Highlights
The binning methods of [`numpy.histogram_bin_edges`](https://numpy.org/doc/stable/reference/generated/numpy.histogram_bin_edges.html) are now available in `compute_bias`, `compute_marginal`, `plot_bias` and `plot_marginal`.
The default argument of `bin_method` of these functions changed to `"auto"`.
Additionally, strings/categorical/enum features now display all the remaining (unique) values of a feature as `"rest-n"` where `n` indicates the number of unique values. This way, `n_bins` is strictly adhered to.
The marginal plot from the example [Regression on Workers' Compensation Dataset](https://lorentzenchr.github.io/model-diagnostics/examples/regression_on_workers_compensation/#33-marginal-plot-a-model-overview-per-feature) now looks like this:

What's Changed
* MNT hatchling >= 1.26.3 by lorentzenchr in https://github.com/lorentzenchr/model-diagnostics/pull/192
* DOC improve docstring of add_marginal_subplot by lorentzenchr in https://github.com/lorentzenchr/model-diagnostics/pull/193
* ENH add numpy binning options by lorentzenchr in https://github.com/lorentzenchr/model-diagnostics/pull/194
* REL increase to version 1.4.0 by lorentzenchr in https://github.com/lorentzenchr/model-diagnostics/pull/195
**Full Changelog**: https://github.com/lorentzenchr/model-diagnostics/compare/v1.3.0...v1.4.0