release if necessary. See the full release notes or issue tracker on GitHub for a complete list. 1.11.1 Support for non-unique indexes All objects can now work with non-unique indexes. Data alignment Pandas More complex recipes are in the Cookbook 6.2 Pandas Cookbook The goal of this cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas. These are examples with McNamara • John W. O’Brien • Jonathan Chambers • Joris Van den Bossche • jreback • jsexauer • Julia Evans • Júlio • Katie Atkinson • kdiether • Kelsey Jordahl • Kevin Sheppard • K.-Michael Aye

12, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 1.11.1 New features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . New features – Pipe – Other Enhancements • API Changes • Performance Improvements • Bug Fixes 1.11.1 New features 1.11.1.1 Pipe We’ve introduced a new method DataFrame.pipe(). As suggested by the pandas More complex recipes are in the Cookbook 6.2 pandas Cookbook The goal of this cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas. These are examples with

11, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 1.11.1 Enhancements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . data will be removed in favor of a separately installable package. See here for details (GH8961) 1.11.1 Enhancements 1.11.1.1 CategoricalIndex We introduce a CategoricalIndex, a new type of index object pandas More complex recipes are in the Cookbook 6.2 pandas Cookbook The goal of this cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas. These are examples with

A handy pandas cheat sheet. 3.6.2 Community guides pandas Cookbook by Julia Evans The goal of this 2015 cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas

(November 21, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 1.11.1 New features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Formatting • Enhancements • API changes – Deprecations • Performance Improvements • Bug Fixes 1.11.1 New features 1.11.1.1 Conditional HTML Formatting Warning: This is a new feature and is under active pandas More complex recipes are in the Cookbook 6.2 pandas Cookbook The goal of this cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas. These are examples with

also a number of important API changes that long-time pandas users should pay close attention to. 1.11.1 File parsing new features The delimited file parsing engine (the guts of read_csv and read_table) pandas More complex recipes are in the Cookbook 6.2 pandas Cookbook The goal of this cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas. These are examples with McNamara • John W. O’Brien • Jonathan Chambers • Joris Van den Bossche • jreback • jsexauer • Julia Evans • Júlio • Katie Atkinson • kdiether • Kelsey Jordahl • Kevin Sheppard • K.-Michael Aye

rank method, masking functions for DataFrame, and intraday time-series filtering for DataFrame. 1.11.1 New features • Series.sort, DataFrame.sort, and DataFrame.sort_index can now be specified in a per-column pandas More complex recipes are in the Cookbook 6.2 pandas Cookbook The goal of this cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas. These are examples with McNamara • John W. O’Brien • Jonathan Chambers • Joris Van den Bossche • jreback • jsexauer • Julia Evans 1462 Chapter 35. Release Notes pandas: powerful Python data analysis toolkit, Release 0.15

Jonathan Larkin + • Joris Van den Bossche • Josh Dimarsky + • Joshua Smith + • Josiah Baker + • Julia Signell + • Jung Dong Ho + • Justin Cole + • Justin Zheng • Kaiqi Dong • Karthigeyan + • Katherine A handy pandas cheat sheet. 2.7.2 Community guides pandas Cookbook by Julia Evans The goal of this 2015 cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas operations, pd.NA follows the rules of the three-valued logic (or Kleene logic, similarly to R, SQL and Julia). This logic means to only propagate missing values when it is logically required. For example, for

should be a transparent change with only very limited API implications. See Internal Refactoring 1.11.1 API changes • read_excel now supports an integer in its sheetname argument giving the index of the pandas More complex recipes are in the Cookbook 7.2 pandas Cookbook The goal of this cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas. These are examples with McNamara • John W. O’Brien • Jonathan Chambers • Joris Van den Bossche • jreback • jsexauer • Julia Evans • Júlio • Katie Atkinson • kdiether • Kelsey Jordahl • Kevin Sheppard • K.-Michael Aye

tutorials by the community, geared mainly for new users. pandas cookbook by Julia Evans The goal of this 2015 cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas operations, pd.NA follows the rules of the three-valued logic (or Kleene logic, similarly to R, SQL and Julia). This logic means to only propagate missing values when it is logically required. For example, for Joris Van den Bossche • Jose • JoseNavy • Josh Dimarsky • Josh Friedlander • Joshua Klein + • Julia Signell • Julian Schnitzler + • Kaiqi Dong • Kasim Panjri + • Katie Smith + • Kelly + • Kenil