# v.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
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