Version 0.6.0 (November 25, 2011)#
New features#
- Added - meltfunction to- pandas.core.reshape
- Added - levelparameter to group by level in Series and DataFrame descriptive statistics (GH313)
- Added - headand- tailmethods to Series, analogous to DataFrame (GH296)
- Added - Series.isinfunction which checks if each value is contained in a passed sequence (GH289)
- Added - float_formatoption to- Series.to_string
- Added - skip_footer(GH291) and- converters(GH343) options to- read_csvand- read_table
- Added - drop_duplicatesand- duplicatedfunctions for removing duplicate DataFrame rows and checking for duplicate rows, respectively (GH319)
- Implemented operators ‘&’, ‘|’, ‘^’, ‘-’ on DataFrame (GH347) 
- Added - Series.mad, mean absolute deviation
- Added - orientoption to- DataFrame.from_dict
- Added passing list of tuples or list of lists to - DataFrame.from_records(GH357)
- Allow multiple columns in - byargument of- DataFrame.sort_index(GH92, GH362)
- Added fast - get_valueand- put_valuemethods to DataFrame (GH360)
- Added - covinstance methods to Series and DataFrame (GH194, GH362)
- Added - read_clipboardfunction to parse DataFrame from clipboard (GH300)
- Added - nuniquefunction to Series for counting unique elements (GH297)
- Made DataFrame constructor use Series name if no columns passed (GH373) 
- Added - DataFrame.to_htmlfor writing DataFrame to HTML (GH387)
- Added support for MaskedArray data in DataFrame, masked values converted to NaN (GH396) 
- Added - rawoption to- DataFrame.applyfor performance if only need ndarray (GH309)
- Added proper, tested weighted least squares to standard and panel OLS (GH303) 
Performance enhancements#
- VBENCH Cythonized - cache_readonly, resulting in substantial micro-performance enhancements throughout the code base (GH361)
- VBENCH Special Cython matrix iterator for applying arbitrary reduction operations with 3-5x better performance than - np.apply_along_axis(GH309)
- VBENCH Improved performance of - MultiIndex.from_tuples
- VBENCH Special Cython matrix iterator for applying arbitrary reduction operations 
- VBENCH + DOCUMENT Add - rawoption to- DataFrame.applyfor getting better performance when
- VBENCH Faster cythonized count by level in Series and DataFrame (GH341) 
- VBENCH? Significant GroupBy performance enhancement with multiple keys with many “empty” combinations 
- VBENCH New Cython vectorized function - map_inferspeeds up- Series.applyand- Series.mapsignificantly when passed elementwise Python function, motivated by (GH355)
- VBENCH Significantly improved performance of - Series.order, which also makes np.unique called on a Series faster (GH327)
- VBENCH Vastly improved performance of GroupBy on axes with a MultiIndex (GH299) 
Contributors#
A total of 8 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.
- Adam Klein + 
- Chang She + 
- Dieter Vandenbussche 
- Jeff Hammerbacher + 
- Nathan Pinger + 
- Thomas Kluyver 
- Wes McKinney 
- Wouter Overmeire +