BUG-23224 Allow integer_array to be initialized with all None

Author: JustinZhengBC

pandas/core/arrays/integer.py

@@ -174,8 +174,12 @@ def coerce_to_array(values, dtype, mask=None, copy=False):
         inferred_type = infer_dtype(values)
         if inferred_type not in ['floating', 'integer',
                                  'mixed-integer', 'mixed-integer-float']:
-            raise TypeError("{} cannot be converted to an IntegerDtype".format(
-                values.dtype))
+            if inferred_type is 'mixed' and all(isna(x) for x in values):
+                values = np.array([np.nan] * len(values))  # GH 23224
+            else:
+                raise TypeError(
+                    "{} cannot be converted to an IntegerDtype".format(
+                        values.dtype))
 
     elif not (is_integer_dtype(values) or is_float_dtype(values)):
         raise TypeError("{} cannot be converted to an IntegerDtype".format(

pandas/tests/arrays/test_integer.py

@@ -560,6 +560,15 @@ def test_to_integer_array_float():
     assert result.dtype == Int64Dtype()
 
 
+@pytest.mark.parametrize(
+    'result, expected',
+    [
+        (integer_array([None]), integer_array([np.nan])),
+        (integer_array([None, np.nan]), integer_array([np.nan, np.nan]))])
+def test_to_integer_array_none(result, expected):
+    tm.assert_extension_array_equal(result, expected)
+
+
 @pytest.mark.parametrize(
     'values, to_dtype, result_dtype',
     [