Fixed issue by adding a conversion clause to _cmp_method in string_.py

Author: eicchen

pandas/core/arrays/string_.py

@@ -45,6 +45,7 @@
 from pandas.core.dtypes.common import (
     is_array_like,
     is_bool_dtype,
+    is_float_dtype,
     is_integer_dtype,
     is_object_dtype,
     is_string_dtype,
@@ -1110,10 +1111,24 @@ def _cmp_method(self, other, op):
         if op.__name__ in ops.ARITHMETIC_BINOPS:
             result = np.empty_like(self._ndarray, dtype="object")
             result[mask] = self.dtype.na_value
-            result[valid] = op(self._ndarray[valid], other)
-            if isinstance(other, Path):
-                # GH#61940
-                return result
+            try:
+                result[valid] = op(self._ndarray[valid], other)
+                if isinstance(other, Path):
+                    # GH#61940
+                    return result
+            except TypeError:
+                if is_array_like(other):
+                    if is_float_dtype(other.dtype):
+                        # Shorten whole numbers to be ints to match pyarrow behavior
+                        other = [
+                            str(int(x)) if x.is_integer() else str(x) for x in other
+                        ]
+                    else:
+                        other = other.astype(str)
+                    result[valid] = op(self._ndarray[valid], other)
+                else:
+                    raise
+
             return self._from_backing_data(result)
         else:
             # logical

pandas/tests/arrays/floating/test_arithmetic.py

@@ -144,6 +144,7 @@ def test_error_invalid_values(data, all_arithmetic_operators):
             "not implemented",
             "not supported for dtype",
             "Can only string multiply by an integer",
+            "can't multiply sequence by non-int of type 'str'",
         ]
     )
     with pytest.raises(TypeError, match=msg):

pandas/tests/arrays/string_/test_string.py

@@ -269,9 +269,6 @@ def test_add_frame(dtype):
 
     assert arr.__add__(df) is NotImplemented
 
-    # TODO
-    # pyarrow returns a different dtype despite the values being the same
-    # could be addressed this PR if needed
     result = arr + df
     expected = pd.DataFrame([["ax", np.nan, np.nan, np.nan]]).astype(dtype)
     tm.assert_frame_equal(result, expected, check_dtype=False)
@@ -281,6 +278,19 @@ def test_add_frame(dtype):
     tm.assert_frame_equal(result, expected, check_dtype=False)
 
 
+def test_add_frame_mixed_type(dtype):
+    arr = pd.array(["a", "bc", 3, np.nan], dtype=dtype)
+    df = pd.DataFrame([[1, 2, 3.3, 4]])
+
+    result = arr + df
+    expected = pd.DataFrame([["a1", "bc2", "33.3", np.nan]]).astype(dtype)
+    tm.assert_frame_equal(result, expected, check_dtype=False)
+
+    result = df + arr
+    expected = pd.DataFrame([["1a", "2bc", "3.33", np.nan]]).astype(dtype)
+    tm.assert_frame_equal(result, expected, check_dtype=False)
+
+
 def test_comparison_methods_scalar(comparison_op, dtype):
     op_name = f"__{comparison_op.__name__}__"
     a = pd.array(["a", None, "c"], dtype=dtype)