From its previous major release v0.22, the contributors of pandas release the next major version 0.23.0 with numerous new features, enhancements, lists of API changes and deprecations. This release adds pivotal support in performing custom types operations and extended support to arguments and conversion tasks.The upgraded version also power ups with performance improvements along with a large number of bug fixes.
New feature highlights v0.23:
- Round-trippable JSON format with ‘table’ orient.
- Instantiation from dicts respects order for Python 3.6+.
- Dependent column arguments for assign.
- Merging/sorting on a combination of columns and index levels.
- Extending Pandas with custom types.
- Excluding unobserved categories from groupby.
- Changes to make output shape of DataFrame.apply consistent.
- Resolved bugs related to categorical operations like merge, index constructor, factorize.
- Bugs in numeric operations like Series constructor, Index multiplication, DataFrame flex arithmetic fixed.
- Other bugs related to Strings, indexing, Timezones, TimeDelta are also fixed in this version.
Python’s pandas package provides developers with fast, flexible, and expressive data structures making it easy and intuitive to work with “relational” and “labeled” data.
With its continuation release of feature-packed versions, pandas could soon become the most powerful and flexible open source data analysis and manipulation tool for your data science project.
To know more about the API changes, deprecations and performance improvements, please read release documentation on Github.