Emily Riederer | RMarkdown Driven Development | RStudio (2020)
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
rmarkdown
rstudio
testthat
Emily Riederer
Rstudio::conf(2020)
RStudio
Data Science
Machine Learning
Python
Stats
Tidyverse
Data Visualization
Data Viz
Ggplot
Technology
Coding
Connect
Server Pro
Shiny
Rmarkdown
Package Manager
CRAN
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Serious Data Science
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Github
Data Wrangling
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Lazy Evaluation
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Programming Education
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