v2.4.2

What's Changed

• Feature/code quality by @guerinclement in #521
• Bump dash from 1.9.1 to 2.15.0 by @dependabot in #526
• Feature/lint by @guerinclement in #522

New Contributors

• @guerinclement made their first contribution in #521

Full Changelog: v2.4.1...v2.4.2

v2.4.1: Hotfix bug fo TreeExplainer selection

Fix #514 BUG: with version 2.4.0 TreeExplainer is never used

v2.4.0: ⬆️ Support for Python 3.11

Major announcements in this release are :
- Shapash support Python 3.11
- Shapash can compute Shapeley values through Shap for any model supported by Shap

Features:

• Support for Python 3.11 #512
• Be able to use Shapash to compute Shapeley values through Shap for any model supported by Shap #506

Breaking change:

• Removes ACV from shapash and fixes dependencies #482

Fixes:

• #475
• #503
• #497

v2.3.7: Hotfix for handle missing data for categorical columns

Hotfix for handle missing data for categorical columns #490

Fix this issues : #489 #478 #472

Update extra require for report pip install shapash[report] #494

v2.3.6: Add tests for Webapp and first refacto of the webapp

Unit tests of the webapp's callbacks have been created.
In addition, a first refactoring of the Webapp is done to simplify maintenance and future developments.
#463

Some fix:
#455 References and modifications of self in smartapp create unwanted behavior
#483 Bug in Webapp for filter

v2.3.5: ⬆️ Remove numpy and pandas version limits

Remove numpy and pandas version limits.
Shapash has shap and xgboost dependencies that have been released. We no longer need to set numpy and xgboost versions.

Fix #451, #457

v2.3.4: hotfix for shapash and shap with numpy

Hotfix for shapash and shap incompatibility with numpy versions 1.24.0 and above. We limit numpy to a version under 1.24.0.

PR #459 resolves incompatibility between shapash code and numpy.
But Issue #457 remains because of shap incompatibility with numpy.
PR #460 limits numpy versions under 1.24.0.

v2.3.3: hotfix for dash and Flask compatibility

Hotfix for dash incompatibility with Flask versions 2.3.0 and above. We limit Flask to a version under 2.3.0.

v2.3.2: hotfix for pandas 2.0.0

Hotfix for pandas 2.0.0, however, we limit pandas for the moment because some tests do not pass with xgboost.

The main bug on the app with pandas 2.0.0 is fixed
#451 fix pandas version until xgboost is fixed and fix other code for pandas

Other fixes:
#440 Remove data from package
#441 scatter plot prediction when not enough data

We have a new tutorial and a new dataset:
#443 Feature/tutorial accident

v2.3.0 : ✨ 2 news Additional dataset columns and Identity card

These 2 new features are designed to understand its model just by browsing the Webapp and have all the necessary information

• With additional dataset columns to have other contextual information than the features of the model
• With an Identity card to better see characteristics of a single sample

✨ Features
#422 Feature/webapp visuals
#424 Feature/id card
#425 Feature/additional data
#426 Target and error columns in dataset

⬆️ Upgrade dependencies and stop support for Python 3.7
#418 maximum version for category_encoders and bump version
#414 maximum version for sklearn
#421 Feature/fix sklearn ce dropping Python 3.7

🐛 Bug fixes
#428 Selecting an index via the Index input box for integers on Windows fails
#429 Selecting an invalid index via the Index input box logs an error
#430 Local explaination plot fails on positive/negative contributions display for specific cases
#433 SmartExplainer method init_app fails when no y_pred
#431 Errors are not managed when manipulating filters on the Shapash Webapp
#432, #434 Update python version for docs