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 (GH 428)
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 (GH 437, GH 438). set_value is capable of producing an enlarged object.
Add PyQt table widget to sandbox (GH 435)
DataFrame.align can accept Series arguments and an axis option (GH 461)
Implement new SparseArray and SparseList data structures. SparseSeries now derives from SparseArray (GH 463)
Better console printing options (GH 453)
Implement fast data ranking for Series and DataFrame, fast versions of scipy.stats.rankdata (GH 428)
Implement DataFrame.from_items alternate constructor (GH 444)
DataFrame.convert_objects method for inferring better dtypes for object columns (GH 302)
Add rolling_corr_pairwise function for computing Panel of correlation matrices (GH 189)
Add margins option to pivot_table for computing subgroup aggregates (GH 114)
Add Series.from_csv function (GH 482)
Can pass DataFrame/DataFrame and DataFrame/Series to rolling_corr/rolling_cov (GH #462)
MultiIndex.get_level_values can accept the level name

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)

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