.. _whatsnew_0152:

v0.15.2 (December ??, 2014)
---------------------------

This is a minor release from 0.15.1 and includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug fixes. We recommend that all
users upgrade to this version.

- Highlights include:

- :ref:`Enhancements <whatsnew_0152.enhancements>`
- :ref:`API Changes <whatsnew_0152.api>`
- :ref:`Performance Improvements <whatsnew_0152.performance>`
- :ref:`Experimental Changes <whatsnew_0152.experimental>`
- :ref:`Bug Fixes <whatsnew_0152.bug_fixes>`

.. _whatsnew_0152.api:

API changes
~~~~~~~~~~~

- Bug in concat of Series with ``category`` dtype which were coercing to ``object``. (:issue:`8641`)

- ``Series.all`` and ``Series.any`` now support the ``level`` and ``skipna`` parameters. ``Series.all``, ``Series.any``, ``Index.all``, and ``Index.any`` no longer support the ``out`` and ``keepdims`` parameters, which existed for compatibility with ndarray. Various index types no longer support the ``all`` and ``any`` aggregation functions and will now raise ``TypeError``. (:issue:`8302`):

  .. ipython:: python

     s = pd.Series([False, True, False], index=[0, 0, 1])
     s.any(level=0)

- ``Panel`` now supports the ``all`` and ``any`` aggregation functions. (:issue:`8302`):

  .. ipython:: python

     p = pd.Panel(np.random.rand(2, 5, 4) > 0.1)
     p.all()

.. _whatsnew_0152.enhancements:

Enhancements
~~~~~~~~~~~~

- Added ability to export Categorical data to Stata (:issue:`8633`).  See :ref:`here <io.stata-categorical>` for limitations of categorical variables exported to Stata data files.
- Added ability to export Categorical data to to/from HDF5 (:issue:`7621`). Queries work the same as if it was an object array. However, the ``category`` dtyped data is stored in a more efficient manner. See :ref:`here <io.hdf5-categorical>` for an example and caveats w.r.t. prior versions of pandas.
- Added support for ``utcfromtimestamp()``, ``fromtimestamp()``, and ``combine()`` on `Timestamp` class (:issue:`5351`).
- Added Google Analytics (`pandas.io.ga`) basic documentation (:issue:`8835`). See :ref:`here<remote_data.ga>`.
- Added flag ``order_categoricals`` to ``StataReader`` and ``read_stata`` to select whether to order imported categorical data (:issue:`8836`).  See :ref:`here <io.stata-categorical>` for more information on importing categorical variables from Stata data files.

.. _whatsnew_0152.performance:

Performance
~~~~~~~~~~~

.. _whatsnew_0152.experimental:

Experimental
~~~~~~~~~~~~


.. _whatsnew_0152.bug_fixes:

Bug Fixes
~~~~~~~~~
- Bug in packaging pandas with ``py2app/cx_Freeze`` (:issue:`8602`, :issue:`8831`)
- Bug in ``groupby`` signatures that didn't include \*args or \*\*kwargs (:issue:`8733`).
- ``io.data.Options`` now raises ``RemoteDataError`` when no expiry dates are available from Yahoo and when it receives no data from Yahoo (:issue:`8761`), (:issue:`8783`).
- Unclear error message in csv parsing when passing dtype and names and the parsed data is a different data type (:issue:`8833`)
- Bug in slicing a multi-index with an empty list and at least one boolean indexer (:issue:`8781`)
- ``io.data.Options`` now raises ``RemoteDataError`` when no expiry dates are available from Yahoo (:issue:`8761`).
- ``Timedelta`` kwargs may now be numpy ints and floats (:issue:`8757`).
- ``sql_schema`` now generates dialect appropriate ``CREATE TABLE`` statements (:issue:`8697`)
- ``slice`` string method now takes step into account (:issue:`8754`)
- Bug in ``BlockManager`` where setting values with different type would break block integrity (:issue:`8850`)
- Fix negative step support for label-based slices (:issue:`8753`)

  Old behavior:

  .. code-block:: python

     In [1]: s = pd.Series(np.arange(3), ['a', 'b', 'c'])
     Out[1]:
     a    0
     b    1
     c    2
     dtype: int64

     In [2]: s.loc['c':'a':-1]
     Out[2]:
     c    2
     dtype: int64

  New behavior:

  .. ipython:: python

     s = pd.Series(np.arange(3), ['a', 'b', 'c'])
     s.loc['c':'a':-1]


- Imported categorical variables from Stata files retain the ordinal information in the underlying data (:issue:`8836`).



- Defined ``.size`` attribute across ``NDFrame`` objects to provide compat with numpy >= 1.9.1; buggy with ``np.array_split`` (:issue:`8846`)


- Skip testing of histogram plots for matplotlib <= 1.2 (:issue:`8648`).






- Bug where ``get_data_google``returned object dtypes (:issue:`3995`)










- Bug in `pd.infer_freq`/`DataFrame.inferred_freq` that prevented proper sub-daily frequency inference
  when the index contained DST days (:issue:`8772`).
- Bug where index name was still used when plotting a series with ``use_index=False`` (:issue:`8558`).

- Bugs when trying to stack multiple columns, when some (or all)
  of the level names are numbers (:issue:`8584`).
