A few months ago I did a mini project using open crime data and R to create crime visualisations. At that time, I was already thinking about a web app using Shiny but I couldn’t justify the time to develop the app and then set up a server etc. Not until two weeks ago when I received an invitation to join the alpha testing of ShinyApps.

ShinyApps – A Wonderful Discovery

I went through the ShinyApps’ getting started guide. Everything looks pretty straight forward. So I decided to go ahead and moved my codes from the crime visualisation project to a new ShinyApps project. The progress was unexpectedly smooth. Given that I had no web application development experience prior to this mini exercise, I consider this a quick success! All credit goes to the RStudio team for providing these tools and hosting services (especially Tareef Kawaf who kindly answered all my questions).

I would summarise the whole process in the following few steps:

1. Sign up for a ShingApps alpha testing account here (you will need a Google account).
2. Install packages shiny and shinyapps (click on the links for installation help).
3. Sign in to my.shinyapps.io, give your ShinyApps account a name (“blenditbayes” in my case) and get your application token/secret.
4. Go through the tutorials, create the ui.R and server.R scripts for your app.
5. Test the app locally using runApp().
6. Once you’re happy with the app, apply your token/secret and deploy your app using deployApp().

CrimeMap in Action

First, enter a location of your choice (e.g. London) within England, Wales and Northern Ireland. Select the first month of crime data collection and then the length of the analysis period. After that, click on the “Update” button. My experience is that the graphs should come up within a minute if the length of analysis is less than or equal to 6 months. Depending on the location and the length of analysis, the process might take longer (say a couple minutes).

The outputs (at the time of writing) are displayed in three tabs: Data, Crime Map and Trends. The Data tab shows the original crime data records downloaded from the data.police.uk (I may add a feature like “download as CSV in future). The crime map is a density plot of the crime data. Finally, the trends tab shows bar charts of crime records over time in different crime categories. Right click on the map and you can save the image in its original size (1280 x 1280).

Fine-tuning the Density Plots

The Density Plot Settings allow user to modify the “behind the scenes” ggplot2 codes. You can modify the layer transparency (alpha range), the number of bins, the width and the colour of the boundary lines as well as the colours of the gradient. My hope is to develop a user-friendly interface that allows users to quickly create maps with their own favourite themes.

Surely, ggplot2 is much more powerful than that and has a lot more settings available. What other settings would you like to see here? Please let me know.