.. _whatsnew_0801:

v0.8.1 (July 22, 2012)
----------------------

This release includes a few new features, performance enhancements, and over 30
bug fixes from 0.8.0.  New features include notably NA friendly string
processing functionality and a series of new plot types and options.

New features
~~~~~~~~~~~~

  - Add `vectorized string processing methods <basics.string_methods>`__
    accessible via Series.str (GH620_)
  - Add option to disable adjustment in EWMA (GH1584_)
  - `Radviz plot <visualization.radviz>`__ (GH1566_)
  - `Parallel coordinates plot <visualization.parallel_coordinates>`__
  - `Bootstrap plot <visualization.bootstrap>`__
  - Per column styles and secondary y-axis plotting (GH1559_)
  - New datetime converters millisecond plotting  (GH1599_)
  - Add option to disable "sparse" display of hierarchical indexes (GH1538_)
  - Series/DataFrame's ``set_index`` method can `append levels
    <indexing.set_index>`__ to an existing Index/MultiIndex (GH1569_, GH1577_)

Performance improvements
~~~~~~~~~~~~~~~~~~~~~~~~

  - Improved implementation of rolling min and max (thanks to `Bottleneck
    <http://berkeleyanalytics.com/bottleneck/>`__ !)
  - Add accelerated ``'median'`` GroupBy option (GH1358_)
  - Significantly improve the performance of parsing ISO8601-format date
    strings with ``DatetimeIndex`` or ``to_datetime`` (GH1571_)
  - Improve the performance of GroupBy on single-key aggregations and use with
    Categorical types
  - Significant datetime parsing performance improvments

.. _GH620: https://github.com/pydata/pandas/issues/620
.. _GH1358: https://github.com/pydata/pandas/issues/1358
.. _GH1538: https://github.com/pydata/pandas/issues/1538
.. _GH1559: https://github.com/pydata/pandas/issues/1559
.. _GH1584: https://github.com/pydata/pandas/issues/1584
.. _GH1566: https://github.com/pydata/pandas/issues/1566
.. _GH1569: https://github.com/pydata/pandas/issues/1569
.. _GH1571: https://github.com/pydata/pandas/issues/1571
.. _GH1577: https://github.com/pydata/pandas/issues/1577
.. _GH1599: https://github.com/pydata/pandas/issues/1599
