fixup! ENH: Parametrized CategoricalDtype

Author: TomAugspurger

doc/source/categorical.rst

@@ -95,15 +95,15 @@ Anywhere above we passed a keyword ``dtype='category'``, we used the default beh
 2. categories are unordered.
 
 To control those behaviors, instead of passing ``'category'``, use an instance
-of :class:`~pd.api.types.CategoricalDtype`.
+of :class:`~pandas.api.types.CategoricalDtype`.
 
 .. ipython:: python
 
     from pandas.api.types import CategoricalDtype
 
     s = pd.Series(["a", "b", "c", "a"])
     cat_type = CategoricalDtype(categories=["b", "c", "d"],
-                                ordered=False)
+                                ordered=True)
     s_cat = s.astype(cat_type)
     s_cat
 
@@ -181,9 +181,9 @@ array. In other words, ``dtype='category'`` is equivalent to
 Equality Semantics
 ~~~~~~~~~~~~~~~~~~
 
-Two instances of :class:`~pandas.api.types.CategoricalDtype` compare equal whenever the have
-the same categories and orderedness. When comparing two unordered categoricals, the
-order of the ``categories`` is not considered
+Two instances of :class:`~pandas.api.types.CategoricalDtype` compare equal
+whenever they have the same categories and orderedness. When comparing two
+unordered categoricals, the order of the ``categories`` is not considered
 
 .. ipython:: python
 

doc/source/whatsnew/v0.21.0.txt

@@ -112,7 +112,7 @@ e.g., when converting string data to a ``Categorical``:
 The ``.dtype`` property of a ``Categorical``, ``CategoricalIndex`` or a
 ``Series`` with categorical type will now return an instance of ``CategoricalDtype``.
 
-See :ref:`CategoricalDtype <categorical.categoricaldtype>` for more.
+See the :ref:`CategoricalDtype docs <categorical.categoricaldtype>` for more.
 
 .. _whatsnew_0210.enhancements.other:
 

pandas/core/dtypes/dtypes.py

@@ -130,7 +130,6 @@ class CategoricalDtype(ExtensionDtype):
     Examples
     --------
     >>> t = CategoricalDtype(categories=['b', 'a'], ordered=True)
-    >>> s = Series(['a', 'a', 'b', 'b', 'a'], dtype=t)
     >>> pd.Series(['a', 'b', 'a', 'c'], dtype=t)
     0      a
     1      b
@@ -205,7 +204,7 @@ def __eq__(self, other):
             return hash(self) == hash(other)
 
     def __unicode__(self):
-        tpl = u'CategoricalDtype({}ordered={})'
+        tpl = u'CategoricalDtype(categories={}ordered={})'
         if self.categories is None:
             data = u"None, "
         else: