## Contents ## I have created these materials to demonstrate how to use R (via the tidyverse syntax) to wrangle data from large data set into manageable, "tidy" dataframes suited to particular analyses. I am sharing these materials to provide a practical example of using R for data wrangling. I hope that you find them useful! The data set, **oSpan_RuG_anon.csv**, contains output for several hundred participants on the automated operation span task from Prof. Randy Engle's [lab][1]. These data were collected by Dr. Jonathan Mall as part of his PhD project. This operation span program is designed to conveniently provide the experimenter with summary scores, but other aspects of the data (such as processing task accuracies and response times) are also preserved in the data, but take some work to extract usefully. The R markdown script, **parseWMSpan.Rmd** walks through how to use tidyverse functions to extract and organize elements of the output for analysis. It demonstrates and explains use of several of the tidyverse functions. This file can be run in R Studio and is editable. The summary notebook **parseWMSpan.nb.html** can be downloaded and opened in a web-browser. It contains nicely-formatted text, code chunks, and resulting output, and is not editable. I have licensed this project CC-By Attribution. If you are adding the data I have shared to an existing data set, please cite this OSF project. If you are writing about learning to organize data with R, then you may cite this project. If you are writing R scripts based on mine, there is no need to cite this project. Questions or comments about these scripts may be directed to Dr. Candice Morey (moreyc@cardiff.ac.uk). [1]: http://englelab.gatech.edu