avoid invalid dtype comparision warning

Author: jreback

pandas/_libs/index.pyx

@@ -535,8 +535,8 @@ cpdef convert_scalar(ndarray arr, object value):
             return Timedelta(value).value
         raise ValueError("cannot set a Timedelta with a non-timedelta")
 
-    if (issubclass(arr.dtype.type, (np.integer, np.floating, np.complex)) and not
-            issubclass(arr.dtype.type, np.bool_)):
+    if (issubclass(arr.dtype.type, (np.integer, np.floating, np.complex)) and
+            not issubclass(arr.dtype.type, np.bool_)):
         if util.is_bool_object(value):
             raise ValueError('Cannot assign bool to float/integer series')
 

pandas/core/internals.py

@@ -4940,11 +4940,18 @@ def _putmask_smart(v, m, n):
 
         # avoid invalid dtype comparisons
         if not is_numeric_v_string_like(nn, nn_at):
-            comp = (nn == nn_at)
-            if is_list_like(comp) and comp.all():
-                nv = v.copy()
-                nv[m] = nn_at
-                return nv
+
+            # only compare integers/floats
+            # don't compare integers to datetimelikes
+            if (is_float_dtype(nn.dtype) or
+                    is_integer_dtype(nn.dtype) and
+                    is_float_dtype(nn_at.dtype) or
+                    is_integer_dtype(nn_at.dtype)):
+                comp = (nn == nn_at)
+                if is_list_like(comp) and comp.all():
+                    nv = v.copy()
+                    nv[m] = nn_at
+                    return nv
     except (ValueError, IndexError, TypeError):
         pass