PCA 3D Visualiser

You'll need Adobe Flash Player v10 or later in order to run PCA 3D Visualiser. You can get the latest version of Flash Player here.

Scenario 1: Solvents

 

For example, imagine you’re a chemist who has run out of Triethylene Glycol at a crucial stage of an experiment – disaster beckons, but a quick play with the Solvents sample dataset in the PCA Visualiser 3D immediately shows you that Diethylene Glycol, Formamide and Cyclohexanol show very similar characteristics. After confirming that this is indeed the case you have a rummage in your stock cupboard and discover a batch of Diethylene Glycol, and the crisis is averted!

 

Scenario 2: Superheroes

Similarly, you might lie awake at night wondering how you’d match up a boxing match between your favourite Superheroes…. The Silver Surfer has expressed an interest, so you decide to find someone who is the polar opposite, to ensure an interesting contest: the Superheroes sample dataset in the PCA Visualiser 3D instantly shows you that the perfect candidate would be the Invisible Woman. All you have to do now is find her, which is easier said than done…..

 

Enter your own data!

Your data is not stored or monitored in any way, and there is no sign up or registration required.

The Visualiser will take the PCA output from the statistical analysis package of your choice – simply paste it (in tab-delimited format) into the opening form, and you’re away. You’ll be prompted to define which columns you wish to visualise, and if required your data will be automatically normalised. While this tool was developed with the aim of visualising PCA data, it can of course be used to visualise any 3D data points of your choosing!

 

If you’d like any further guidance on how to make the most of this tool, or if you have any feedback on it, then we’d be very happy if you contact us. Happy visualising!

 

About the PCA 3D Visualser

Principal component analysis, or PCA, is widely used to reduce the dimensionality of datasets into a set of uncorrelated variables. This is all well and good, but how do you actually use these variables do better understand the relationships between your observations?

The easiest way to understand the relationship between two variables has always been to plot them on an XY scatter chart - but what about three variables? Here's our PCA 3D Visualiser, which allows you to plot, visualise and play with your data to help you better understand it.

We have provided a couple of sample datasets (featuring Solvents and Superheroes) to help you get started with the Visualiser, but where it really comes into its own is when you use it with your own data (Scenario 3 above!).

When you’re in the visualisation screen then things really start to get interesting – you can click and drag on the plot to rotate the data points, you can click on a point to view its properties, you can filter the dataset, and lots more besides!

We hope that our sample datasets will be useful in getting you going…