fix isin method for series

doc/source/whatsnew/v2.1.0.rst

@@ -409,9 +409,9 @@ Other
 - Bug in :func:`assert_almost_equal` now throwing assertion error for two unequal sets (:issue:`51727`)
 - Bug in :func:`assert_frame_equal` checks category dtypes even when asked not to check index type (:issue:`52126`)
 - Bug in :meth:`DataFrame.reindex` with a ``fill_value`` that should be inferred with a :class:`ExtensionDtype` incorrectly inferring ``object`` dtype (:issue:`52586`)
+- Bug in :meth:`Series.isin` when ``values`` is of type ``Dataframe`` throw a ``TypeError`` (:issue:`43460`)
 - Bug in :meth:`Series.map` when giving a callable to an empty series, the returned series had ``object`` dtype. It now keeps the original dtype (:issue:`52384`)
 - Bug in :meth:`Series.memory_usage` when ``deep=True`` throw an error with Series of objects and the returned value is incorrect, as it does not take into account GC corrections (:issue:`51858`)
--
 
 .. ***DO NOT USE THIS SECTION***
 

pandas/core/algorithms.py

@@ -63,6 +63,7 @@
     PandasDtype,
 )
 from pandas.core.dtypes.generic import (
+    ABCDataFrame,
     ABCDatetimeArray,
     ABCExtensionArray,
     ABCIndex,
@@ -465,6 +466,12 @@ def isin(comps: AnyArrayLike, values: AnyArrayLike) -> npt.NDArray[np.bool_]:
             f"to isin(), you passed a [{type(values).__name__}]"
         )
 
+    if isinstance(values, ABCDataFrame):
+        raise TypeError(
+            "only list-like objects are allowed to be passed "
+            f"to isin(), you passed a [{type(values).__name__}]"
+        )
+
     if not isinstance(values, (ABCIndex, ABCSeries, ABCExtensionArray, np.ndarray)):
         orig_values = list(values)
         values = _ensure_arraylike(orig_values)

pandas/core/series.py

@@ -5050,7 +5050,7 @@ def isin(self, values) -> Series:
         Raises
         ------
         TypeError
-          * If `values` is a string
+          * If `values` is a string or a dataframe
 
         See Also
         --------

pandas/io/formats/style.py

@@ -2687,7 +2687,9 @@ def _get_numeric_subset_default(self):
         # Returns a boolean mask indicating where `self.data` has numerical columns.
         # Choosing a mask as opposed to the column names also works for
         # boolean column labels (GH47838).
-        return self.data.columns.isin(self.data.select_dtypes(include=np.number))
+        return self.data.columns.isin(
+            self.data.select_dtypes(include=np.number).columns
+        )
 
     @doc(
         name="background",

pandas/tests/test_algos.py

@@ -876,14 +876,16 @@ class TestIsin:
     def test_invalid(self):
         msg = (
             r"only list-like objects are allowed to be passed to isin\(\), "
-            r"you passed a \[int\]"
+            r"you passed a"
         )
-        with pytest.raises(TypeError, match=msg):
+        with pytest.raises(TypeError, match=f"{msg} \\[int\\]"):
             algos.isin(1, 1)
-        with pytest.raises(TypeError, match=msg):
+        with pytest.raises(TypeError, match=f"{msg} \\[int\\]"):
             algos.isin(1, [1])
-        with pytest.raises(TypeError, match=msg):
+        with pytest.raises(TypeError, match=f"{msg} \\[int\\]"):
             algos.isin([1], 1)
+        with pytest.raises(TypeError, match=f"{msg} \\[DataFrame\\]"):
+            algos.isin([1], DataFrame({"Column": [1]}))
 
     def test_basic(self):
         result = algos.isin([1, 2], [1])