DOC: add intersphinx mapping for python library, close #1556

Author: lodagro

doc/source/conf.py

@@ -234,7 +234,8 @@
 
 # Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {
-        'statsmodels' : ('http://statsmodels.sourceforge.net/devel/', None)
+        'statsmodels' : ('http://statsmodels.sourceforge.net/devel/', None),
+        'python': ('http://docs.python.org/', None)
                       }
 import glob
 autosummary_generate = glob.glob("*.rst")

doc/source/io.rst

@@ -70,7 +70,7 @@ data into a DataFrame object. They can take a number of arguments:
     cases by "sniffing." The separator may be specified as a regular
     expression; for instance you may use '\s*' to indicate arbitrary
     whitespace.
-  - ``dialect``: string or csv.Dialect instance to expose more ways to specify
+  - ``dialect``: string or :class:`python:csv.Dialect` instance to expose more ways to specify
     the file format
   - ``header``: row number to use as the column names, and the start of the data.
     Defaults to 0 (first row); specify None if there is no header row.
@@ -164,7 +164,7 @@ You can also use a list of columns to create a hierarchical index:
 
 The ``dialect`` keyword gives greater flexibility in specifying the file format.
 By default it uses the Excel dialect but you can specify either the dialect name
-or a `csv.Dialect <docs.python.org/library/csv.html#csv.Dialect>`_ instance.
+or a :class:``python:csv.Dialect`` instance.
 
 .. ipython:: python
    :suppress:
@@ -573,8 +573,8 @@ Automatically "sniffing" the delimiter
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 ``read_csv`` is capable of inferring delimited (not necessarily
-comma-separated) files. YMMV, as pandas uses the Sniffer_ class of the csv
-module.
+comma-separated) files. YMMV, as pandas uses the :class:`python:csv.Sniffer`
+class of the csv module.
 
 .. ipython:: python
    :suppress:
@@ -588,8 +588,6 @@ module.
     print open('tmp2.sv').read()
     read_csv('tmp2.sv')
 
-.. _Sniffer: http://docs.python.org/library/csv.html#csv.Sniffer
-
 .. _io.chunking:
 
 Iterating through files chunk by chunk