Data Science Tool Building (with Wes McKinney)
Wes McKinney talks about data science tool building, what it took to get pandas off the ground and how he approaches building “human interfaces to data” to make individuals more productive.
About Wes McKinney
Since 2007, Wes has been developing data analysis software, mostly for use in the Python programming language. His primary objective has been improving user productivity, increasing performance and efficiency, and enhancing data interoperability. He is best known for creating the pandas project and writing the book Python for Data Analysis. Since 2015, he has been focused on the Apache Arrow project. He also contributed to Apache Kudu (incubating) and Apache Parquet (where I am a PMC member). He was the co-founder and CEO of DataPad. He later spent a couple years leading efforts to bring Python and Hadoop together at Cloudera. In 2018, Wes founded Ursa Labs, a not-for-profit open source development group in partnership with RStudio. In 2018, he became a Member of The Apache Software Foundation.
Links from the show
DATAFRAMED SURVEY
- DataFramed Survey (take it so that we can make an even better podcast for you)
DATAFRAMED GUEST SUGGESTIONS
- DataFramed Guest Suggestions (who do you want to hear on Season 2?)
FROM THE INTERVIEW
- Wes on Twitter
- Roads and Bridges: The Unseen Labor Behind Our Digital Infrastructure by Nadia Eghbal
- pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
- Ursa Labs
FROM THE SEGMENTS
Data Science Best Practices (with Ben Skrainka ~17:10)
- To Explain or To Predict? (By Galit Shmueli)
- Statistical Modeling: The Two Cultures (By Leo Breiman)
- The Book of Why (By Judea Pearl & Dana Mackenzie)
Studies in Interpretability (with Peadar Coyle at ~39:00)
- Modelling Loss Curves in Insurance with RStan (By Mick Cooney)
- Lime: Explaining the predictions of any machine learning classifier
- Probabilistic Programming Primer
Original music and sounds by The Sticks.