BUG: Raise ValueError for non numerical join columns in merge_asof

doc/source/whatsnew/v1.1.0.rst

@@ -957,6 +957,7 @@ Reshaping
 - Bug in :func:`cut` raised an error when non-unique labels (:issue:`33141`)
 - Ensure only named functions can be used in :func:`eval()` (:issue:`32460`)
 - Fixed bug in :func:`melt` where melting MultiIndex columns with ``col_level`` > 0 would raise a ``KeyError`` on ``id_vars`` (:issue:`34129`)
+- :meth:`merge_asof` raises ``ValueError`` instead of cryptic ``TypeError`` in case of non-numerical merge columns (:issue:`29130`)
 
 Sparse
 ^^^^^^

pandas/core/reshape/merge.py

@@ -1637,9 +1637,11 @@ def _get_merge_keys(self):
 
         # note this function has side effects
         (left_join_keys, right_join_keys, join_names) = super()._get_merge_keys()
+        len_by_cols = 0 if self.left_by is None else len(self.left_by)
 
         # validate index types are the same
         for i, (lk, rk) in enumerate(zip(left_join_keys, right_join_keys)):
+
             if not is_dtype_equal(lk.dtype, rk.dtype):
                 if is_categorical_dtype(lk.dtype) and is_categorical_dtype(rk.dtype):
                     # The generic error message is confusing for categoricals.
@@ -1661,6 +1663,13 @@ def _get_merge_keys(self):
                     )
                 raise MergeError(msg)
 
+            if i >= len_by_cols:
+                if is_object_dtype(rk.dtype) or is_object_dtype(lk.dtype):
+                    raise ValueError(
+                        f"Incompatible merge [{i}] dtype, {repr(lk.dtype)} and "
+                        f"{repr(rk.dtype)}, both sides must have numeric dtype"
+                    )
+
         # validate tolerance; datetime.timedelta or Timedelta if we have a DTI
         if self.tolerance is not None:
 

pandas/tests/reshape/merge/test_merge_asof.py

@@ -1339,3 +1339,35 @@ def test_merge_index_column_tz(self):
             index=pd.Index([0, 1, 2, 3, 4]),
         )
         tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "data",
+    [["2019-06-01 00:09:12", "2019-06-01 00:10:29"], [1.0, "2019-06-01 00:10:29"]],
+)
+def test_non_numerical_dtype(data):
+    # GH 29130
+    left = pd.DataFrame({"x": data})
+    right = pd.DataFrame({"x": data})
+    with pytest.raises(
+        ValueError,
+        match=r"Incompatible merge \[0\] dtype, .*, both sides must have numeric dtype",
+    ):
+        pd.merge_asof(left, right, on="x")
+
+
+def test_some_issues():
+    left = pd.DataFrame({"a": ["12", "13", "15"], "left_val1": ["a", "b", "c"]})
+    right = pd.DataFrame({"a": ["a", "b", "c"], "left_val": ["d", "e", "f"]})
+    with pytest.raises(
+        ValueError,
+        match=r"Incompatible merge \[1\] dtype, .*, both sides must have numeric dtype",
+    ):
+        pd.merge_asof(
+            left,
+            right,
+            left_on="left_val1",
+            right_on="a",
+            left_by="a",
+            right_by="left_val",
+        )