Dython

Welcome!

Dython is a set of Data analysis tools in pYTHON 3.x, which can let you get more insights about your data.

This library was designed with analysis usage in mind - meaning ease-of-use, functionality and readability are the core values of this library. Production-grade performance, on the other hand, were not considered.

Here are some cool things you can do with it:

Given a dataset, Dython will automatically find which features are categorical and which are numerical, compute a relevant measure of association between each and every feature, and plot it all as an easy-to-read heat-map. And all this is done with a single line:

from dython.nominal import associations
associations(data)

The result:

Here's another thing - given a machine-learning multi-class model's predictions, you can easily display each class' ROC curve, AUC score and find the estimated-optimal thresholds - again, with a single line of code:

from dython.model_utils import metric_graph

metric_graph(y_true, y_pred, metric='roc')

The result:

Installation

Dython can be installed directly using pip:

pip install dython

Other installation options are available, see the installation page for more information.

Examples

See some usage examples of nominal.associations and model_utils.roc_graph on the examples page.

Citing

When using Dython, please cite it using this citation:

@article{Zychlinski2025,
    doi = {10.21105/joss.09174},
    url = {https://doi.org/10.21105/joss.09174},
    year = {2025},
    publisher = {The Open Journal},
    volume = {10},
    number = {116},
    pages = {9174},
    author = {Shaked Zychlinski},
    title = {dython: A Set of Analysis and Visualization Tools for Data and Variables in Python},
    journal = {Journal of Open Source Software}
 }