DataFramed

#49 Data Science Tool Building

November 19, 2018 Season 1 Episode 49
DataFramed
#49 Data Science Tool Building
Chapters
DataFramed
#49 Data Science Tool Building
Nov 19, 2018 Season 1 Episode 49
DataCamp
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.
Show Notes

Hugo speaks with Wes McKinney, creator of the pandas project for data analysis tools in Python and author of Python for Data Analysis, among many other things. Wes and Hugo talk 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. On top of this, they’ll talk about the future of data science tooling, including the Apache arrow project and how it can facilitate this future, the importance of DataFrames that are portable between programming languages and building tools that facilitate data analysis work in the big data limit. Pandas initially arose from Wes noticing that people were nowhere near as productive as they could be due to lack of tooling & the projects he’s working on today, which they’ll discuss, arise from the same place and present a bold vision for the future.

LINKS FROM THE SHOW

DATAFRAMED SURVEY

DATAFRAMED GUEST SUGGESTIONS

FROM THE INTERVIEW

FROM THE SEGMENTS

Data Science Best Practices (with Ben Skrainka ~17:10)

Studies in Interpretability (with Peadar Coyle at ~39:00)



Original music and sounds by The Sticks.



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