If you want to plot a chart with a few outliers in ggplot, you might be temped to use ylim. The problem with ylim is that it removes the data points that go beyond the limits.
For instance, if you have the following data:
data <- data.frame(x = 1:20, y = c(rnorm(19), 500))
If you plot this with no changes, this is what you get:
ggplot(data, aes(x,y)) + geom_line()
It’s kind of hard to understand what’s going on in other points other than the last, so some zooming comes in handy. If you use ylim, this is what happens:
ggplot(data, aes(x,y)) + geom_line() + ylim(-5…
Time Maps are a great way to understand events that happen with a certain cadence over time. Take a look at this article by Mark Watson for an excellent explanation on what they are and when they can be useful.
The end result of this article will be to create a Time Map that looks like this:
The type of data I usually want to put in this type of chart comes in the form
<TimeStamp> | <Event>. Here’s an example data frame:
df <- data.frame(helper = c(rnorm(500, 120, 100),
rnorm(500, 1, .8))) …
We are using monit to make sure our Shiny Server is running properly. We also want to make sure our applications and reports aren’t broken.
Testing “normal” Shiny applications can be achieved with
check host, but Rmd files are trickier... they return a success page, and only then do they build the report, which later can lead to an undetected error.
Our solution was to use puppeteer to test these pages.
This may differ from distribution to distribution. We are using CentOS, so the 1st thing was upgrading nodejs to a later version. This was done using nvm.
The commands look something…