diff --git a/doc/source/getting_started/install.rst b/doc/source/getting_started/install.rst
index b5c512cdc8328..25b499a46ffaf 100644
--- a/doc/source/getting_started/install.rst
+++ b/doc/source/getting_started/install.rst
@@ -146,7 +146,6 @@ Installing using your Linux distribution's package manager.
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 The commands in this table will install pandas for Python 3 from your distribution.
-To install pandas for Python 2, you may need to use the ``python-pandas`` package.
 
 .. csv-table::
     :header: "Distribution", "Status", "Download / Repository Link", "Install method"
diff --git a/doc/source/user_guide/enhancingperf.rst b/doc/source/user_guide/enhancingperf.rst
index 2df5b9d82dcc3..22ef4ccd6f07f 100644
--- a/doc/source/user_guide/enhancingperf.rst
+++ b/doc/source/user_guide/enhancingperf.rst
@@ -78,11 +78,6 @@ four calls) using the `prun ipython magic function <http://ipython.org/ipython-d
 By far the majority of time is spend inside either ``integrate_f`` or ``f``,
 hence we'll concentrate our efforts cythonizing these two functions.
 
-.. note::
-
-  In Python 2 replacing the ``range`` with its generator counterpart (``xrange``)
-  would mean the ``range`` line would vanish. In Python 3 ``range`` is already a generator.
-
 .. _enhancingperf.plain:
 
 Plain Cython
diff --git a/doc/source/user_guide/io.rst b/doc/source/user_guide/io.rst
index d0780e4ab8dba..22bf34c40abc5 100644
--- a/doc/source/user_guide/io.rst
+++ b/doc/source/user_guide/io.rst
@@ -41,8 +41,7 @@ The pandas I/O API is a set of top level ``reader`` functions accessed like
 
 .. note::
    For examples that use the ``StringIO`` class, make sure you import it
-   according to your Python version, i.e. ``from StringIO import StringIO`` for
-   Python 2 and ``from io import StringIO`` for Python 3.
+   with ``from io import StringIO`` for Python 3.
 
 .. _io.read_csv_table:
 
@@ -912,16 +911,6 @@ data columns:
    significantly faster, ~20x has been observed.
 
 
-.. note::
-
-   When passing a dict as the `parse_dates` argument, the order of
-   the columns prepended is not guaranteed, because `dict` objects do not impose
-   an ordering on their keys. On Python 2.7+ you may use `collections.OrderedDict`
-   instead of a regular `dict` if this matters to you. Because of this, when using a
-   dict for 'parse_dates' in conjunction with the `index_col` argument, it's best to
-   specify `index_col` as a column label rather then as an index on the resulting frame.
-
-
 Date parsing functions
 ++++++++++++++++++++++
 
@@ -2453,7 +2442,7 @@ Specify a number of rows to skip:
 
    dfs = pd.read_html(url, skiprows=0)
 
-Specify a number of rows to skip using a list (``xrange`` (Python 2 only) works
+Specify a number of rows to skip using a list (``range`` works
 as well):
 
 .. code-block:: python
@@ -3124,11 +3113,7 @@ Pandas supports writing Excel files to buffer-like objects such as ``StringIO``
 
 .. code-block:: python
 
-   # Safe import for either Python 2.x or 3.x
-   try:
-       from io import BytesIO
-   except ImportError:
-       from cStringIO import StringIO as BytesIO
+   from io import BytesIO
 
    bio = BytesIO()