Version 0.6.1 (December 13, 2011)

New features

  • Can append single rows (as Series) to a DataFrame

  • Add Spearman and Kendall rank correlation options to Series.corr and DataFrame.corr (GH428)

  • Added get_value and set_value methods to Series, DataFrame, and Panel for very low-overhead access (>2x faster in many cases) to scalar elements (GH437, GH438). set_value is capable of producing an enlarged object.

  • Add PyQt table widget to sandbox (GH435)

  • DataFrame.align can accept Series arguments and an axis option (GH461)

  • Implement new SparseArray and SparseList data structures. SparseSeries now derives from SparseArray (GH463)

  • Better console printing options (GH453)

  • Implement fast data ranking for Series and DataFrame, fast versions of scipy.stats.rankdata (GH428)

  • Implement DataFrame.from_items alternate constructor (GH444)

  • DataFrame.convert_objects method for inferring better dtypes for object columns (GH302)

  • Add rolling_corr_pairwise function for computing Panel of correlation matrices (GH189)

  • Add margins option to pivot_table for computing subgroup aggregates (GH114)

  • Add Series.from_csv function (GH482)

  • Can pass DataFrame/DataFrame and DataFrame/Series to rolling_corr/rolling_cov (GH #462)

  • MultiIndex.get_level_values can accept the level name

Performance improvements

  • Improve memory usage of DataFrame.describe (do not copy data unnecessarily) (PR #425)

  • Optimize scalar value lookups in the general case by 25% or more in Series and DataFrame

  • Fix performance regression in cross-sectional count in DataFrame, affecting DataFrame.dropna speed

  • Column deletion in DataFrame copies no data (computes views on blocks) (GH #158)

Contributors

For contributors, please see /usr/share/doc/contributors_list.txt or https://github.com/pandas-dev/pandas/graphs/contributors