R tidyverse, dplyr and ggplot2 at Tampa Bay Data Science Group

Datetime:2016-08-23 01:45:46          Topic:          Share

At Tampa Bay Data Science Group , this month Dr. Thomas Keller presented on intro to the R tidyverse: dplyr,ggplot2, and some Twitter conference data visualization . Two other good dplyr/ggplot resources is this blog post ( https://rollingyours.wordpress.com/2016/07/19/dplyr-and-zika-epilogue/ ) and this recent JSM talk by Jim Horton ( https://github.com/Amherst-Statistics/JSM2016-thinkwithR/blob/master/jsm2016-horton.pdf )

Here are links to the slides ( http://thomas-keller.github.io/talks/intro_ggplot_twitter_conf_20160808.pdf ) , R markdown ( http://thomas-keller.github.io/talks/intro_r_ggplot_20160808.Rmd ) and R html ( http://thomas-keller.github.io/talks/intro_r_ggplot_20160808.html )

Swami Chandrasekaran made a Curriculum via Metro map.

Abstract:In a recent ranking of programming languages, R has climbed the ranks to 5th place in 2016; notably making it the most popular statistical programming language, and is free and open-source to boot! One reason for its continue popularity is the unparalleled power of its visualization libraries. In the past few years one library, ggplot2, and a cluster of related support libraries called the "tidyverse" have arisen that provide powerful idioms to R, including piping and functional approaches that are popular amongst data scientists in other programming languages for its ability to allow the concise expression of a workflow of transforming or reshaping data. I will introduce a few worked examples showing off the the utility of the dplyr library when matched with ggplot2. I will close with a demonstration of a library I am developing now aimed at helping people analyze the some of social medial (Twitter, specifically) of conferences. The Twitter library code is available at https://github.com/thomas-keller/tweet-conf . Slides and R code will end up here http://thomas-keller.github.io/talks/ .

Speaker's Bio:Thomas Keller is a Computational Biologist and Data Scientist in the Tampa Bay region. He completed a PhD in 2012 in the field of Evolutionary Biology, and has been writing code to throw data around and visualize it since 2007 in Python and R. He is currently exploring postdoctoral appointments studying evolutionary biology, and can be reached by email at thomas (dot) e (dot) keller (at) gmail (dot) com or on Twitter at @tek_keller. Longer-form thoughts coalesce on a blog at  http://thomas-keller.github.io/blog/ .