diff --git a/doc/source/api.rst b/doc/source/api.rst
index 2e59bf6533205..fea8b95bb2bcf 100644
--- a/doc/source/api.rst
+++ b/doc/source/api.rst
@@ -38,9 +38,8 @@ Pickling
    load
    save
 
-File IO
-~~~~~~~
-
+Flat File IO
+^^^^^^^^^^^^
 .. currentmodule:: pandas.io.parsers
 
 .. autosummary::
@@ -62,9 +61,13 @@ File IO
    :toctree: generated/
 
    read_stata
+   read_fwf
+   read_clipboard
 
 .. currentmodule:: pandas.io.html
 
+HTML IO
+^^^^^^^
 .. autosummary::
    :toctree: generated/
 
@@ -80,6 +83,46 @@ SQL
 
    read_sql
 
+Excel IO
+^^^^^^^^
+.. currentmodule:: pandas.io.parsers
+
+.. autosummary::
+   :toctree: generated/
+
+   ExcelFile.parse
+
+SQL IO
+^^^^^^
+.. currentmodule:: pandas.io.sql
+
+.. autosummary::
+   :toctree: generated/
+
+   read_frame
+   write_frame
+
+.. currentmodule:: pandas.io
+
+.. autosummary::
+   :toctree: generated/
+
+   sql
+
+STATA IO
+^^^^^^^^
+.. currentmodule:: pandas.io.stata
+
+.. autosummary::
+   :toctree: generated/
+
+   read_stata
+   StataReader.data
+   StataReader.data_label
+   StataReader.value_labels
+   StataReader.variable_labels
+   StataWriter.write_file
+
 HDFStore: PyTables (HDF5)
 ~~~~~~~~~~~~~~~~~~~~~~~~~
 
@@ -94,6 +137,17 @@ HDFStore: PyTables (HDF5)
    HDFStore.get
    HDFStore.select
 
+Top-level Missing Data
+~~~~~~~~~~~~~~~~~~~~~~
+
+.. currentmodule:: pandas.core.common
+
+.. autosummary::
+   :toctree: generated/
+
+   isnull
+   notnull
+
 Standard moving window functions
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
diff --git a/doc/source/io.rst b/doc/source/io.rst
index 5bf3075f2688e..a8d5cf4ab2f60 100644
--- a/doc/source/io.rst
+++ b/doc/source/io.rst
@@ -667,9 +667,9 @@ should pass the ``escapechar`` option:
 
 Files with Fixed Width Columns
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-While `read_csv` reads delimited data, the :func:`~pandas.io.parsers.read_fwf`
+While ``read_csv`` reads delimited data, the :func:`~pandas.io.parsers.read_fwf`
 function works with data files that have known and fixed column widths.
-The function parameters to `read_fwf` are largely the same as `read_csv` with
+The function parameters to ``read_fwf`` are largely the same as `read_csv` with
 two extra parameters:
 
   - ``colspecs``: a list of pairs (tuples), giving the extents of the
@@ -2123,23 +2123,30 @@ Writing to STATA format
 
 .. _io.StataWriter:
 
-The method ``to_stata`` will write a DataFrame into a .dta file. 
+The method :func:`~pandas.io.stata.StataWriter.write_file` of
+:class:`~pandas.io.stata.StataWriter` will write a DataFrame into a .dta file.
 The format version of this file is always the latest one, 115.
 
 .. ipython:: python
 
-   df = DataFrame(randn(10,2),columns=list('AB'))
-   df.to_stata('stata.dta')
+   from pandas.io.stata import StataWriter
+   df = DataFrame(randn(10, 2), columns=list('AB'))
+   writer = StataWriter('stata.dta', df)
+   writer.write_file()
 
 Reading from STATA format
 ~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. _io.StataReader:
+.. _io.statareader:
 
 .. versionadded:: 0.11.1
 
 The top-level function ``read_stata`` will read a dta format file
 and return a DataFrame:
+The class :class:`~pandas.io.stata.StataReader` will read the header of the
+given dta file at initialization. Its method
+:func:`~pandas.io.stata.StataReader.data` will read the observations,
+converting them to a DataFrame which is returned:
 
 .. ipython:: python
 
@@ -2153,6 +2160,7 @@ also be retrieved by the function ``variable_labels``, which requires data to be
 called before (see ``pandas.io.stata.StataReader``).
 
 The StataReader supports .dta Formats 104, 105, 108, 113-115.
+Alternatively, the function :func:`~pandas.io.stata.read_stata` can be used
 
 .. ipython:: python
    :suppress:
diff --git a/pandas/core/common.py b/pandas/core/common.py
index ee8b3bbbda647..994a57247e50b 100644
--- a/pandas/core/common.py
+++ b/pandas/core/common.py
@@ -48,17 +48,19 @@ class AmbiguousIndexError(PandasError, KeyError):
 _INT64_DTYPE = np.dtype(np.int64)
 
 def isnull(obj):
-    '''
-    Detect missing values (NaN in numeric arrays, None/NaN in object arrays)
+    """Detect missing values (NaN in numeric arrays, None/NaN in object arrays)
 
     Parameters
     ----------
-    arr: ndarray or object value
+    arr : ndarray or object value
+        Object to check for null-ness
 
     Returns
     -------
-    boolean ndarray or boolean
-    '''
+    isnulled : array-like of bool or bool
+        Array or bool indicating whether an object is null or if an array is
+        given which of the element is null.
+    """
     return _isnull(obj)
 
 
@@ -187,18 +189,20 @@ def _isnull_ndarraylike_old(obj):
 
 
 def notnull(obj):
-    '''
-    Replacement for numpy.isfinite / -numpy.isnan which is suitable
-    for use on object arrays.
+    """Replacement for numpy.isfinite / -numpy.isnan which is suitable for use
+    on object arrays.
 
     Parameters
     ----------
-    arr: ndarray or object value
+    arr : ndarray or object value
+        Object to check for *not*-null-ness
 
     Returns
     -------
-    boolean ndarray or boolean
-    '''
+    isnulled : array-like of bool or bool
+        Array or bool indicating whether an object is *not* null or if an array
+        is given which of the element is *not* null.
+    """
     res = isnull(obj)
     if np.isscalar(res):
         return not res
diff --git a/pandas/io/__init__.py b/pandas/io/__init__.py
index e69de29bb2d1d..a984c40cdc098 100644
--- a/pandas/io/__init__.py
+++ b/pandas/io/__init__.py
@@ -0,0 +1,2 @@
+import sql
+import stata