BUG/TST (string dtype): raise proper TypeError in interpolate

pandas/core/arrays/arrow/array.py

@@ -2160,7 +2160,7 @@ def interpolate(
         """
         # NB: we return type(self) even if copy=False
         if not self.dtype._is_numeric:
-            raise ValueError("Values must be numeric.")
+            raise TypeError(f"Cannot interpolate with {self.dtype} dtype")
 
         if (
             not pa_version_under13p0

pandas/core/arrays/numpy_.py

@@ -287,6 +287,9 @@ def interpolate(
         See NDFrame.interpolate.__doc__.
         """
         # NB: we return type(self) even if copy=False
+        if not self.dtype._is_numeric:
+            raise TypeError(f"Cannot interpolate with {self.dtype} dtype")
+
         if not copy:
             out_data = self._ndarray
         else:

pandas/tests/extension/test_arrow.py

@@ -3451,7 +3451,9 @@ def test_string_to_datetime_parsing_cast():
 )
 def test_interpolate_not_numeric(data):
     if not data.dtype._is_numeric:
-        with pytest.raises(ValueError, match="Values must be numeric."):
+        ser = pd.Series(data)
+        msg = re.escape(f"Cannot interpolate with {ser.dtype} dtype")
+        with pytest.raises(TypeError, match=msg):
             pd.Series(data).interpolate()
 
 

pandas/tests/frame/methods/test_interpolate.py

@@ -64,11 +64,7 @@ def test_interpolate_inplace(self, frame_or_series, request):
         assert np.shares_memory(orig, obj.values)
         assert orig.squeeze()[1] == 1.5
 
-    # TODO(infer_string) raise proper TypeError in case of string dtype
-    @pytest.mark.xfail(
-        using_string_dtype(), reason="interpolate doesn't work for string"
-    )
-    def test_interp_basic(self):
+    def test_interp_basic(self, using_infer_string):
         df = DataFrame(
             {
                 "A": [1, 2, np.nan, 4],
@@ -77,7 +73,8 @@ def test_interp_basic(self):
                 "D": list("abcd"),
             }
         )
-        msg = "DataFrame cannot interpolate with object dtype"
+        dtype = "str" if using_infer_string else "object"
+        msg = f"[Cc]annot interpolate with {dtype} dtype"
         with pytest.raises(TypeError, match=msg):
             df.interpolate()
 
@@ -88,7 +85,8 @@ def test_interp_basic(self):
 
         # check we DID operate inplace
         assert np.shares_memory(df["C"]._values, cvalues)
-        assert np.shares_memory(df["D"]._values, dvalues)
+        if not using_infer_string:
+            assert np.shares_memory(df["D"]._values, dvalues)
 
     @pytest.mark.xfail(
         using_string_dtype(), reason="interpolate doesn't work for string"