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Merge PR #2755
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wesm committed Feb 10, 2013
2 parents 0033f0a + 7065ff0 commit 1511d3f
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6 changes: 6 additions & 0 deletions RELEASE.rst
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Expand Up @@ -81,6 +81,12 @@ pandas 0.11.0
- Fix some boolean indexing inconsistencies in Series __getitem__/__setitem__
(GH2776_)

``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)

.. _GH622: https://github.com/pydata/pandas/issues/622
.. _GH797: https://github.com/pydata/pandas/issues/797
.. _GH2778: https://github.com/pydata/pandas/issues/2778
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29 changes: 29 additions & 0 deletions doc/source/io.rst
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Expand Up @@ -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
Expand Down Expand Up @@ -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
~~~~~~~~~~~~~~~~~~~~~~

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18 changes: 18 additions & 0 deletions doc/source/v0.10.2.txt
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.. _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.

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