(GH30841) • Bug in Index constructor incorrectly allowing 2-dimensional input arrays (GH13601, GH27125) 1.10 Contributors A total of 303 people contributed patches to this release. People with a “+” by their Arıbal + • Andreas Buhr + • Andrew Munch + • Andy • Angela Ambroz + • Aniruddha Bhattacharjee + 1.10. Contributors 33 pandas: powerful Python data analysis toolkit, Release 1.0.0 • Ankit Dhankhar + Lustig • Isaac Virshup + • Ivan Bessarabov + • JMBurley + • Jack Bicknell + • Jacob Buckheit + 1.10. Contributors 35 pandas: powerful Python data analysis toolkit, Release 1.0.0 • Jan Koch • Jan

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 stack(0).reset_index(1) In [71]: df Out[71]: level_1 X Y row 0 One 1.10 1.20 0 Two 1.11 1.22 1 One 1.10 1.20 1 Two 1.11 1.22 2 One 1.10 1.20 2 Two 1.11 1.22 # And fix the labels (Notice the label 'level_1'

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 toolkit, Release 1.3.3 (continued from previous page) row 0 One 1.10 1.20 0 Two 1.11 1.22 1 One 1.10 1.20 1 Two 1.11 1.22 2 One 1.10 1.20 2 Two 1.11 1.22 # And fix the labels (Notice the label 'level_1'

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 toolkit, Release 1.3.4 (continued from previous page) row 0 One 1.10 1.20 0 Two 1.11 1.22 1 One 1.10 1.20 1 Two 1.11 1.22 2 One 1.10 1.20 2 Two 1.11 1.22 # And fix the labels (Notice the label 'level_1'

Cookbook. A handy pandas cheat sheet. 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 stack(0).reset_index(1) In [71]: df Out[71]: level_1 X Y row 0 One 1.10 1.20 0 Two 1.11 1.22 1 One 1.10 1.20 1 Two 1.11 1.22 2 One 1.10 1.20 2 Two 1.11 1.22 (continues on next page) 2.22. Cookbook

Cookbook. A handy pandas cheat sheet. 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 stack(0).reset_index(1) In [71]: df Out[71]: level_1 X Y row 0 One 1.10 1.20 0 Two 1.11 1.22 1 One 1.10 1.20 1 Two 1.11 1.22 2 One 1.10 1.20 2 Two 1.11 1.22 (continues on next page) 870 Chapter 2.

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 stack(0).reset_index(1) In [71]: df Out[71]: level_1 X Y row 0 One 1.10 1.20 0 Two 1.11 1.22 1 One 1.10 1.20 1 Two 1.11 1.22 2 One 1.10 1.20 2 Two 1.11 1.22 (continues on next page) 890 Chapter 2.

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 stack(0).reset_index(1) In [71]: df Out[71]: level_1 X Y row 0 One 1.10 1.20 0 Two 1.11 1.22 1 One 1.10 1.20 1 Two 1.11 1.22 2 One 1.10 1.20 2 Two 1.11 1.22 (continues on next page) 890 Chapter 2.

Cookbook. A handy pandas cheat sheet. 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 stack(0).reset_index(1) In [71]: df Out[71]: level_1 X Y row 0 One 1.10 1.20 0 Two 1.11 1.22 1 One 1.10 1.20 1 Two 1.11 1.22 2 One 1.10 1.20 2 Two 1.11 1.22 (continues on next page) 872 Chapter 3.

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 toolkit, Release 1.4.2 (continued from previous page) row 0 One 1.10 1.20 0 Two 1.11 1.22 1 One 1.10 1.20 1 Two 1.11 1.22 2 One 1.10 1.20 2 Two 1.11 1.22 # And fix the labels (Notice the label 'level_1'