[SciPy-User] [ANN] patsy version 0.2.0 released

[Nathaniel Smith]

Hi all,

I've just released version 0.2.0 of patsy, a Python library for
describing statistical models (especially linear models, or models
that have a linear component) and
building design matrices. Patsy brings the convenience of R "formulas"
to Python.

-- New in this release

(for more details: https://patsy.readthedocs.org/en/latest/changes.html#v0-2-0)

New support for automatically detecting and (optionally) removing
missing values.

New stateful transform for B-spline regression: bs(). (Requires scipy.)

Added a core API to make it possible to run predictions on only a
subset of model terms. (This is particularly useful for e.g. plotting
the isolated effect of a single fitted spline term.) See
DesignMatrixBuilder.subset().

LookupFactor now allows users to mark variables as categorical directly.

pandas.Categorical objects are now recognized as representing
categorical data and handled appropriately.

Better error reporting for exceptions raised by user code inside
formulas. We now, whenever possible, tag the generated exception with
information about which factor’s code raised it, and use this
information to give better error reporting.

EvalEnvironment.capture() now takes a reference argument, to make it
easier to implement new dmatrix()-like functions.

Miscellaneous doc improvements and bug fixes.

-- General information

Documentation:
  http://patsy.readthedocs.org/

Downloads:
  http://pypi.python.org/pypi/patsy/

Dependencies:
  numpy
  Python 2.5 or later (Python 3 works)

Optional dependencies:
  nose: needed to run tests
  scipy: needed for spline-related functions like 'bs'

Install:
  pip install patsy
    or
  python setup.py install

Code and bug tracker:
  https://github.com/pydata/patsy

Mailing list:
  pydata at googlegroups.com
  http://groups.google.com/group/pydata
  http://news.gmane.org/gmane.comp.python.pydata

License:
  2-clause BSD, see LICENSE.txt for details.

Share and enjoy,
-n