Lately, I got the chance to play around with Shiny and Leaflet a lot - and it is really fun! So I decided to catch up on an old post of mine and build a Shiny application where you can upload your own GPX files and plot them directly in the browser.

Of course, you will need some GPX file to try it out. You can get an example file here (you gonna need to save it in a .gpx file with a text editor, though). Also, the Shiny application will always plot the first track saved in a GPX file. Also, only tracks are supported at the moment, no routes or waypoints. Basically, most sports tracker apps or devices produce such files.
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[EDIT: The function now also inludes the possibility to plot the IQR around the median. I shifted the median slightly downwards to prevent the SD and the IQR from overlapping.]

I wrote a function to visualise results of Likert scale items. Please find the function below the post. Here is an example plot:

The function is called 'plot.likert' and takes the following arguments:

- vec: The vector with the raw results

- possible.values: A vector with all the possible values.
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Today I want to write about a solution to a quite specific problem. Suppose, you want to label cells in your 'vcd' package mosaic plots in a custom way. For example, we might want to use cell labels which indicate "too much" or "too few" cases (given your expected values). Such labels might be "+" and "-" (and maybe "++" and "--" for higher residuals).
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png("goodbye.png", height = 625, width = 500)

par(col = "purple")

plot(1, 1, xlim = c(0,800), ylim = c(0,1600), type = "n", bty = "n", xaxt = "n", yaxt = "n", xlab = "", ylab = "")

symbols(x = 400, y = 1200, circles = 400, add = T, lwd = 40)

lines(x = c(400, 400), y = c(900, 100), lwd = 40, lend = 1)

lines(x = c(480, 320), y = c(500, 500), lwd = 40, lend = 1)

polygon(x = c(400, 480, 400, 320, 400), y = c(-20, 200, 100, 200, -20), col = "purple", border = "purple")

polygon(x = c(450, 500,

R is great, and you can do a LOT OF stuff with it.

However, sometimes you want to do really basic stuff with huge or a lot of files. At work, I have to do that a lot because I am mostly dealing with language data that often needs some pre-processing.

Most of these operations are done much, much faster on the level of the operating system (preferably in Bash on Linux or Unix, i.e. Mac OS).
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