TST: io/pytables.py tests now raise NotImplementedError for dtype==category

Author: jreback

pandas/io/pytables.py

@@ -1773,6 +1773,9 @@ def set_atom(self, block, block_items, existing_col, min_itemsize,
             raise TypeError(
                 "[unicode] is not implemented as a table column")
 
+        elif dtype == 'category':
+            raise NotImplementedError
+
         # this is basically a catchall; if say a datetime64 has nans then will
         # end up here ###
         elif inferred_type == 'string' or dtype == 'object':

pandas/io/tests/test_pytables.py

@@ -4349,25 +4349,28 @@ def test_query_with_nested_special_character(self):
         tm.assert_frame_equal(expected, result)
 
     def test_categorical(self):
-        try:
+        # FIXME
+
+        with ensure_clean_store(self.path) as store:
+
             s = Series(Categorical(['a', 'b', 'b', 'a', 'a', 'c'], levels=['a','b','c','d']))
-            # FIXME: AttributeError: 'Categorical' object has no attribute 'T'
-            s.to_hdf(self.path, "cat_series_alone")
-            s2 = read_hdf(self.path, "cat_series_alone")
-            tm.assert_series_equal(s, s2)
+
+            self.assertRaises(NotImplementedError, store.append, 's', s, format='table')
+            #store.append('s', s, format='table')
+            #result = store.select('s')
+            #tm.assert_series_equal(s, result)
+
             df = DataFrame({"s":s, "vals":[1,2,3,4,5,6]})
-            df.to_hdf(self.path, "cat_frame_alone")
-            df2 = read_hdf(self.path, "cat_frame_alone")
-            tm.assert_frame_equal(df, df2)
+            self.assertRaises(NotImplementedError, store.append, 'df', df, format='table')
+            #store.append('df', df, format='table')
+            #result = store.select('df')
+            #tm.assert_frame_equal(df, df2)
+
             # Ok, this doesn't work yet
             # FIXME: TypeError: cannot pass a where specification when reading from a Fixed format store. this store must be selected in its entirety
-            #result = read_hdf(hdf_file, "frame_alone", where = ['index>2'])
+            #result = store.select('df', where = ['index>2'])
             #tm.assert_frame_equal(df[df.index>2],result)
 
-        finally:
-            safe_remove(self.path)
-
-
 def _test_sort(obj):
     if isinstance(obj, DataFrame):
         return obj.reindex(sorted(obj.index))