Journal

All Posts

• Github.com cumulative blame in 5 lines of python

  January 31, 2016 · data-science dataviz git

  Visualize your GitHub repository growth over time using the git-pandas Python library and GitHubProfile class-all in just a few lines of code.

• Decision Strategies: Beyond Expected Value

  January 28, 2016 · mathematics

  An exploration of decision-making strategies that go beyond simple expected value calculations, incorporating concepts of ruin and windfall.

• Data-driven engineering team management with gitnoc and git-pandas

  January 19, 2016 · data visualization dataviz git

  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

  January 17, 2016 · data-analysis git git-pandas

  Learn how git-pandas enables creating organization-wide punchcard visualizations, aggregating commit activity across multiple repositories for a unified view.

• How to Write Comprehensions and Alienate People

  January 8, 2016 · best-practices data-science programming

  A tongue-in-cheek guide to writing Python comprehensions that will make your colleagues question their life choices and your sanity.

• Gitpandas v0.0.6: python 2.7, fileowners, file-wise blame and examples

  January 7, 2016 · data-analysis data-science git

  Overview of git-pandas v0.0.6 release, highlighting new features like Python 2.7 support, file-wise blame, file owner determination, and other improvements.

• Market-Product fit vs Product-Market fit

  December 28, 2015 · entrepreneurship startups

  An exploration of the differences between market-product fit and product-market fit, and how to determine which path is right for your startup.

• Git-Pandas v0.0.5: coverage.py, risk, and more

  December 25, 2015 · data-analysis git git-pandas

  Git-pandas v0.0.5 is out! Adds coverage.py support, file change rate metrics for risk analysis, API updates, time-based filtering for commits.

• Common Data Pitfalls for Recurring Machine Learning Systems

  December 20, 2015 · analytics data-engineering data-science

  Explore common data pitfalls in recurring machine learning systems, including new categories, data format changes, sending issues, deduplication, and updates.

• Visualize all of your git repositories with gitnoc and git-pandas

  December 13, 2015 · data visualization dataviz git

  Visualize git repositories at scale using GitNOC & git-pandas. Create profiles to analyze cumulative blame & file change rates across multiple projects.