- The lowest officially supported Python version is now 2.5. So far as
I know everything still works with Python 2.4, but as everyone else
has continued to drop support for 2.4, testing on 2.4 has become so
much trouble that I’ve given up.
- New support for automatically detecting and (optionally) removing
missing values (see NAAction).
- 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.)
- LookupFactor now allows users to mark variables as
- 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.
Other: miscellaneous doc improvements and bug fixes.