Bug: Fix Inconsistent Behavior for Series.searchsorted

doc/source/whatsnew/v2.0.0.rst

@@ -740,6 +740,8 @@ Metadata
 
 Other
 ^^^^^
+- Bug in :meth:`Series.searchsorted` inconsistent behavior when accepting :class:`DataFrame` as parameter ``value`` (:issue:`49620`)
+-
 
 .. ***DO NOT USE THIS SECTION***
 

pandas/core/base.py

@@ -1270,6 +1270,13 @@ def searchsorted(
         sorter: NumpySorter = None,
     ) -> npt.NDArray[np.intp] | np.intp:
 
+        if isinstance(value, ABCDataFrame):
+            msg = (
+                "Value must be array-like or scalar, "
+                f"{type(value).__name__} is not supported"
+            )
+            raise ValueError(msg)
+
         values = self._values
         if not isinstance(values, np.ndarray):
             # Going through EA.searchsorted directly improves performance GH#38083

pandas/tests/series/methods/test_searchsorted.py

@@ -1,5 +1,7 @@
 import numpy as np
+import pytest
 
+import pandas as pd
 from pandas import (
     Series,
     Timestamp,
@@ -65,3 +67,10 @@ def test_searchsorted_sorter(self):
         res = ser.searchsorted([0, 3], sorter=np.argsort(ser))
         exp = np.array([0, 2], dtype=np.intp)
         tm.assert_numpy_array_equal(res, exp)
+
+    def test_searchsorted_Dataframe_fail(self):
+        ser = Series([1, 2, 3, 4, 5])
+        vals = pd.DataFrame([[1, 2], [3, 4]])
+        msg = "Value must be array-like or scalar, DataFrame is not supported"
+        with pytest.raises(ValueError, match=msg):
+            ser.searchsorted(vals)