BUG: issue in HDFStore with too many selectors in a where

RELEASE.rst

@@ -22,6 +22,12 @@ Where to get it
 * Binary installers on PyPI: http://pypi.python.org/pypi/pandas
 * Documentation: http://pandas.pydata.org
 
+  ``HDFStore``
+
+    - Fix weird PyTables error when using too many selectors in a where
+    - Provide dotted attribute access to ``get`` from stores (e.g. store.df == store['df'])
+    - Internally, change all variables to be private-like (now have leading underscore)
+
 pandas 0.10.1
 =============
 

doc/source/io.rst

@@ -1021,6 +1021,9 @@ In a current or later Python session, you can retrieve stored objects:
    # store.get('df') is an equivalent method
    store['df']
 
+   # dotted (attribute) access provides get as well
+   store.df
+
 Deletion of the object specified by the key
 
 .. ipython:: python
@@ -1363,6 +1366,32 @@ Notes & Caveats
 	# we have provided a minimum minor_axis indexable size
 	store.root.wp_big_strings.table
 
+DataTypes
+~~~~~~~~~
+
+``HDFStore`` will map an object dtype to the ``PyTables`` underlying dtype. This means the following types are known to work:
+
+    - floating : ``float64, float32, float16`` *(using* ``np.nan`` *to represent invalid values)*
+    - integer : ``int64, int32, int8, uint64, uint32, uint8``
+    - bool
+    - datetime64[ns] *(using* ``NaT`` *to represent invalid values)*
+    - object : ``strings`` *(using*  ``np.nan`` *to represent invalid values)*
+
+Currently, ``unicode`` and ``datetime`` columns (represented with a dtype of ``object``), **WILL FAIL**. In addition, even though a column may look like a ``datetime64[ns]``,
+if it contains ``np.nan``, this **WILL FAIL**. You can try to convert datetimelike columns to proper ``datetime64[ns]`` columns, that possibily contain ``NaT`` to represent invalid values. (Some of these issues have been addressed and these conversion may not be necessary in future versions of pandas)
+
+    .. ipython:: python
+
+       import datetime
+       df = DataFrame(dict(datelike = Series([datetime.datetime(2001,1,1),datetime.datetime(2001,1,2),np.nan])))
+       df
+       df.dtypes
+
+       # to convert
+       df['datelike'] = Series(df['datelike'].values,dtype='M8[ns]')
+       df
+       df.dtypes
+
 External Compatibility
 ~~~~~~~~~~~~~~~~~~~~~~
 

doc/source/v0.10.2.txt

@@ -0,0 +1,18 @@
+.. _whatsnew_0102:
+
+v0.10.2 (February ??, 2013)
+---------------------------
+
+This is a minor release from 0.10.1 and includes many new features and
+enhancements along with a large number of bug fixes. There are also a number of
+important API changes that long-time pandas users should pay close attention
+to.
+
+**Enhancements**
+
+  - In ``HDFStore``, provide dotted attribute access to ``get`` from stores (e.g. store.df == store['df'])
+
+See the `full release notes
+<https://github.com/pydata/pandas/blob/master/RELEASE.rst>`__ or issue tracker
+on GitHub for a complete list.
+

doc/source/whatsnew.rst

@@ -16,6 +16,8 @@ What's New
 
 These are new features and improvements of note in each release.
 
+.. include:: v0.10.2.txt
+
 .. include:: v0.10.1.txt
 
 .. include:: v0.10.0.txt