3823411
doi
10.5281/zenodo.3823411
oai:zenodo.org:3823411
RMarkdown Driven Development
Emily Riederer
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
reproducible research
rmarkdown
open science
<p>RMarkdown enables analysts to engage with code interactively, embrace literate programming, and rapidly produce a wide variety of high-quality data products such as documents, emails, dashboards, and websites. However, RMarkdown is less commonly explored and celebrated for the important role it can play in helping R users grow into developers. In this talk, I will provide an overview of RMarkdown Driven Development: a workflow for converting one-off analysis into a well-engineered and well-designed R package with deep empathy for user needs. We will explore how the methodical incorporation of good coding practices such as modularization and testing naturally evolves a single-file RMarkdown into an R project or package. Along the way, we will discuss big-picture questions like “optimal stopping” (why some data products are better left as single files or projects) and concrete details such as the {here} and {testthat} packages which can provide step-change improvements to project sustainability.</p>
Zenodo
2020-05-13
info:eu-repo/semantics/lecture
3823410
1589401236.706903
1473460
md5:5368a4ff9f6706308ef0c85ff12d7e37
https://zenodo.org/records/3823411/files/rdd-csvconf-riederer-20200510.pdf
public
10.5281/zenodo.3823410
isVersionOf
doi