Packages

infer
infer is a tidyverse-consistent package for statistical inference. However, infer is more exciting because it makes running a t-test more like how we learned it in stats class. That is, infer requires you to specify your explanatory and response variables, state your hypothesis with hypothesize, generate the permutations or simulations, then calculate your chosen statistic. It’s another step in the right direction for consistency and clarity, which is great for getting more people coding (and doing statistics properly). For more on infer, my friend, Rich Pauloo, takes a deeper dive here.

sf
sf is a tidyverse-consistent package for spatial data. sf’s main thrust is to use what are called simple features, aka “standard for the exchange of spatial feature data, meaning points, lines and polygons (and not e.g. vector topology, networks, or rasters).” I’ve only scratched the surface with sf thus far, but it promises seamless integration with ggplot (using geom_sf) in a soon-to-be-released version. Here’s a helpful primer from Ryan Peek.

tidygraph & ggraph
These packages are, say it with me, tidyverse-consistent packages for network analysis. tidygraph takes the place of tidyr while ggraph fills the role of ggplot in your workflow. I haven’t used this myself, but the presentation slides are available here and a blogpost.

tibbletime
tibbletime handles time-series data in a tidyverse format. The conference presentation slides can be found here.

See here for all conference presentations