Visualising activity on a project

Friday 5th March, 2010

We’ve got a few new faces here and are saying goodbye to some old ones, so now seems like a good a time as any to look back at what we’ve been doing. Below is a clipe from YouTube showing activity in our code repository since we started a fresh one in late 2008.

If you’re interested it was created using Code Swarm and MEncoder.

Visualising the age of consent

Wednesday 10th February, 2010

In the course of my usual data-immersion session in my RSS reader of choice I came across a short but thought-provoking post by Stephen Law linking to some data on the age of consent.

Being a big fan of data visualisation I decided to have a go at representing the data in a way that can be more easily absorbed. So, armed with the source data, a list of ISO country codes, and the docs for the Google Chart API, I started playing.

The biggest question when visualising data, just like with statistics, is deciding what you’re looking for. This data is complex enough to be difficult to show in its entirity, involving maybe a dozen or so possible pieces of information for each location.

Here I’ve opted to look at the difference between the age of consent for straight couples and gay couples.

Blue indicates larger differences between straight and gay ages of consent (or illegality)

I Love Visualisations

Thursday 20th November, 2008
I love visualisations

Visualisation du jour

I love visualisations. Not in a short-lived fiery way, but in that way that’s based on mutual understanding, respect for each other’s space, and not hogging the remote control.

A good visualisation can sell an idea. A good visualisation can let the human eye’s abilities take a set of data and run with it. A good visualisation can inform a decision, or even prompt entirely new questions.

Visualisation of the day

I’m not going to try and explain this visualisation on the left, partialy because it wouldn’t make much sense to anyone but one or two people I work with, but trust me, I found it really useful.

It reveals quite clearly the aspects of this data I wanted to isolate, highlights where I’m going wrong, and has told me a few things about the underlying system that I hadn’t realised. The only thing I’m not happy about is that it’s not in colour.

I don’t think I need a second opinion. I’m a data geek.

Update: Have now given in and created a colour version where the green RGB value is set to intensity, and red is proportional to standard deviation. It rocks my dweeby little world.