Open-Source
44 posts
Category Encoders accepted into scikit-learn-contrib
Category Encoders, a Python library for encoding categorical variables, has been accepted into the scikit-learn-contrib ecosystem. A project milestone!
Category Encoders now on conda-forge
The category_encoders Python package is now available on conda-forge, making installation easier for Conda users. Learn about the package and feedstock.
When do I work on what?
Use git-pandas to analyze and visualize work patterns across open source vs. closed source projects. Compare commit times with punchcard plots. Learn the code.
Estimating the time spent on a project with git-pandas
Learn how to estimate project development time using commit history with git-pandas. Compares to git_time_extractor, git-hours, and glass.
Automating documentation workflow with sphinx and github pages
Explore a comprehensive guide on automating the deployment of Sphinx documentation to GitHub Pages, streamlining your workflow with efficient practices.
Pypi-publisher: a simple cli for publishing python libraries
Introducing pypi-publisher (ppp): a CLI tool simplifying Python library publishing. Handles .pypirc updates, linting, git tags, and PyPI sdist uploads.
Using survival analysis and git-pandas to estimate code quality
Apply survival analysis with git-pandas to measure code quality in Git repositories by analyzing code longevity and contributor patterns over time.
Git-pandas v1.0.0, or how to check for a stable release
Explore git-pandas v1.0.0, focusing on interface consistency, parameter naming, and API simplification for improved data analysis workflows.
Data-driven engineering team management with gitnoc and git-pandas
Leverage git-pandas and gitnoc for data-driven engineering management. Visualize git data for insights on bus factor, risk, project growth, and team oversight.
Create organization-wide punchcards with git-pandas
Learn how git-pandas enables creating organization-wide punchcard visualizations, aggregating commit activity across multiple repositories for a unified view.