Month: October 2018

Another one for me before I forget, I seem to have terrible problems writing headings and tables in a loop in RMarkdown. Everything gets crushed together because the line returns don’t seem to work properly and either the table or the headings get mangled. Well here it is, the thing I just did that worked:

for(i in 1:2){

  cat("Heading ", i, "\n")
  
  cat("===========================")
  
  pandoc.table(iris)
}

That’s it! Don’t put any other weird “\n”s or [HTML line breaks which I now realise WordPress will interpret literally] in. You don’t need them!

I’m pretty sure I’ve made up the word shinyverse, to refer to all the packages that either use or complement Shiny. This is a non-exhaustive list of shinyverse packages, mainly for my benefit when I inevitably forget, but if it’s useful for you too then that’s good too.

shiny.semantic adds support for the Semantic UI library to Shiny. Useful if you want your Shiny apps to look a bit different or there’s something in the library that you need.

shinyaframe doesn’t particularly sound like the kind of thing that everyone reading this will drop everything to do on a rainy weekend, but it’s awesome so it’s worth mentioning here. It allows you to use Mozilla A-Frame to create virtual reality visualisations with Shiny!

shinycssloaders does very nice simple loading animations for while your Shiny application is thinking about how to draw an output.

shinydashboard is so commonly used that I tend to think of it as what you might call “base-Shiny” (another terms I made up). If you’ve never made a Shiny dashboard I suggest you have a look.

shinyWidgets is a lovely package that extends the number of widgets you can use. I’ve used the date picker in the past but there are plenty to choose from.

shinythemes is another one that feels like base-Shiny. Change the appearance of you Shiny apps very easily by selecting one of several themes in the UI preamble.

shinytest is for testing Shiny applications.

shinymaterial allows you to use a UI design based on the Google Material look.

shinyLP allows you to make a landing page for Shiny apps, either to give more information or to allow a user to select one of several applications.

shinyjs. Another base-Shiny one. Easily add canned or custom JavaScript

shinyFiles allows the user to navigate the file system on the server.

bsplus allows you to add lots of things which are in Bootstrap but not in Shiny to your apps (and to RMarkdown, to boot).

rintrojs allows you to make JavaScript powered introductions to your app. Pretty neat.

crosstalk is seriously neat and allows you to use Shiny widgets that have been programmed to interact with each other, or write this interaction yourself if you’re a package author. Once you or someone else has done this, Shiny (or RMarkdown) outputs can automatically react to each other’s state (filtering, brushing etc.)

There must be other people out there doing this, so I’ll share this neat thing I found today. Quite often, you’ll have a dataset that has a lot of columns, only one of which will have something in it for each row. Survey Monkey, in particular, produces these kinds of sheets if you use branching logic. So if you work in one bit of the Trust, your team name will be found in one column, but if you branched elsewhere in the survey because you work somewhere else, it is in another column. Lots of columns, but each individual has only one non-missing element in each (because they only work in one place and only see that question once).

In the past I’ve done hacky things with finding non missing elements in each column line by line and then gluing it all together. Well today I’ve got 24 columns so I wasn’t going to do it like that today. Sure enough, dplyr has a nice way of doing it, using coalesce.

coalesce(!!!(staffData %>%
               select(TeamC1 : TeamC24)))

That’s it! It accepts vectors of the same length or, as in this case, a dataframe with !!! around it. Bang bang bang (as it’s pronounced) is like bang bang (!!) except it substitutes lots of things in one place instead of one thing in one place. So it’s like feeding coalesce a lot of vectors, which is what it wants.

I really can’t believe it’s that simple.