Updated according to comments

Author: tp

doc/source/basics.rst

@@ -251,8 +251,8 @@ replace NaN with some other value using ``fillna`` if you wish).
 Flexible Comparisons
 ~~~~~~~~~~~~~~~~~~~~
 
-Note that Series and DataFrame have the binary comparison methods eq, ne, lt, gt,
-le, and ge whose behavior is analogous to the binary
+Series and DataFrame have the binary comparison methods ``eq``, ``ne``, ``lt``, ``gt``,
+``le``, and ``ge`` whose behavior is analogous to the binary
 arithmetic operations described above:
 
 .. ipython:: python

doc/source/dsintro.rst

@@ -698,7 +698,7 @@ DataFrame in tabular form, though it won't always fit the console width:
 
    print(baseball.iloc[-20:, :12].to_string())
 
-Note that wide DataFrames will be printed across multiple rows by
+Wide DataFrames will be printed across multiple rows by
 default:
 
 .. ipython:: python
@@ -845,11 +845,9 @@ DataFrame objects with mixed-type columns, all of the data will get upcasted to
 
 .. note::
 
-   Unfortunately Panel, being less commonly used than Series and DataFrame,
+   Panel, being less commonly used than Series and DataFrame,
    has been slightly neglected feature-wise. A number of methods and options
-   available in DataFrame are not available in Panel. This will get worked
-   on, of course, in future releases. And faster if you join me in working on
-   the codebase.
+   available in DataFrame are not available in Panel.
 
 .. _dsintro.to_panel:
 

doc/source/groupby.rst

@@ -140,7 +140,7 @@ columns:
 
     In [5]: grouped = df.groupby(get_letter_type, axis=1)
 
-Note that pandas Index objects support duplicate values. If a
+pandas Index objects support duplicate values. If a
 non-unique index is used as the group key in a groupby operation, all values
 for the same index value will be considered to be in one group and thus the
 output of aggregation functions will only contain unique index values:

doc/source/io.rst

@@ -3878,7 +3878,7 @@ create a new table!)
 Iterator
 ++++++++
 
-Note that you can pass ``iterator=True`` or ``chunksize=number_in_a_chunk``
+You can pass ``iterator=True`` or ``chunksize=number_in_a_chunk``
 to ``select`` and ``select_as_multiple`` to return an iterator on the results.
 The default is 50,000 rows returned in a chunk.
 
@@ -4419,44 +4419,6 @@ Now you can import the ``DataFrame`` into R:
    starting point if you have stored multiple ``DataFrame`` objects to a
    single HDF5 file.
 
-Backwards Compatibility
-'''''''''''''''''''''''
-
-0.10.1 of ``HDFStore`` can read tables created in a prior version of pandas,
-however query terms using the
-prior (undocumented) methodology are unsupported. ``HDFStore`` will
-issue a warning if you try to use a legacy-format file. You must
-read in the entire file and write it out using the new format, using the
-method ``copy`` to take advantage of the updates. The group attribute
-``pandas_version`` contains the version information. ``copy`` takes a
-number of options, please see the docstring.
-
-
-.. ipython:: python
-   :suppress:
-
-   import os
-   legacy_file_path = os.path.abspath('source/_static/legacy_0.10.h5')
-
-.. ipython:: python
-   :okwarning:
-
-   # a legacy store
-   legacy_store = pd.HDFStore(legacy_file_path,'r')
-   legacy_store
-
-   # copy (and return the new handle)
-   new_store = legacy_store.copy('store_new.h5')
-   new_store
-   new_store.close()
-
-.. ipython:: python
-   :suppress:
-
-   legacy_store.close()
-   import os
-   os.remove('store_new.h5')
-
 
 Performance
 '''''''''''