790: Open-Source Libraries for Data Science at the New York R Conference
Jun 7, 2024
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Data science trailblazers Drew Conway, Jared Lander, Emily Zabor, and JD Long share their favorite R libraries at the New York R Conference. Topics include iGraph for transitioning to full-time R programming, Segway package benefits, Snake Make vs. Targets for data cleaning, and intuitive open-source libraries for non-coders.
iGraph in R helped Drew Conway transition to full-time R programmer.
The targets package in R optimized Jared Lander's workflow with automatic DAG creation.
Deep dives
Favorite Open Source Libraries for Data Science - Drew Conway and iGraph
Drew Conway shares his experience with iGraph, an open source package he discovered during his graduate studies, focusing on social network data. He initially contributed to NetworkX in Python but found iGraph to fulfill his data science needs in R. The package, maintained by individuals including a fellow graduate student now involved in generative AI in law, became instrumental in his transition to a full-time R programmer.
Favorite Open Source Libraries for Data Science - Jared Lander and targets
Jared Lander discusses the targets package in R, highlighting its functionality similar to 'make' in building directed acyclic graphs automatically. By optimizing code execution and utilizing cached results, targets significantly improved Lander's workflow. He also mentions the Python equivalent, snake make, developed by the Python community, reflecting the reciprocal influence between the R and Python data science ecosystems.
The experts reveal their top open-source R libraries with us live from the New York R Conference! This Super Data Science Podcast episode features an exclusive panel with data science trailblazers Drew Conway, Jared Lander, Emily Zabor, and JD Long. They share their favorite R libraries and valuable insights to enhance your data science practice.