review suggestions

src/nested_pandas/series/dtype.py

@@ -28,7 +28,7 @@ class NestedDtype(ExtensionDtype):
     """Attributes to use as metadata for __eq__ and __hash__"""
 
     @property
-    def na_value(self) -> pd.NA:
+    def na_value(self) -> Type[pd.NA]:
         """The missing value for this dtype"""
         return pd.NA
 

src/nested_pandas/series/ext_array.py

@@ -161,13 +161,6 @@ def to_numpy(self, dtype: None = None, copy: bool = False, na_value: Any = no_de
         # Hack with np.empty is the only way to force numpy to create 1-d array of objects
         result = np.empty(shape=array.shape, dtype=object)
 
-        # TODO: delete block once confirmed NA is better to return
-        # fill NaNs - Fill with an empty dictionary using the same columns
-        # nan_vals = pd.isna(array)
-        # if sum(nan_vals) > 0:
-        #    na_idx = np.where(nan_vals)
-        #    array[na_idx] = {key: [] for key in array[np.where(~nan_vals)[0][0]].keys()}
-
         # We do copy=False here because user's 'copy' is already handled by ArrowExtensionArray.to_numpy
         result[:] = [pd.DataFrame(value, copy=False) if not pd.isna(value) else pd.NA for value in array]
         return result