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Establishing Meaningful Performance Comparisons between R and Python

Establishing Meaningful Performance Comparisons between R and Python

R vs Python Reproducible Python Environment The Data Small Medium Big The Code R “Base” - utils::read.csv() readr::read_csv() data.table::fread() Python pandas.read_csv() Dependencies Only The Test Initial Carpentry The Results Execution Times tl;dr Appendices Dependency Load Times Summary Tables Environment IDE R Python System R vs Python Performance comparisons between R and Python suck. Most seem to be run in Jupyter Notebook and many are using Python’s rpy2 library to run poorly optimized R code. I’m not an anti-for() loop Nazi (yes, you can use them effectively in R),...

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Thoughts on Teaching R and Yet Another Tidyverse Intro

March 16, 2018
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Thoughts on Teaching R and Yet Another Tidyverse Intro

Context Reflection Resources Up Front tibble %__% “Tidy” Data select() columns filter() Rows mutate() Columns arrange() Rows group_by() for Grouped Data summarize() Image credit to R Memes for Statistical Fiends Considering this is a blog post, I’m going to get all bloggy here before jumping into the code. Context I recently had the opportunity to teach some R coding to colleagues and classmates in a series of workshops. Some had already dabbled in R...

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GDELT, Missiles, and Image Collection

January 22, 2018
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GDELT, Missiles, and Image Collection

The Global Database of Events, Language, and Tone, or GDELT, is “a realtime network diagram and database of global human society for open research”. The potential for a firehose stream of global data has tantalizing possibilities for research, but concrete examples of work beyond simple evaluations of the database’s capabilities are notably absent… See also: My hasty walkthrough from November 2017, Evaluating...

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