Chapter 1. What’s New pandas: powerful Python data analysis toolkit, Release 0.7.3 • Add log x and y scaling options to DataFrame.plot and Series.plot • Add kurt methods to Series and DataFrame for computing item access to Panel and add IPython completion (PR563) • Add logy option to Series.plot for log-scaling on the Y axis • Add index and header options to DataFrame.to_string • Can pass multiple DataFrames vertical bar plot barh : horizontal bar plot logy : boolean, default False For line plots, use log scaling on y axis xticks : sequence Values to use for the xticks yticks : sequence Values to use for

Python data analysis toolkit, Release 0.15.2 df.plot(kind=’barh’, stacked=True) • Add log x and y scaling options to DataFrame.plot and Series.plot • Add kurt methods to Series and DataFrame for computing item access to Panel and add IPython completion (GH563) • Add logy option to Series.plot for log-scaling on the Y axis • Add index and header options to DataFrame.to_string • Can pass multiple DataFrames logx : boolean, default False Use log scaling on x axis logy : boolean, default False Use log scaling on y axis loglog : boolean, default False Use log scaling on both x and y axes xticks : sequence

Python data analysis toolkit, Release 0.15.1 df.plot(kind=’barh’, stacked=True) • Add log x and y scaling options to DataFrame.plot and Series.plot • Add kurt methods to Series and DataFrame for computing item access to Panel and add IPython completion (GH563) • Add logy option to Series.plot for log-scaling on the Y axis • Add index and header options to DataFrame.to_string • Can pass multiple DataFrames logx : boolean, default False Use log scaling on x axis logy : boolean, default False Use log scaling on y axis loglog : boolean, default False Use log scaling on both x and y axes xticks : sequence

Python data analysis toolkit, Release 0.14.0 df.plot(kind=’barh’, stacked=True) • Add log x and y scaling options to DataFrame.plot and Series.plot • Add kurt methods to Series and DataFrame for computing item access to Panel and add IPython completion (GH563) • Add logy option to Series.plot for log-scaling on the Y axis • Add index and header options to DataFrame.to_string • Can pass multiple DataFrames logx : boolean, default False Use log scaling on x axis logy : boolean, default False Use log scaling on y axis loglog : boolean, default False Use log scaling on both x and y axes secondary_y : boolean

(April 12, 2012) 51 pandas: powerful Python data analysis toolkit, Release 0.12.0 • Add log x and y scaling options to DataFrame.plot and Series.plot • Add kurt methods to Series and DataFrame for computing item access to Panel and add IPython completion (GH563) • Add logy option to Series.plot for log-scaling on the Y axis • Add index and header options to DataFrame.to_string • Can pass multiple DataFrames legend : logx : boolean, default False For line plots, use log scaling on x axis logy : boolean, default False For line plots, use log scaling on y axis secondary_y : boolean or sequence of ints, default

Python data analysis toolkit, Release 0.13.1 df.plot(kind=’barh’, stacked=True) • Add log x and y scaling options to DataFrame.plot and Series.plot • Add kurt methods to Series and DataFrame for computing item access to Panel and add IPython completion (GH563) • Add logy option to Series.plot for log-scaling on the Y axis • Add index and header options to DataFrame.to_string • Can pass multiple DataFrames legend logx : boolean, default False For line plots, use log scaling on x axis logy : boolean, default False For line plots, use log scaling on y axis secondary_y : boolean or sequence of ints, default

default NA values for read_csv() (GH30821) 1.5.15 Documentation Improvements • Added new section on Scaling to large datasets (GH28315). • Added sub-section on Query MultiIndex for HDF5 datasets (GH28791) This is done by inferring the result type of an expression from its arguments and operators. 3.19 Scaling to large datasets Pandas provides data structures for in-memory analytics, which makes using pandas pandas operations need to make intermediate copies. This document provides a few recommendations for scaling your analysis to larger datasets. It’s a complement to enhancingperf, which focuses on speeding up

Python data analysis toolkit, Release 0.17.0 df.plot(kind='barh', stacked=True) • Add log x and y scaling options to DataFrame.plot and Series.plot • Add kurt methods to Series and DataFrame for computing item access to Panel and add IPython completion (GH563) • Add logy option to Series.plot for log-scaling on the Y axis • Add index and header options to DataFrame.to_string • Can pass multiple DataFrames logx : boolean, default False Use log scaling on x axis logy : boolean, default False Use log scaling on y axis loglog : boolean, default False Use log scaling on both x and y axes xticks : sequence

Expression evaluation via eval() . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 829 2.19 Scaling to large datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . This is done by inferring the result type of an expression from its arguments and operators. 2.19 Scaling to large datasets Pandas provides data structures for in-memory analytics, which makes using pandas pandas operations need to make intermediate copies. This document provides a few recommendations for scaling your analysis to larger datasets. It’s a complement to Enhancing performance, which focuses on speeding

Expression evaluation via eval() . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 843 2.22 Scaling to large datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . This is done by inferring the result type of an expression from its arguments and operators. 2.22 Scaling to large datasets Pandas provides data structures for in-memory analytics, which makes using pandas pandas operations need to make intermediate copies. This document provides a few recommendations for scaling your analysis to larger datasets. It’s a complement to Enhancing performance, which focuses on speeding