At R For The Rest of Us we spend a lot of time creating bespoke parameterised reports for our clients. In these reports, we often use CSS to create polished documents and to control the placement of our images. We’ve written about this approach elsewhere. In a recent project creating a needs assessment report on
In one of the lessons in Fundamentals of R, I teach people how to use the group_by() and summarize() functions to calculate simple summaries (e.g. if I have population data on all states, what is the total population of the United States?). But what if you want to group by a
Surveys often have multiple choice, select all that apply questions. Being able to wrangle this type of data in R can be challenging. Figuring out the right way to get your data into the (tidy) structure necessary for visualizing it with ggplot can be complicated. And, to make things even more complicated, different survey tools
Ever since I started working on my book R Without Statistics people have asked me for details on how I’m writing it. If your mental model for how a book gets written involves dozens of Word documents, you may be in for a surprise (my father certainly was). In writing R
n early 2020, I started to have conversations with publishers about doing a book on R. I was excited about the possibility, but wasn’t exactly sure what the book would be about. Then COVID came and, with two young kids at home, writing a book was not going to happen. In the
We’re often asked by clients to make maps, and oftentimes they ask us to make heatmaps. For example, we made heatmaps with {ggplot2} in these reports on 2020 U.S. Census outreach efforts. And we made interactive heatmaps with the {leaflet} package in this map
