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### Interactive Parallel Coordinates with Multiple Colours

For my research project, I need a tool to visualise results from multi-objective optimisations. Below is one of my early attempts using base R and parcoord in the MASS package, I have no problem using them for publication. However, these charts are all static. For a practical decision support tool (something I am working on), I need the charts to be interactive so that users can adjust the range/thresholds in each parameter and narrow down the things to display in real time.

Many thanks to Ken (timelyportfolio) who kindly pointed me to his code examples. Based on that, I developed a prototype version of the interactive parallel coordinates plot with multiple colours (as shown above). OK, the values in the chart are totally unrelated to my research – I just used the ‘Theoph’ dataset in R for testing purposes. Yet, this is a much needed exercise to see if I can use rCharts parallel coordinates for my research. The answer, of course, is YES. It also works with my customised colour palette too (using Bart Simpson this time)!

Here is the R code for the above chart:

### Showing your rCharts on bl.ocks.org

In the process of making this plot, I also discovered how to display rCharts (d3, html or practically any code) on Mike Bostock’s site “bl.ocks.org“. If you haven’t seen his site, do check this out. It is one of the coolest things on earth.

I wanted to have a gallery like that too … but I didn’t know how. I used to think that Ramnath and Ken must have bought Mike a beer so that they can have their stuff hosted on bl.ocks.org (see bl.ocks.org/ramnathv and bl.ocks.org/timelyportfolio). I was very wrong, everyone with a GitHub account can do it. All you need are your imagination (and some gists). The site automatically pulls your gists and displays them as beautiful blocks gallery.

In order to display your cool rCharts on bl.ocks.org, you can either:
1. publish the rCharts to gist using the ‘$publish’ function (e.g. r1$publish(‘name.of.gist’, host = ‘gist’)  where r1 is the rCharts object)
2. save the rCharts as a stand-alone HTML (e.g. r1\$save(‘index.html’, cdn = TRUE)) and then include it in a gist.
For optimal display, I would recommend setting your rCharts size to 960 x 500 (same as the display size on bl.ocks.org). You can also include a ‘README.md’ file and a ‘thumbnail.png’ to provide more information. I think the best resolution for the thumbnail is 230 x 120 (about the same aspect ratio as full display). You will need to manually push the png file (see this post for more details).

So here are the parallel coodinates plot as shown on bl.ocks.org

… and my gallery at bl.ocks.org/woobe

### Latest on Colour Palette Generator

First, let me point you to Russell Dinnage’s blog post. It is easily one of the finest R blog posts I’ve read so far. All these colours and graphs. Wow! It’s yet another #RCanDoThat moment for me (so good it needs a hashtag).

So many thanks to his effort and cool ideas, we continue to add more functions to the rPlotter package. It is also a great opportunity for us to better understand the pull/merge GitHub mechanism.

### Credits

Again, I would like to thank Ken for his help (not only this time but many times before this on visualisation stuff) as well as Ramnath, Mike and Russell.