major release from 0.7.3 and includes extensive work on the time series handling and processing infrastructure as well as a great deal of new functionality throughout the library. It includes over 700 commits of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) • New unified concatenation subclasses can be viewed as implementing an ordered set in addition to providing the support infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create one directly

of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) 3 pandas: powerful Python subclasses can be viewed as implementing an ordered set in addition to providing the support infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create one directly

of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) • New unified concatenation subclasses can be viewed as implementing an ordered set in addition to providing the support infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create one directly

major release from 0.7.3 and includes extensive work on the time series handling and processing infrastructure as well as a great deal of new functionality throughout the library. It includes over 700 commits of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) • New unified concatenation object with duplicate entries into a set, an exception will be raised. Index also provides the infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create an Index directly

of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) • New unified concatenation subclasses can be viewed as implementing an ordered set in addition to providing the support infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create one directly

major release from 0.7.3 and includes extensive work on the time series handling and processing infrastructure as well as a great deal of new functionality throughout the library. It includes over 700 commits of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) • New unified concatenation object with duplicate entries into a set, an exception will be raised. Index also provides the infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create an Index directly

major release from 0.7.3 and includes extensive work on the time series handling and processing infrastructure as well as a great deal of new functionality throughout the library. It includes over 700 commits of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) • New unified concatenation object with duplicate entries into a set, an exception will be raised. Index also provides the infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create an Index directly

major release from 0.7.3 and includes extensive work on the time series handling and processing infrastructure as well as a great deal of new functionality throughout the library. It includes over 700 commits of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) • New unified concatenation object with duplicate entries into a set, an exception will be raised. Index also provides the infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create an Index directly

major release from 0.7.3 and includes extensive work on the time series handling and processing infrastructure as well as a great deal of new functionality throughout the library. It includes over 700 commits of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) • New unified concatenation object with duplicate entries into a set, an exception will be raised. Index also provides the infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create an Index directly

major release from 0.7.3 and includes extensive work on the time series handling and processing infrastructure as well as a great deal of new functionality throughout the library. It includes over 700 commits of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting in substantial performance gains (GH220, GH249, GH267) • New unified concatenation Data pandas: powerful Python data analysis toolkit, Release 0.19.0 Index also provides the infrastructure necessary for lookups, data alignment, and reindexing. The easiest way to create an Index directly