Resource Round-Up: R in Industry Edition

One of the ways that practices of reproducible research can be brought into industry is through the development of custom R packages and data tools for one’s company / organization. Not only can these tools deliver large efficiency gains and standardization, they ideally infuse corporate culture with the shared passion and mission found in open source communities. Similar to [my favorite readings on reproducible research], the benefits of internal R packages are a common theme in my talks and on my Twitter feed1. [Read More]

Rtistic: A package-by-numbers repo

Last winter, I attended a holiday party at a “paint-and-sip” venue. For those unfamiliar, “paint-and-sip” is a semi-trendy cottage industry offering evenings of music, wine, and a guided painting activity. For example, my group painted sasquatch on a snowy winter’s eve: A very bad painting of a sasquatch in a forest As often happens, this completely unrelated thing set me thinking about R. What made painting fun when we lacked the talent and experience to excel, when it almost surely wouldn’t turn out very well, and when “failure” would be very visibly and undeniably on display? [Read More]

RMarkdown Driven Development (RmdDD)

Introduction RMarkdown is an excellent platform for capturing narrative analysis and code to create reproducible reports, blogs, slides, books, and more. One benefit of RMarkdown is its abilities to keep an analyst in the “flow” of their work and to capture their thought process along the way. However, thought processes are rarely linear; as a result, first-draft RMarkdown scripts rarely are either. This is fine for some individual analysis and preliminary exploration but can significantly decrease how understandable and resilient an RMarkdown will be in the future. [Read More]