review doc fixes

pandas-dev · Feb 26, 2018 · cd134a8 · cd134a8
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diff --git a/doc/source/categorical.rst b/doc/source/categorical.rst
@@ -185,6 +185,12 @@ are consistent among all columns.
     df_cat['A']
     df_cat['B']
 
+.. note::
+
+    To perform table-wise conversion, where all labels in the entire ``DataFrame`` are used as
+    categories for each column, the ``categories`` parameter can be determined programatically by
+    ``categories = pd.unique(df.values.ravel())``.
+
 If you already have `codes` and `categories`, you can use the 
 :func:`~pandas.Categorical.from_codes` constructor to save the factorize step 
 during normal constructor mode:

diff --git a/doc/source/whatsnew/v0.23.0.txt b/doc/source/whatsnew/v0.23.0.txt
@@ -271,13 +271,14 @@ The :func:`DataFrame.assign` now accepts dependent keyword arguments for python
 
 .. _whatsnew_0230.enhancements.astype_category:
 
-``DataFrame.astype`` performs columnwise conversion to ``Categorical``
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+``DataFrame.astype`` performs column-wise conversion to ``Categorical``
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-:meth:`DataFrame.astype` can now perform columnwise conversion to ``Categorical`` by supplying the string ``'category'`` or a :class:`~pandas.api.types.CategoricalDtype`.
-Previously, attempting this would raise a ``NotImplementedError``. (:issue:`18099`)
+:meth:`DataFrame.astype` can now perform column-wise conversion to ``Categorical`` by supplying the string ``'category'`` or
+a :class:`~pandas.api.types.CategoricalDtype`. Previously, attempting this would raise a ``NotImplementedError``. See the
+:ref:`categorical.objectcreation` section of the documentation for more details and examples. (:issue:`12860`, :issue:`18099`)
 
-Supplying the string ``'category'`` performs columnwise conversion, with only labels appearing in a given column set as categories:
+Supplying the string ``'category'`` performs column-wise conversion, with only labels appearing in a given column set as categories:
 
 .. ipython:: python
 
@@ -298,8 +299,6 @@ Supplying a ``CategoricalDtype`` will make the categories in each column consist
     df['A'].dtype
     df['B'].dtype
 
-See the :ref:`categorical.objectcreation` section of the documentation for more details and examples.
-
 .. _whatsnew_0230.enhancements.other:
 
 Other Enhancements