Wes McKinney’s fingerprints are all over the modern data stack — from inventing Pandas to co-creating Arrow. But before all that, Wes was organizing speedrun communities and hacking together better ways to wrangle datasets in finance. In this conversation, he shares his origin story and what makes good tools good. Stay tuned for part 2, coming soon.

What’s Inside:

• How frustration with data work led Wes to build pandas (and leave a PhD)
• A nostalgic dive into the GoldenEye speedrunning scene
• Why read_csv performance is a deeply personal crusade
• Lessons from convincing friends to quit finance and go open source
• Founding startups, launching Arrow, and the Ibis origin story
• The beauty of letting contributors take the reins
• Shout-out to Philip Cloud, pandas’ resident pun master
• Why open communities win — and what it takes to build them

Before Hadley Wickham became a pillar of modern data science, he was a spreadsheet-loving teenager making databases for his dad’s job. In this episode, he reflects on the early days of his involvement with R, the birth of tidyverse, and how real-world unpredictability — like a bear in a field — shapes data science.

What’s Inside:

• Hadley’s first brush with R code … inside a Word doc
• Consulting as a grad student — and learning what people really want from stats
• How messy Excel sheets inspired the tidy data revolution
• Writing R packages as a form of self-defense (and productivity)
• The secret sauce of building the tidyverse team
• On focus, burnout, and saying “no” to GitHub pull requests
• Current obsession: using LLMs  to make data science faster, easier, and more fun
• How writing books is a form of tidying ideas, and how a Shiny textbook led to a custom bike