Abstract:
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Three languages dominate modern data-intensive computing tasks: R, Python, and Julia. Comparisons and cases for using any one of these computing environments has tended to focus on benchmarks. While execution speed provides a quantifiable comparison it is often only a small part of what makes an effective environment for computing with data. Rather than trying to provide a head-to-head comparison, this talk identifies some of the data structures and grammatical constructs that have lead to the success of the languages. This talk will also show how these concepts are being used across these languages and where they could be further taken advantage of.
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