Tools for Analyzing R Code the Tidy Way

Lucy D’Agostino McGowan, Sean Kross, Jeffrey Leek

Research output: Contribution to journalArticlepeer-review

Abstract

With the current emphasis on reproducibility and replicability, there is an increasing need to examine how data analyses are conducted. In order to analyze the between researcher variability in data analysis choices as well as the aspects within the data analysis pipeline that contribute to the variability in results, we have created two R packages: matahari and tidycode. These packages build on methods created for natural language processing; rather than allowing for the processing of natural language, we focus on R code as the substrate of interest. The matahari package facilitates the logging of everything that is typed in the R console or in an R script in a tidy data frame. The tidycode package contains tools to allow for analyzing R calls in a tidy manner. We demonstrate the utility of these packages as well as walk through two examples.

Original languageEnglish (US)
Pages (from-to)226-242
Number of pages17
JournalR Journal
Volume12
Issue number1
DOIs
StatePublished - 2020

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

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