Notebook to show Raw Data Feature

[johnwalz97]

Internal Notes for Reviewers

Adding a notebook to directly demo the new Raw Data feature as well as a quick fix to better display raw data via the inspect() function.

External Release Notes

[github-actions]

PR Summary

This pull request introduces a new Jupyter notebook, understand_utilize_rawdata.ipynb, which provides a comprehensive guide on how to understand and utilize the RawData feature in ValidMind tests. The notebook includes setup instructions, usage examples, and custom test creation using RawData. It demonstrates how to access, inspect, and utilize RawData for creating custom outputs such as ROC curves, Pearson Correlation Matrices, and Precision-Recall Curves.

Additionally, the PR enhances the validmind/utils.py module by improving the handling of generic objects. The handle_generic_object method now includes a try-except block to safely return the class name of an object, and the default method has been added to provide a preview of DataFrame objects, including their type, a preview of the first five rows, and their shape. This enhancement improves the robustness and readability of object handling within the ValidMind library.

Test Suggestions

• Run the Jupyter notebook to ensure all cells execute without errors and produce the expected outputs.
• Test the RawData feature by creating custom tests and verifying the output customization using the provided examples.
• Verify the new default method in validmind/utils.py correctly handles DataFrame objects by returning the expected preview and shape information.
• Test the handle_generic_object method to ensure it correctly returns the class name of various object types, including those without a __str__ method.

[validbeck]

Thanks John! I cleaned up the notebook, applied our style guidelines, and moved it into how_to. Once this PR is merged I'll also wrap the notebook into our docs site.