Create HTML profiling reports from pandas DataFrame objects
The current dependency policy is suboptimal. Pinning the dependencies is great for reproducibility (high guarantee to work), but on the downside requires frequent maintenance and introduces compatibility issues with other packages. Therefore, we are moving away from pinning dependencies and instead specify a minimum version.
Early releases of pandas v1 demonstrated many regressions that broke functionality (as acknowledged by the authors here). At this point, pandas is more stable and we notice high demand for compatibility. We move on to support pandas' latest versions. To ensure compatibility with both versions, we have extended the test matrix to test against both pandas 0.x.y and 1.x.y.
Python 3.6 introduces ordered dicts and f-strings, which we now rely on. This means that from pandas-profiling 2.6, you should minimally run Python 3.6. For users that for some reason cannot update, you can use pandas-profiling 2.5.0, but you unfortunately won't benefit from updates or maintenance.
Starting from this release, we use Github Actions and Travis CI combined to increase maintainability. Travis CI handles the testing, Github Actions automates part of the development process by running black and building the docs.
Deprecation:
Stability:
Other improvements:
Deprecation:
Stability:
Other improvements:
The v2.4.0 release decouples the data structure of reports from the actual rendering. It's now much simpler to change the user interface, whether the user is in a jupyter notebook, webpage, native application or just wants a json view of the data.
We are also proud to announce that we are accepted for the GitHub Sponsor programme. You are cordially invited to support me through this programme, because you want to see me continue working on this project and to boost community funding, GitHub will match your contribution!
Other improvements:
Special thanks to @marco-cardoso @ajupton @lvwerra @gliptak @neomatrix369 for their contributions.
Thanks @bensdm and @huaiweicheng for your valuable contributions to this version!
New release introducing variable size binning (via astropy), PyCharm integration and various fixes and optimizations.
missingno
package to 0.4.2, fixing the font size in the bar
diagram.Thanks to: @Utsav37 @mansenfranzen @jakevdp
Fix [#211] and README
The pandas-profiling
release version 2.1.0 includes:
srcdoc
attribute (which fixes [#199]), a full-width option is added and the column layout is improved.Contributors: @abhilashshakti @adamrossnelson @manycoding @InsciteAnalytics
Bugfix on version structure for 2.0.2.
Revised version structure, fixed recursion preventing installation of dependencies ([#184]).
The setup.py file used to include utils from the package prior to installation. This causes errors when the dependencies are not yet present.