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A post about bee colonies. I wanted make a plot for each state and have each plot be plotted to the x y location of that state on a map. I used the package geo_facet.

I've been using Rmarkdown to write reports at work. Whenever I start a project I end up having to look stuff up that I've looked up a million times before. The setup ends up taking so much time and brain power that I end up spending half a day on it. So I figured I'd write it up so I don't have to google my face off to get up and running.

If you need to pass a column name as a function parameter to a dplyr function/verb such as filter() or mutate() do this:

Similar to my post last week, we are again looking at another AIM data visualization. The last visualization was created from the raw AIM data, pulled from ArcGIS online. This visualization is pulled from terradat, AIMs online data repository for QA/QCed data, and looks at cover over three populations of Gunnison sage-grouse in Colorado, the San Miguel population, the Gunnison population and the Pinon Mesa population.

I don't put a lot of what I do at work here. I try to keep work at work and a lot of what I post here is for fun. Lately though, I've been producing some visualizations from Assessment Inventory and Monitoring (AIM) data that I think are worth sharing.

I recently started using VS code for R development. There is an awesome newish R extension for VS Code. It takes a little setup, it works best with the addition of radian, a python package, but otherwise it works really well. There are solid instructions on the extension page. I love Rstudio for the most part, but I got frusterated by the lack of editor customization (mostly line height). So here we are.