v.0.6.0 (November 25, 2011)

New Features

  • Added melt function to pandas.core.reshape
  • Added level parameter to group by level in Series and DataFrame descriptive statistics (GH313)
  • Added head and tail methods to Series, analogous to to DataFrame (GH296)
  • Added Series.isin function which checks if each value is contained in a passed sequence (GH289)
  • Added float_format option to Series.to_string
  • Added skip_footer (GH291) and converters (GH343) options to read_csv and read_table
  • Added drop_duplicates and duplicated functions for removing duplicate DataFrame rows and checking for duplicate rows, respectively (GH319)
  • Implemented operators ‘&’, ‘|’, ‘^’, ‘-‘ on DataFrame (GH347)
  • Added Series.mad, mean absolute deviation
  • Added QuarterEnd DateOffset (GH321)
  • Added dot to DataFrame (GH65)
  • Added orient option to Panel.from_dict (GH359, GH301)
  • Added orient option to DataFrame.from_dict
  • Added passing list of tuples or list of lists to DataFrame.from_records (GH357)
  • Added multiple levels to groupby (GH103)
  • Allow multiple columns in by argument of DataFrame.sort_index (GH92, GH362)
  • Added fast get_value and put_value methods to DataFrame (GH360)
  • Added cov instance methods to Series and DataFrame (GH194, GH362)
  • Added kind='bar' option to DataFrame.plot (GH348)
  • Added idxmin and idxmax to Series and DataFrame (GH286)
  • Added read_clipboard function to parse DataFrame from clipboard (GH300)
  • Added nunique function to Series for counting unique elements (GH297)
  • Made DataFrame constructor use Series name if no columns passed (GH373)
  • Support regular expressions in read_table/read_csv (GH364)
  • Added DataFrame.to_html for writing DataFrame to HTML (GH387)
  • Added support for MaskedArray data in DataFrame, masked values converted to NaN (GH396)
  • Added DataFrame.boxplot function (GH368)
  • Can pass extra args, kwds to DataFrame.apply (GH376)
  • Implement DataFrame.join with vector on argument (GH312)
  • Added legend boolean flag to DataFrame.plot (GH324)
  • Can pass multiple levels to stack and unstack (GH370)
  • Can pass multiple values columns to pivot_table (GH381)
  • Use Series name in GroupBy for result index (GH363)
  • Added raw option to DataFrame.apply for 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 raw option to DataFrame.apply for 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_infer speeds up Series.apply and Series.map significantly 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

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