diff --git a/pandas/tests/arrays/numpy_/__init__.py b/pandas/tests/arrays/numpy_/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/pandas/tests/arrays/numpy_/test_indexing.py b/pandas/tests/arrays/numpy_/test_indexing.py
new file mode 100644
index 0000000000000..f92411efe774c
--- /dev/null
+++ b/pandas/tests/arrays/numpy_/test_indexing.py
@@ -0,0 +1,30 @@
+import numpy as np
+
+from pandas.core.dtypes.common import is_scalar
+
+import pandas as pd
+import pandas._testing as tm
+
+
+class TestSearchsorted:
+    def test_searchsorted_numeric_dtypes_scalar(self, any_real_numpy_dtype):
+        arr = pd.array([1, 3, 90], dtype=any_real_numpy_dtype)
+        result = arr.searchsorted(30)
+        assert is_scalar(result)
+        assert result == 2
+
+        result = arr.searchsorted([30])
+        expected = np.array([2], dtype=np.intp)
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_searchsorted_numeric_dtypes_vector(self, any_real_numpy_dtype):
+        arr = pd.array([1, 3, 90], dtype=any_real_numpy_dtype)
+        result = arr.searchsorted([2, 30])
+        expected = np.array([1, 2], dtype=np.intp)
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_searchsorted_sorter(self, any_real_numpy_dtype):
+        arr = pd.array([3, 1, 2], dtype=any_real_numpy_dtype)
+        result = arr.searchsorted([0, 3], sorter=np.argsort(arr))
+        expected = np.array([0, 2], dtype=np.intp)
+        tm.assert_numpy_array_equal(result, expected)
diff --git a/pandas/tests/arrays/test_numpy.py b/pandas/tests/arrays/numpy_/test_numpy.py
similarity index 100%
rename from pandas/tests/arrays/test_numpy.py
rename to pandas/tests/arrays/numpy_/test_numpy.py
diff --git a/pandas/tests/arrays/string_/test_indexing.py b/pandas/tests/arrays/string_/test_indexing.py
new file mode 100644
index 0000000000000..41466c43288c3
--- /dev/null
+++ b/pandas/tests/arrays/string_/test_indexing.py
@@ -0,0 +1,16 @@
+from pandas.core.dtypes.common import is_scalar
+
+import pandas as pd
+
+
+class TestSearchsorted:
+    def test_searchsorted(self, string_dtype):
+        arr = pd.array(["a", "b", "c"], dtype=string_dtype)
+
+        result = arr.searchsorted("a", side="left")
+        assert is_scalar(result)
+        assert result == 0
+
+        result = arr.searchsorted("a", side="right")
+        assert is_scalar(result)
+        assert result == 1
diff --git a/pandas/tests/arrays/test_array.py b/pandas/tests/arrays/test_array.py
index 329d28c263ff2..3c8d12556bf1c 100644
--- a/pandas/tests/arrays/test_array.py
+++ b/pandas/tests/arrays/test_array.py
@@ -10,7 +10,6 @@
 import pandas as pd
 import pandas._testing as tm
 from pandas.api.extensions import register_extension_dtype
-from pandas.api.types import is_scalar
 from pandas.arrays import (
     BooleanArray,
     DatetimeArray,
@@ -391,61 +390,3 @@ def test_array_not_registered(registry_without_decimal):
     result = pd.array(data, dtype=DecimalDtype)
     expected = DecimalArray._from_sequence(data)
     tm.assert_equal(result, expected)
-
-
-class TestArrayAnalytics:
-    def test_searchsorted(self, string_dtype):
-        arr = pd.array(["a", "b", "c"], dtype=string_dtype)
-
-        result = arr.searchsorted("a", side="left")
-        assert is_scalar(result)
-        assert result == 0
-
-        result = arr.searchsorted("a", side="right")
-        assert is_scalar(result)
-        assert result == 1
-
-    def test_searchsorted_numeric_dtypes_scalar(self, any_real_numpy_dtype):
-        arr = pd.array([1, 3, 90], dtype=any_real_numpy_dtype)
-        result = arr.searchsorted(30)
-        assert is_scalar(result)
-        assert result == 2
-
-        result = arr.searchsorted([30])
-        expected = np.array([2], dtype=np.intp)
-        tm.assert_numpy_array_equal(result, expected)
-
-    def test_searchsorted_numeric_dtypes_vector(self, any_real_numpy_dtype):
-        arr = pd.array([1, 3, 90], dtype=any_real_numpy_dtype)
-        result = arr.searchsorted([2, 30])
-        expected = np.array([1, 2], dtype=np.intp)
-        tm.assert_numpy_array_equal(result, expected)
-
-    @pytest.mark.parametrize(
-        "arr, val",
-        [
-            [
-                pd.date_range("20120101", periods=10, freq="2D"),
-                pd.Timestamp("20120102"),
-            ],
-            [
-                pd.date_range("20120101", periods=10, freq="2D", tz="Asia/Hong_Kong"),
-                pd.Timestamp("20120102", tz="Asia/Hong_Kong"),
-            ],
-            [
-                pd.timedelta_range(start="1 day", end="10 days", periods=10),
-                pd.Timedelta("2 days"),
-            ],
-        ],
-    )
-    def test_search_sorted_datetime64_scalar(self, arr, val):
-        arr = pd.array(arr)
-        result = arr.searchsorted(val)
-        assert is_scalar(result)
-        assert result == 1
-
-    def test_searchsorted_sorter(self, any_real_numpy_dtype):
-        arr = pd.array([3, 1, 2], dtype=any_real_numpy_dtype)
-        result = arr.searchsorted([0, 3], sorter=np.argsort(arr))
-        expected = np.array([0, 2], dtype=np.intp)
-        tm.assert_numpy_array_equal(result, expected)