diff --git a/pandas/core/missing.py b/pandas/core/missing.py
index cc783a88c8482..e83a0518d97f6 100644
--- a/pandas/core/missing.py
+++ b/pandas/core/missing.py
@@ -39,8 +39,6 @@ def mask_missing(arr, values_to_mask):
             # numpy elementwise comparison warning
             if is_numeric_v_string_like(arr, x):
                 mask = False
-            # elif is_object_dtype(arr):
-            #     mask = lib.scalar_compare(arr, x, operator.eq)
             else:
                 mask = arr == x
 
@@ -53,8 +51,6 @@ def mask_missing(arr, values_to_mask):
             # numpy elementwise comparison warning
             if is_numeric_v_string_like(arr, x):
                 mask |= False
-            # elif is_object_dtype(arr):
-            #     mask |= lib.scalar_compare(arr, x, operator.eq)
             else:
                 mask |= arr == x
 
diff --git a/pandas/types/cast.py b/pandas/types/cast.py
index cd3f3a2bf5a96..518b0dad98df5 100644
--- a/pandas/types/cast.py
+++ b/pandas/types/cast.py
@@ -350,9 +350,6 @@ def _infer_dtype_from_scalar(val, pandas_dtype=False):
         else:
             if pandas_dtype:
                 dtype = DatetimeTZDtype(unit='ns', tz=val.tz)
-                # ToDo: This localization is not needed if
-                # DatetimeTZBlock doesn't localize internal values
-                val = val.tz_localize(None)
             else:
                 # return datetimetz as object
                 return np.object_, val
@@ -381,9 +378,7 @@ def _infer_dtype_from_scalar(val, pandas_dtype=False):
         dtype = np.complex_
 
     elif pandas_dtype:
-        # to do use util
-        from pandas.tseries.period import Period
-        if isinstance(val, Period):
+        if lib.is_period(val):
             dtype = PeriodDtype(freq=val.freq)
             val = val.ordinal