", "dti"])
-
-
-@pytest.fixture
-def wide_multi_index():
-    """
-    Return a MultiIndex that is wider than the display (>80 characters).
-    """
-    n = 1000
-    ci = pd.CategoricalIndex(list("a" * n) + (["abc"] * n))
-    dti = pd.date_range("2000-01-01", freq="s", periods=n * 2)
-    levels = [ci, ci.codes + 9, dti, dti, dti]
-    names = ["a", "b", "dti_1", "dti_2", "dti_3"]
-    return MultiIndex.from_arrays(levels, names=names)
diff --git a/pandas/tests/indexes/multi/test_duplicates.py b/pandas/tests/indexes/multi/test_duplicates.py
index ee1edaa27f804..a69248cf038f8 100644
--- a/pandas/tests/indexes/multi/test_duplicates.py
+++ b/pandas/tests/indexes/multi/test_duplicates.py
@@ -11,12 +11,31 @@
 from pandas import (
     NA,
     DatetimeIndex,
+    Index,
     MultiIndex,
     Series,
 )
 import pandas._testing as tm
 
 
+@pytest.fixture
+def idx_dup():
+    # compare tests/indexes/multi/conftest.py
+    major_axis = Index(["foo", "bar", "baz", "qux"])
+    minor_axis = Index(["one", "two"])
+
+    major_codes = np.array([0, 0, 1, 0, 1, 1])
+    minor_codes = np.array([0, 1, 0, 1, 0, 1])
+    index_names = ["first", "second"]
+    mi = MultiIndex(
+        levels=[major_axis, minor_axis],
+        codes=[major_codes, minor_codes],
+        names=index_names,
+        verify_integrity=False,
+    )
+    return mi
+
+
 @pytest.mark.parametrize("names", [None, ["first", "second"]])
 def test_unique(names):
     mi = MultiIndex.from_arrays([[1, 2, 1, 2], [1, 1, 1, 2]], names=names)
diff --git a/pandas/tests/indexes/multi/test_formats.py b/pandas/tests/indexes/multi/test_formats.py
index 1736f65e355fb..52ff3109128f2 100644
--- a/pandas/tests/indexes/multi/test_formats.py
+++ b/pandas/tests/indexes/multi/test_formats.py
@@ -139,8 +139,11 @@ def test_repr(self, idx):
            names=['first', ...], length=6)"""
             assert result == expected
 
-    def test_rjust(self, narrow_multi_index):
-        mi = narrow_multi_index
+    def test_rjust(self):
+        n = 1000
+        ci = pd.CategoricalIndex(list("a" * n) + (["abc"] * n))
+        dti = pd.date_range("2000-01-01", freq="s", periods=n * 2)
+        mi = MultiIndex.from_arrays([ci, ci.codes + 9, dti], names=["a", "b", "dti"])
         result = mi[:1].__repr__()
         expected = """\
 MultiIndex([('a', 9, '2000-01-01 00:00:00')],
@@ -182,8 +185,13 @@ def test_rjust(self, narrow_multi_index):
            names=['a', 'b', 'dti'], length=2000)"""
         assert result == expected
 
-    def test_tuple_width(self, wide_multi_index):
-        mi = wide_multi_index
+    def test_tuple_width(self):
+        n = 1000
+        ci = pd.CategoricalIndex(list("a" * n) + (["abc"] * n))
+        dti = pd.date_range("2000-01-01", freq="s", periods=n * 2)
+        levels = [ci, ci.codes + 9, dti, dti, dti]
+        names = ["a", "b", "dti_1", "dti_2", "dti_3"]
+        mi = MultiIndex.from_arrays(levels, names=names)
         result = mi[:1].__repr__()
         expected = """MultiIndex([('a', 9, '2000-01-01 00:00:00', '2000-01-01 00:00:00', ...)],
            names=['a', 'b', 'dti_1', 'dti_2', 'dti_3'])"""  # noqa: E501
diff --git a/pandas/tests/indexes/multi/test_get_set.py b/pandas/tests/indexes/multi/test_get_set.py
index 0720a1e1c648c..e362fc8a05a46 100644
--- a/pandas/tests/indexes/multi/test_get_set.py
+++ b/pandas/tests/indexes/multi/test_get_set.py
@@ -95,8 +95,9 @@ def test_get_level_number_out_of_bounds(multiindex_dataframe_random_data):
         frame.index._get_level_number(-3)
 
 
-def test_set_name_methods(idx, index_names):
+def test_set_name_methods(idx):
     # so long as these are synonyms, we don't need to test set_names
+    index_names = ["first", "second"]
     assert idx.rename == idx.set_names
     new_names = [name + "SUFFIX" for name in index_names]
     ind = idx.set_names(new_names)
diff --git a/pandas/tests/indexes/multi/test_names.py b/pandas/tests/indexes/multi/test_names.py
index 8ae643eb3626d..45f19b4d70fb9 100644
--- a/pandas/tests/indexes/multi/test_names.py
+++ b/pandas/tests/indexes/multi/test_names.py
@@ -83,11 +83,11 @@ def test_copy_names():
         multi_idx.copy(names=[["mario"], ["luigi"]])
 
 
-def test_names(idx, index_names):
+def test_names(idx):
     # names are assigned in setup
-    assert index_names == ["first", "second"]
+    assert idx.names == ["first", "second"]
     level_names = [level.name for level in idx.levels]
-    assert level_names == index_names
+    assert level_names == idx.names
 
     # setting bad names on existing
     index = idx
diff --git a/pandas/tests/indexes/test_setops.py b/pandas/tests/indexes/test_setops.py
index d126d32e627cd..1f328c06b483b 100644
--- a/pandas/tests/indexes/test_setops.py
+++ b/pandas/tests/indexes/test_setops.py
@@ -30,6 +30,25 @@
 )
 
 
+@pytest.fixture(
+    params=tm.ALL_REAL_NUMPY_DTYPES
+    + [
+        "object",
+        "category",
+        "datetime64[ns]",
+        "timedelta64[ns]",
+    ]
+)
+def any_dtype_for_small_pos_integer_indexes(request):
+    """
+    Dtypes that can be given to an Index with small positive integers.
+
+    This means that for any dtype `x` in the params list, `Index([1, 2, 3], dtype=x)` is
+    valid and gives the correct Index (sub-)class.
+    """
+    return request.param
+
+
 def test_union_same_types(index):
     # Union with a non-unique, non-monotonic index raises error
     # Only needed for bool index factory
diff --git a/pandas/tests/io/data/gbq_fake_job.txt b/pandas/tests/io/data/gbq_fake_job.txt
deleted file mode 100644
index b0995222292e4..0000000000000
--- a/pandas/tests/io/data/gbq_fake_job.txt
+++ /dev/null
@@ -1 +0,0 @@
-{'status': {'state': 'DONE'}, 'kind': 'bigquery#job', 'statistics': {'query': {'cacheHit': True, 'totalBytesProcessed': '0'}, 'endTime': '1377668744674', 'totalBytesProcessed': '0', 'startTime': '1377668744466'}, 'jobReference': {'projectId': '57288129629', 'jobId': 'bqjob_r5f956972f0190bdf_00000140c374bf42_2'}, 'etag': '"4PTsVxg68bQkQs1RJ1Ndewqkgg4/oO4VmgFrAku4N6FWci9s7iFIftc"', 'configuration': {'query': {'createDisposition': 'CREATE_IF_NEEDED', 'query': 'SELECT * FROM [publicdata:samples.shakespeare]', 'writeDisposition': 'WRITE_TRUNCATE', 'destinationTable': {'projectId': '57288129629', 'tableId': 'anonb5ec450da88eeeb78a27784ea482ee75a146d442', 'datasetId': '_d0b4f5f0d50dc68a3eb0fa6cba66a9a8687d9253'}}}, 'id': '57288129629:bqjob_r5f956972f0190bdf_00000140c374bf42_2', 'selfLink': 'https://www.googleapis.com/bigquery/v2/projects/57288129629/jobs/bqjob_r5f956972f0190bdf_00000140c374bf42_2'}
\ No newline at end of file
diff --git a/pandas/tests/io/excel/conftest.py b/pandas/tests/io/excel/conftest.py
deleted file mode 100644
index 15ff52d5bea48..0000000000000
--- a/pandas/tests/io/excel/conftest.py
+++ /dev/null
@@ -1,41 +0,0 @@
-import pytest
-
-import pandas._testing as tm
-
-from pandas.io.parsers import read_csv
-
-
-@pytest.fixture
-def frame(float_frame):
-    """
-    Returns the first ten items in fixture "float_frame".
-    """
-    return float_frame[:10]
-
-
-@pytest.fixture
-def tsframe():
-    return tm.makeTimeDataFrame()[:5]
-
-
-@pytest.fixture(params=[True, False])
-def merge_cells(request):
-    return request.param
-
-
-@pytest.fixture
-def df_ref(datapath):
-    """
-    Obtain the reference data from read_csv with the Python engine.
-    """
-    filepath = datapath("io", "data", "csv", "test1.csv")
-    df_ref = read_csv(filepath, index_col=0, parse_dates=True, engine="python")
-    return df_ref
-
-
-@pytest.fixture(params=[".xls", ".xlsx", ".xlsm", ".ods", ".xlsb"])
-def read_ext(request):
-    """
-    Valid extensions for reading Excel files.
-    """
-    return request.param
diff --git a/pandas/tests/io/excel/test_odswriter.py b/pandas/tests/io/excel/test_odswriter.py
index ecee58362f8a9..271353a173d2a 100644
--- a/pandas/tests/io/excel/test_odswriter.py
+++ b/pandas/tests/io/excel/test_odswriter.py
@@ -13,7 +13,10 @@
 
 odf = pytest.importorskip("odf")
 
-pytestmark = pytest.mark.parametrize("ext", [".ods"])
+
+@pytest.fixture
+def ext():
+    return ".ods"
 
 
 def test_write_append_mode_raises(ext):
diff --git a/pandas/tests/io/excel/test_openpyxl.py b/pandas/tests/io/excel/test_openpyxl.py
index 53cbd1ce3cceb..2df9ec9e53516 100644
--- a/pandas/tests/io/excel/test_openpyxl.py
+++ b/pandas/tests/io/excel/test_openpyxl.py
@@ -17,10 +17,13 @@
 
 openpyxl = pytest.importorskip("openpyxl")
 
-pytestmark = pytest.mark.parametrize("ext", [".xlsx"])
 
+@pytest.fixture
+def ext():
+    return ".xlsx"
 
-def test_to_excel_styleconverter(ext):
+
+def test_to_excel_styleconverter():
     from openpyxl import styles
 
     hstyle = {
diff --git a/pandas/tests/io/excel/test_readers.py b/pandas/tests/io/excel/test_readers.py
index 74fe5166df65f..abbdb77efad0e 100644
--- a/pandas/tests/io/excel/test_readers.py
+++ b/pandas/tests/io/excel/test_readers.py
@@ -22,6 +22,7 @@
     Index,
     MultiIndex,
     Series,
+    read_csv,
 )
 import pandas._testing as tm
 from pandas.core.arrays import (
@@ -117,6 +118,16 @@ def read_ext(engine_and_read_ext):
     return read_ext
 
 
+@pytest.fixture
+def df_ref(datapath):
+    """
+    Obtain the reference data from read_csv with the Python engine.
+    """
+    filepath = datapath("io", "data", "csv", "test1.csv")
+    df_ref = read_csv(filepath, index_col=0, parse_dates=True, engine="python")
+    return df_ref
+
+
 def adjust_expected(expected: DataFrame, read_ext: str) -> None:
     expected.index.name = None
 
diff --git a/pandas/tests/io/excel/test_writers.py b/pandas/tests/io/excel/test_writers.py
index b9ea440b3e859..22cd0621fd4c4 100644
--- a/pandas/tests/io/excel/test_writers.py
+++ b/pandas/tests/io/excel/test_writers.py
@@ -34,6 +34,19 @@
 from pandas.io.excel._util import _writers
 
 
+@pytest.fixture
+def frame(float_frame):
+    """
+    Returns the first ten items in fixture "float_frame".
+    """
+    return float_frame[:10]
+
+
+@pytest.fixture(params=[True, False])
+def merge_cells(request):
+    return request.param
+
+
 @pytest.fixture
 def path(ext):
     """
@@ -444,8 +457,8 @@ def test_mixed(self, frame, path):
             recons = pd.read_excel(reader, sheet_name="test1", index_col=0)
         tm.assert_frame_equal(mixed_frame, recons)
 
-    def test_ts_frame(self, tsframe, path):
-        df = tsframe
+    def test_ts_frame(self, path):
+        df = tm.makeTimeDataFrame()[:5]
 
         # freq doesn't round-trip
         index = pd.DatetimeIndex(np.asarray(df.index), freq=None)
@@ -516,8 +529,9 @@ def test_inf_roundtrip(self, path):
 
         tm.assert_frame_equal(df, recons)
 
-    def test_sheets(self, frame, tsframe, path):
+    def test_sheets(self, frame, path):
         # freq doesn't round-trip
+        tsframe = tm.makeTimeDataFrame()[:5]
         index = pd.DatetimeIndex(np.asarray(tsframe.index), freq=None)
         tsframe.index = index
 
@@ -633,10 +647,11 @@ def test_excel_roundtrip_indexname(self, merge_cells, path):
         tm.assert_frame_equal(result, df)
         assert result.index.name == "foo"
 
-    def test_excel_roundtrip_datetime(self, merge_cells, tsframe, path):
+    def test_excel_roundtrip_datetime(self, merge_cells, path):
         # datetime.date, not sure what to test here exactly
 
         # freq does not round-trip
+        tsframe = tm.makeTimeDataFrame()[:5]
         index = pd.DatetimeIndex(np.asarray(tsframe.index), freq=None)
         tsframe.index = index
 
@@ -751,8 +766,8 @@ def test_to_excel_timedelta(self, path):
             recons = pd.read_excel(reader, sheet_name="test1", index_col=0)
         tm.assert_frame_equal(expected, recons)
 
-    def test_to_excel_periodindex(self, tsframe, path):
-        xp = tsframe.resample("ME", kind="period").mean()
+    def test_to_excel_periodindex(self, path):
+        xp = tm.makeTimeDataFrame()[:5].resample("ME", kind="period").mean()
 
         xp.to_excel(path, sheet_name="sht1")
 
@@ -814,8 +829,9 @@ def test_to_excel_multiindex_cols(self, merge_cells, frame, path):
             frame.columns = [".".join(map(str, q)) for q in zip(*fm)]
         tm.assert_frame_equal(frame, df)
 
-    def test_to_excel_multiindex_dates(self, merge_cells, tsframe, path):
+    def test_to_excel_multiindex_dates(self, merge_cells, path):
         # try multiindex with dates
+        tsframe = tm.makeTimeDataFrame()[:5]
         new_index = [tsframe.index, np.arange(len(tsframe.index), dtype=np.int64)]
         tsframe.index = MultiIndex.from_arrays(new_index)
 
diff --git a/pandas/tests/io/excel/test_xlsxwriter.py b/pandas/tests/io/excel/test_xlsxwriter.py
index c4d02d71390cc..94f6bdfaf069c 100644
--- a/pandas/tests/io/excel/test_xlsxwriter.py
+++ b/pandas/tests/io/excel/test_xlsxwriter.py
@@ -9,7 +9,10 @@
 
 xlsxwriter = pytest.importorskip("xlsxwriter")
 
-pytestmark = pytest.mark.parametrize("ext", [".xlsx"])
+
+@pytest.fixture
+def ext():
+    return ".xlsx"
 
 
 def test_column_format(ext):
diff --git a/pandas/tests/io/json/conftest.py b/pandas/tests/io/json/conftest.py
index f3736252e850a..4e848cd48b42d 100644
--- a/pandas/tests/io/json/conftest.py
+++ b/pandas/tests/io/json/conftest.py
@@ -7,10 +7,3 @@ def orient(request):
     Fixture for orients excluding the table format.
     """
     return request.param
-
-
-@pytest.fixture(params=["ujson", "pyarrow"])
-def engine(request):
-    if request.param == "pyarrow":
-        pytest.importorskip("pyarrow.json")
-    return request.param
diff --git a/pandas/tests/io/json/test_readlines.py b/pandas/tests/io/json/test_readlines.py
index f5342e0ab1a38..d96ccb4b94cc2 100644
--- a/pandas/tests/io/json/test_readlines.py
+++ b/pandas/tests/io/json/test_readlines.py
@@ -25,6 +25,13 @@ def lines_json_df():
     return df.to_json(lines=True, orient="records")
 
 
+@pytest.fixture(params=["ujson", "pyarrow"])
+def engine(request):
+    if request.param == "pyarrow":
+        pytest.importorskip("pyarrow.json")
+    return request.param
+
+
 def test_read_jsonl():
     # GH9180
     result = read_json(StringIO('{"a": 1, "b": 2}\n{"b":2, "a" :1}\n'), lines=True)
diff --git a/pandas/tests/io/parser/usecols/test_usecols_basic.py b/pandas/tests/io/parser/usecols/test_usecols_basic.py
index 15b321c4616ca..23138f2710caf 100644
--- a/pandas/tests/io/parser/usecols/test_usecols_basic.py
+++ b/pandas/tests/io/parser/usecols/test_usecols_basic.py
@@ -98,7 +98,7 @@ def test_usecols_with_names(all_parsers):
 @pytest.mark.parametrize(
     "names,usecols", [(["b", "c"], [1, 2]), (["a", "b", "c"], ["b", "c"])]
 )
-def test_usecols_relative_to_names(all_parsers, names, usecols, request):
+def test_usecols_relative_to_names(all_parsers, names, usecols):
     data = """\
 1,2,3
 4,5,6
diff --git a/pandas/tests/io/test_fsspec.py b/pandas/tests/io/test_fsspec.py
index 8726d44c9c3ed..a1dec8a2d05b4 100644
--- a/pandas/tests/io/test_fsspec.py
+++ b/pandas/tests/io/test_fsspec.py
@@ -23,6 +23,28 @@
 )
 
 
+@pytest.fixture
+def fsspectest():
+    pytest.importorskip("fsspec")
+    from fsspec import register_implementation
+    from fsspec.implementations.memory import MemoryFileSystem
+    from fsspec.registry import _registry as registry
+
+    class TestMemoryFS(MemoryFileSystem):
+        protocol = "testmem"
+        test = [None]
+
+        def __init__(self, **kwargs) -> None:
+            self.test[0] = kwargs.pop("test", None)
+            super().__init__(**kwargs)
+
+    register_implementation("testmem", TestMemoryFS, clobber=True)
+    yield TestMemoryFS()
+    registry.pop("testmem", None)
+    TestMemoryFS.test[0] = None
+    TestMemoryFS.store.clear()
+
+
 @pytest.fixture
 def df1():
     return DataFrame(
diff --git a/pandas/tests/io/xml/conftest.py b/pandas/tests/io/xml/conftest.py
index c88616eb78029..aafda0ff62bbd 100644
--- a/pandas/tests/io/xml/conftest.py
+++ b/pandas/tests/io/xml/conftest.py
@@ -1,9 +1,11 @@
+from pathlib import Path
+
 import pytest
 
 
 @pytest.fixture
-def xml_data_path(tests_io_data_path, datapath):
-    return tests_io_data_path / "xml"
+def xml_data_path():
+    return Path(__file__).parent.parent / "data" / "xml"
 
 
 @pytest.fixture
diff --git a/pandas/tests/plotting/test_misc.py b/pandas/tests/plotting/test_misc.py
index 84f9cd87db97c..56028249fe517 100644
--- a/pandas/tests/plotting/test_misc.py
+++ b/pandas/tests/plotting/test_misc.py
@@ -15,6 +15,7 @@
     interval_range,
     period_range,
     plotting,
+    read_csv,
 )
 import pandas._testing as tm
 from pandas.tests.plotting.common import (
@@ -30,6 +31,14 @@
 cm = pytest.importorskip("matplotlib.cm")
 
 
+@pytest.fixture
+def iris(datapath) -> DataFrame:
+    """
+    The iris dataset as a DataFrame.
+    """
+    return read_csv(datapath("io", "data", "csv", "iris.csv"))
+
+
 @td.skip_if_installed("matplotlib")
 def test_import_error_message():
     # GH-19810
diff --git a/pandas/tests/resample/conftest.py b/pandas/tests/resample/conftest.py
index 90c2a91a22158..1033d908eb22d 100644
--- a/pandas/tests/resample/conftest.py
+++ b/pandas/tests/resample/conftest.py
@@ -1,5 +1,4 @@
 from datetime import datetime
-import warnings
 
 import numpy as np
 import pytest
@@ -8,8 +7,6 @@
     DataFrame,
     Series,
 )
-from pandas.core.indexes.datetimes import date_range
-from pandas.core.indexes.period import period_range
 
 # The various methods we support
 downsample_methods = [
@@ -44,40 +41,6 @@ def resample_method(request):
     return request.param
 
 
-@pytest.fixture
-def simple_date_range_series():
-    """
-    Series with date range index and random data for test purposes.
-    """
-
-    def _simple_date_range_series(start, end, freq="D"):
-        rng = date_range(start, end, freq=freq)
-        return Series(np.random.default_rng(2).standard_normal(len(rng)), index=rng)
-
-    return _simple_date_range_series
-
-
-@pytest.fixture
-def simple_period_range_series():
-    """
-    Series with period range index and random data for test purposes.
-    """
-
-    def _simple_period_range_series(start, end, freq="D"):
-        with warnings.catch_warnings():
-            # suppress Period[B] deprecation warning
-            msg = "|".join(["Period with BDay freq", r"PeriodDtype\[B\] is deprecated"])
-            warnings.filterwarnings(
-                "ignore",
-                msg,
-                category=FutureWarning,
-            )
-            rng = period_range(start, end, freq=freq)
-        return Series(np.random.default_rng(2).standard_normal(len(rng)), index=rng)
-
-    return _simple_period_range_series
-
-
 @pytest.fixture
 def _index_start():
     """Fixture for parametrization of index, series and frame."""
diff --git a/pandas/tests/resample/test_datetime_index.py b/pandas/tests/resample/test_datetime_index.py
index 2bb114593fcd5..554dc92d8508e 100644
--- a/pandas/tests/resample/test_datetime_index.py
+++ b/pandas/tests/resample/test_datetime_index.py
@@ -53,6 +53,19 @@ def unit(request):
     return request.param
 
 
+@pytest.fixture
+def simple_date_range_series():
+    """
+    Series with date range index and random data for test purposes.
+    """
+
+    def _simple_date_range_series(start, end, freq="D"):
+        rng = date_range(start, end, freq=freq)
+        return Series(np.random.default_rng(2).standard_normal(len(rng)), index=rng)
+
+    return _simple_date_range_series
+
+
 def test_custom_grouper(index, unit):
     dti = index.as_unit(unit)
     s = Series(np.array([1] * len(dti)), index=dti, dtype="int64")
@@ -1208,14 +1221,6 @@ def test_corner_cases(unit):
     tm.assert_index_equal(result.index, ex_index)
 
 
-def test_corner_cases_period(simple_period_range_series):
-    # miscellaneous test coverage
-    len0pts = simple_period_range_series("2007-01", "2010-05", freq="M")[:0]
-    # it works
-    result = len0pts.resample("Y-DEC").mean()
-    assert len(result) == 0
-
-
 def test_corner_cases_date(simple_date_range_series, unit):
     # resample to periods
     ts = simple_date_range_series("2000-04-28", "2000-04-30 11:00", freq="h")
diff --git a/pandas/tests/resample/test_period_index.py b/pandas/tests/resample/test_period_index.py
index f3d095bf4b5ed..2e1b0033fd447 100644
--- a/pandas/tests/resample/test_period_index.py
+++ b/pandas/tests/resample/test_period_index.py
@@ -1,4 +1,5 @@
 from datetime import datetime
+import warnings
 
 import dateutil
 import numpy as np
@@ -40,6 +41,27 @@ def _series_name():
     return "pi"
 
 
+@pytest.fixture
+def simple_period_range_series():
+    """
+    Series with period range index and random data for test purposes.
+    """
+
+    def _simple_period_range_series(start, end, freq="D"):
+        with warnings.catch_warnings():
+            # suppress Period[B] deprecation warning
+            msg = "|".join(["Period with BDay freq", r"PeriodDtype\[B\] is deprecated"])
+            warnings.filterwarnings(
+                "ignore",
+                msg,
+                category=FutureWarning,
+            )
+            rng = period_range(start, end, freq=freq)
+        return Series(np.random.default_rng(2).standard_normal(len(rng)), index=rng)
+
+    return _simple_period_range_series
+
+
 class TestPeriodIndex:
     @pytest.mark.parametrize("freq", ["2D", "1h", "2h"])
     @pytest.mark.parametrize("kind", ["period", None, "timestamp"])
@@ -942,3 +964,11 @@ def test_resample_frequency_ME_QE_error_message(series_and_frame, freq_depr):
     obj = series_and_frame
     with pytest.raises(ValueError, match=msg):
         obj.resample(freq_depr)
+
+
+def test_corner_cases_period(simple_period_range_series):
+    # miscellaneous test coverage
+    len0pts = simple_period_range_series("2007-01", "2010-05", freq="M")[:0]
+    # it works
+    result = len0pts.resample("Y-DEC").mean()
+    assert len(result) == 0
diff --git a/pandas/tests/series/methods/test_reset_index.py b/pandas/tests/series/methods/test_reset_index.py
index bb5ad8cc5a25a..9e6b4ce0df1d6 100644
--- a/pandas/tests/series/methods/test_reset_index.py
+++ b/pandas/tests/series/methods/test_reset_index.py
@@ -136,8 +136,16 @@ def test_reset_index_drop_errors(self):
         with pytest.raises(KeyError, match="not found"):
             s.reset_index("wrong", drop=True)
 
-    def test_reset_index_with_drop(self, series_with_multilevel_index):
-        ser = series_with_multilevel_index
+    def test_reset_index_with_drop(self):
+        arrays = [
+            ["bar", "bar", "baz", "baz", "qux", "qux", "foo", "foo"],
+            ["one", "two", "one", "two", "one", "two", "one", "two"],
+        ]
+        tuples = zip(*arrays)
+        index = MultiIndex.from_tuples(tuples)
+        data = np.random.default_rng(2).standard_normal(8)
+        ser = Series(data, index=index)
+        ser.iloc[3] = np.nan
 
         deleveled = ser.reset_index()
         assert isinstance(deleveled, DataFrame)
diff --git a/pandas/tests/strings/conftest.py b/pandas/tests/strings/conftest.py
index 868b5f1283128..036e4de20ba53 100644
--- a/pandas/tests/strings/conftest.py
+++ b/pandas/tests/strings/conftest.py
@@ -1,4 +1,3 @@
-import numpy as np
 import pytest
 
 from pandas import Series
@@ -131,53 +130,3 @@ def any_string_method(request):
     ...     method(*args, **kwargs)
     """
     return request.param
-
-
-# subset of the full set from pandas/conftest.py
-_any_allowed_skipna_inferred_dtype = [
-    ("string", ["a", np.nan, "c"]),
-    ("bytes", [b"a", np.nan, b"c"]),
-    ("empty", [np.nan, np.nan, np.nan]),
-    ("empty", []),
-    ("mixed-integer", ["a", np.nan, 2]),
-]
-ids, _ = zip(*_any_allowed_skipna_inferred_dtype)  # use inferred type as id
-
-
-@pytest.fixture(params=_any_allowed_skipna_inferred_dtype, ids=ids)
-def any_allowed_skipna_inferred_dtype(request):
-    """
-    Fixture for all (inferred) dtypes allowed in StringMethods.__init__
-
-    The covered (inferred) types are:
-    * 'string'
-    * 'empty'
-    * 'bytes'
-    * 'mixed'
-    * 'mixed-integer'
-
-    Returns
-    -------
-    inferred_dtype : str
-        The string for the inferred dtype from _libs.lib.infer_dtype
-    values : np.ndarray
-        An array of object dtype that will be inferred to have
-        `inferred_dtype`
-
-    Examples
-    --------
-    >>> from pandas._libs import lib
-    >>>
-    >>> def test_something(any_allowed_skipna_inferred_dtype):
-    ...     inferred_dtype, values = any_allowed_skipna_inferred_dtype
-    ...     # will pass
-    ...     assert lib.infer_dtype(values, skipna=True) == inferred_dtype
-    ...
-    ...     # constructor for .str-accessor will also pass
-    ...     Series(values).str
-    """
-    inferred_dtype, values = request.param
-    values = np.array(values, dtype=object)  # object dtype to avoid casting
-
-    # correctness of inference tested in tests/dtypes/test_inference.py
-    return inferred_dtype, values
diff --git a/pandas/tests/strings/test_api.py b/pandas/tests/strings/test_api.py
index 0d2f220e70c56..2914b22a52e94 100644
--- a/pandas/tests/strings/test_api.py
+++ b/pandas/tests/strings/test_api.py
@@ -1,3 +1,4 @@
+import numpy as np
 import pytest
 
 from pandas import (
@@ -9,6 +10,55 @@
 )
 from pandas.core.strings.accessor import StringMethods
 
+# subset of the full set from pandas/conftest.py
+_any_allowed_skipna_inferred_dtype = [
+    ("string", ["a", np.nan, "c"]),
+    ("bytes", [b"a", np.nan, b"c"]),
+    ("empty", [np.nan, np.nan, np.nan]),
+    ("empty", []),
+    ("mixed-integer", ["a", np.nan, 2]),
+]
+ids, _ = zip(*_any_allowed_skipna_inferred_dtype)  # use inferred type as id
+
+
+@pytest.fixture(params=_any_allowed_skipna_inferred_dtype, ids=ids)
+def any_allowed_skipna_inferred_dtype(request):
+    """
+    Fixture for all (inferred) dtypes allowed in StringMethods.__init__
+
+    The covered (inferred) types are:
+    * 'string'
+    * 'empty'
+    * 'bytes'
+    * 'mixed'
+    * 'mixed-integer'
+
+    Returns
+    -------
+    inferred_dtype : str
+        The string for the inferred dtype from _libs.lib.infer_dtype
+    values : np.ndarray
+        An array of object dtype that will be inferred to have
+        `inferred_dtype`
+
+    Examples
+    --------
+    >>> from pandas._libs import lib
+    >>>
+    >>> def test_something(any_allowed_skipna_inferred_dtype):
+    ...     inferred_dtype, values = any_allowed_skipna_inferred_dtype
+    ...     # will pass
+    ...     assert lib.infer_dtype(values, skipna=True) == inferred_dtype
+    ...
+    ...     # constructor for .str-accessor will also pass
+    ...     Series(values).str
+    """
+    inferred_dtype, values = request.param
+    values = np.array(values, dtype=object)  # object dtype to avoid casting
+
+    # correctness of inference tested in tests/dtypes/test_inference.py
+    return inferred_dtype, values
+
 
 def test_api(any_string_dtype):
     # GH 6106, GH 9322
diff --git a/pandas/tests/tseries/offsets/conftest.py b/pandas/tests/tseries/offsets/conftest.py
index c9c4d6c456c53..2fc846353dcb5 100644
--- a/pandas/tests/tseries/offsets/conftest.py
+++ b/pandas/tests/tseries/offsets/conftest.py
@@ -3,35 +3,6 @@
 import pytest
 
 from pandas._libs.tslibs import Timestamp
-from pandas._libs.tslibs.offsets import MonthOffset
-
-from pandas.tseries import offsets
-
-
-@pytest.fixture(
-    params=[
-        getattr(offsets, o) for o in offsets.__all__ if o not in ("Tick", "BaseOffset")
-    ]
-)
-def offset_types(request):
-    """
-    Fixture for all the datetime offsets available for a time series.
-    """
-    return request.param
-
-
-@pytest.fixture(
-    params=[
-        getattr(offsets, o)
-        for o in offsets.__all__
-        if issubclass(getattr(offsets, o), MonthOffset) and o != "MonthOffset"
-    ]
-)
-def month_classes(request):
-    """
-    Fixture for month based datetime offsets available for a time series.
-    """
-    return request.param
 
 
 @pytest.fixture
diff --git a/pandas/tests/tseries/offsets/test_offsets.py b/pandas/tests/tseries/offsets/test_offsets.py
index bc20e840b7c61..8a881e1b30b10 100644
--- a/pandas/tests/tseries/offsets/test_offsets.py
+++ b/pandas/tests/tseries/offsets/test_offsets.py
@@ -102,6 +102,33 @@ def _create_offset(klass, value=1, normalize=False):
     return klass
 
 
+@pytest.fixture(
+    params=[
+        getattr(offsets, o)
+        for o in offsets.__all__
+        if issubclass(getattr(offsets, o), liboffsets.MonthOffset)
+        and o != "MonthOffset"
+    ]
+)
+def month_classes(request):
+    """
+    Fixture for month based datetime offsets available for a time series.
+    """
+    return request.param
+
+
+@pytest.fixture(
+    params=[
+        getattr(offsets, o) for o in offsets.__all__ if o not in ("Tick", "BaseOffset")
+    ]
+)
+def offset_types(request):
+    """
+    Fixture for all the datetime offsets available for a time series.
+    """
+    return request.param
+
+
 @pytest.fixture
 def dt():
     return Timestamp(datetime(2008, 1, 2))