statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 6.5 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . from a level (GH159) 1.1.2 Performance improvements • Use khash for Series.value_counts, add raw function to algorithms.py (GH861) • Intercept __builtin__.sum in groupby (GH885) 1.2 v.0.7.1 (February pandas: powerful Python data analysis toolkit, Release 0.7.2 1.2.1 New features • Add to_clipboard function to pandas namespace for writing objects to the system clipboard (GH774) • Add itertuples method

statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 6.5 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . few new features and addresses over a dozen bugs in 0.7.0. 1.1.1 New features • Add to_clipboard function to pandas namespace for writing objects to the system clipboard (#774) • Add itertuples method obtain a DataFrame (#787) 1.2 v.0.7.0 (February 9, 2012) 1.2.1 New features • New unified merge function for efficiently performing full gamut of database / relational-algebra operations. Refactored existing

statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 6.5 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . complete list. 1.1.1 New features • New fixed width file reader, read_fwf • New scatter_matrix function for making a scatter plot matrix from pandas.tools.plotting import scatter_matrix scatter_matrix(df from a level (GH159) 1.2.2 Performance improvements • Use khash for Series.value_counts, add raw function to algorithms.py (GH861) • Intercept __builtin__.sum in groupby (GH885) 1.3 v.0.7.1 (February

statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 9.6 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a’) with no complaints from pandas about am- biguity of the name a. – The top-level pandas.eval() function does not allow you use the ’@’ prefix and provides you with an error message telling you so. – ensure that the name attribute of the original series is propagated to the result (GH6265). – If the function provided to GroupBy.apply returns a named series, the name of the series will be kept as the name

statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 9.6 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . compare if two NDFrames are equal have equal axes, dtypes, and values. Added the array_equivalent function to compare if two ndarrays are equal. NaNs in identical locations are treated as equal. (GH5283) columns, or the function being applied would be called with an empty Series to guess whether a Series or DataFrame should be returned: In [31]: def applied_func(col): ....: print "Apply function being called

statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 8.6 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 • Implement __nonzero__ for NDFrame objects (GH3691, GH3696) • IO api – added top-level function read_excel to replace the following, The original API is deprecated and will be removed in a future pd.read_excel(’path_to_file.xls’, ’Sheet1’, index_col=None, na_values=[’NA’]) – added top-level function read_sql that is equivalent to the following from pandas.io.sql import read_frame read_frame(.

statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 2.3.6 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 2.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 972 2.26.3 Mutating with User Defined Function (UDF) methods . . . . . . . . . . . . . . . . . . . . . 974 2.26.4 NaN, Integer NA values and NA operator functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1414 3.3.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1415 3.3.7

statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 2.3.6 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 2.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 973 2.26.3 Mutating with User Defined Function (UDF) methods . . . . . . . . . . . . . . . . . . . . . 975 2.26.4 NaN, Integer NA values and NA operator functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1414 3.3.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1415 3.3.7

statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 2.3.6 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212 2.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 932 2.26.3 Mutating with User Defined Function (UDF) methods . . . . . . . . . . . . . . . . . . . . . 934 2.26.4 NaN, Integer NA values and NA operator functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1361 3.3.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1362 3.3.7

statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 2.3.6 Function application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 2.3 operator functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1252 3.3.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1253 3.3.7 operator functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1745 3.4.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1747 vi 3