along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time 2.1 Selection Choices Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis strategies 9.1 Choice Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis

empty Series now return NaN instead of 0, see here. • Compatibility fixes for pypy, see here. • Additions to the drop, reindex and rename API to make them more consistent, see here. • Addition of the new along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time 24.1 Selection Choices Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis

along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time 13.1 Selection Choices Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis to use them: • ENH: Enhancement, new functionality • BUG: Bug fix • DOC: Additions/updates to documentation • TST: Additions/updates to tests • BLD: Updates to the build process/scripts 238 Chapter

along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time Dependencies Selection Choices Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis to use them: • ENH: Enhancement, new functionality • BUG: Bug fix • DOC: Additions/updates to documentation • TST: Additions/updates to tests • BLD: Updates to the build process/scripts • PERF: Performance

along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time Dependencies Selection Choices Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis to use them: • ENH: Enhancement, new functionality • BUG: Bug fix • DOC: Additions/updates to documentation • TST: Additions/updates to tests • BLD: Updates to the build process/scripts • PERF: Performance

along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time 22.1 Selection Choices Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis to use them: • ENH: Enhancement, new functionality • BUG: Bug fix • DOC: Additions/updates to documentation • TST: Additions/updates to tests • BLD: Updates to the build process/scripts • PERF: Performance

along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time 21.1 Selection Choices Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis to use them: • ENH: Enhancement, new functionality • BUG: Bug fix • DOC: Additions/updates to documentation • TST: Additions/updates to tests • BLD: Updates to the build process/scripts • PERF: Performance

along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time 9.1 Selection Choices Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis Choices for Indexing New in version 0.11.0. Object selection has had a number of user-requested additions in order to support more explicit location based indexing. pandas now supports three types of multi-axis

along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time 8.1 Selection Choices Starting in 0.11.0, object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis Choices for Indexing New in version 0.11.0. Object selection has had a number of user-requested additions in order to support more explicit location based indexing. pandas now supports three types of multi-axis

0.0 3.2.1 Different choices for indexing Object selection has had a number of user-requested additions in order to support more explicit location based index- ing. Pandas now supports three types of ‘strongly agree’ vs ‘agree’ or ‘first observation’ vs. ‘second observation’), but numerical operations (additions, divisions, ...) are not possible. All values of categorical data are either in categories or np statistical categorical variables, a Categorical might have an order, but numerical operations (additions, divisions, ...) are not possible. All values of the Categorical are either in categories or np