Resources related to the programming language R.
What is R?
R is a language and free software environment for statistical computing and graphics. It compiles and runs on a variety of UNIX platforms, Windows, and MacOS. It is similar to the S language and environment - in fact, much code written in S will run unaltered in R. The R environment is an integrated suite of software facilities for data manipulation, calculation and graphical display. You can learn more about R from the R Project website.
How Can I Get R?
Presented September 19, 2017.
Presented September 21, 2015.
Presented October 28, 2016.
We are going to briefly explore the tidytext, widyr, and flexdashboard packages to analyze word co-occurrence, look at ngrams, and then visualize the results in word network graphs. Looking at your data in this way can help the user gain an understanding of the underlying data.
Presented January 26, 2017.
This presentation will describe the steps involved in machine learning and will include a demo an application to detect carbon monoxide poisoning in the Kansas syndromic surveillance data.
Presented July 27, 2017.
The inferences we make from data can only be as good as the quality of the data; making sure that we are receiving timely, quality data is important. In this presentation, Mark White will describe a number of functions that he has written to perform data quality checks on Kansas emergency department records from NSSP’s BioSense Platform.
Presented May 31, 2017.
Eric Bakota will go over the results from the survey and then I’ll show a report that we generate at HHD using RMarkdown, SQL, and RODBC. This report uses RODBC to connect to our Electronic Disease Surveillance System (MAVEN) to query data needed for the report. The data are imported to R, where they are processed into the various tables, graphs, charts that are used to generate the report. Automating this report has saved 8-10 hours each month.
Presented May 26, 2016.
Eric Bakota will go over Hadley Wickham’s ‘ggplot2’ package using the same grammar of graphics framework outlined in Wickham’s 2010 paper on the subject. This webinar will discuss how to create a plot by looking at the components that make up its overall structure. It will also go into how these graphics can be integrated into RMarkdown to create an automated report that is visually appealing.
Recording of R-Group Meeting from February 26, 2015 - Jarad Niemi and Nick Michaud discuss how to develop a simply shiny app using R.
Presented January 19, 2016.
This presentation will briefly introduce concepts related to effective visual display and a “big picture” of why and how R is an excellent tool to produce such displays. Through examples, the overall mechanics for producing visuals in R will be shown, as will some “nuts and bolts” details (e.g. the use of color). Methods for creating reproducible (e.g. with user made functions) and interactive (e.g. with the Shiny package) displays will be shown.