![]() There are various ways to split and plot these data. That looks like a reasonable distribution of directions, favouring 225°. Hist(data$direction, main = "Histogram of hypothetical direction frequencies.", xlab = "Direction", ylab = "Frequency") For this tutorial I will simulate 100000 directions using the wrapped normal function (rwrpnorm) from the CircStats package. The dataĪs I mentioned, my data was related to seal swimming directions, gathered from satellite tags. In fact, if you look through the ggplot2 call, it is basically a histogram until the last couple of lines, where it is wrapped into a wind rose. In reality it doesn’t matter too much what you want to plot, and these sorts of plots are more generally used for wind direction illustrations. In my article I wanted a graphic which illustrated the preferred outward post-moult migration direction of adult female southern elephant seals from Marion Island. ![]() As before, I relied heavily on Stack Exchange and many other sites for figuring out how to get my plot looking the way I needed it to, and so this is my attempt to contribute back to the broader community. ![]() This is another post regarding some plots that I needed to make for a publication. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |