I can't believe it has taken me however many years I've been using @rstats#ggplot2ggsave() to realise... it saves the current size of the "Plots" pane in RStudio (or more generally if I had bothered to ever properly read the help text "using the size of the current graphics device")
@jpeelle@rstats I've heard this referred to as a "heatmap" or "density plot" (I prefer the former - a density plot to me is that "layered waves" type plot.)
How to generate this in #rstats depends on what your underlying data looks like, but I've had good success with #ggplot2, as well as dedicated packages for visualization of fitted models.
In my head, the last few days have "felt" like Friday. In the midst of all the chaos, I miraculously am still chugging along with...everything I have to do. This week's #rtistry#ggplot2 work is for the "Wavescapes" chapter. In the last week, I've re-learned more about basic trigonometry than I care for. Here are some snapshots of some WIP outputs as I'm still trying to land on an example to go through step-by-step for the beginning of this chapter.
"{viridis} is an R package that presents colour-blind friendly palettes. It improves the graph readability. The advantage of {viridis} is that the palettes are perceptually uniform, easy to print in greyscale and colour-blind friendly. To use the {viridis} in ggplot2 simply ass:
📊 scale_colour_d()
In the slope graphs I generated in this example, I simply added the function above. The image shows four possible {viridis} palettes. #rstats#accessibility#ggplot2#dataviz
I know it violates the data component/non-data component dichotomy but I wish it were easier to map aesthetics to categorical axis labels #rstats#ggplot2
It’s possible to pass vectors of colors in element_text() but it’s unsupported so you get warnings. That method doesn’t work for bold/italic/etc instead you have to resort to things pike ggtext::element_markdown() but that gets cumbersome in conjunction with controlling the order of levels. #rstats#ggplot2
Don't loose the chance for revisting the best parts of making a graph with #ggplot2() in #R.
In this talk I will replicate one of the #DoboisChallenge plate.
Really pressed into a vector space analysis of C major scale and basic triads this morning, and got a few things out that I hope will inform my playing. Lot's of #ggplot2#rstats graphs too
Inspired and made possible by @nrennie, here's a typewriter elevation map of Japan. The characters to indicate increasing elevation are: 地, 低, 中, 高, and 峰.