allowing eval between numerical values and PintArray

pint_pandas/pint_array.py

@@ -196,7 +196,26 @@ def __repr__(self):
         return self.name
 
     def _get_common_dtype(self, dtypes):
-        if all(isinstance(x, PintType) for x in dtypes):
+        """return the common dtype from list provided.
+
+        If this function is called this means at least on of the ``dtypes``
+        list is a ``PintType``
+
+        In order to be able to be able to perform operation on ``PintType``
+        with scalars, mix of ``PintType`` and numeric values are allowed.
+
+
+        Parameters
+        ----------
+        dtypes (list): list of dtypes in which common is requested
+
+        Returns
+        -------
+        returns self for acceptable cases or None otherwise
+        """
+        if all(
+            isinstance(x, PintType) or pd.api.types.is_numeric_dtype(x) for x in dtypes
+        ):
             return self
         else:
             return None

pint_pandas/testsuite/test_issues.py

@@ -275,6 +275,8 @@ def test_eval(self):
             {
                 "a": pd.Series([1.0, 2.0, 3.0], dtype="pint[meter]"),
                 "b": pd.Series([4.0, 5.0, 6.0], dtype="pint[second]"),
+                "c": [1.0, 2.0, 3.0],
             }
         )
         tm.assert_series_equal(df.eval("a / b"), df["a"] / df["b"])
+        tm.assert_series_equal(df.eval("a / c"), df["a"] / df["c"])