When data is made publicly available, chances are pretty good that somebody somewhere will analyse it and come up with some interesting trends. As Apple provides daily sales figures for iPhone applications, it's pretty hard not to get a little addicted to checking how things are going each day. There are now a large number of iPhone developers around, and making my sales data available for public analysis probably wouldn't be of much interest to anyone - after all, these are my sales, not yours. In fact, I'd go so far as to say no one is really interested in seeing another developer's sales data, unless that developer has made a phenomenal rise to the top of the charts. In fact, I'd say most people would only find this interesting in a "how can I replicate this for myself" kind of way.

The end result is that there's probably some interesting things to be seen in the ebb and flow of the iPhone world, but most of it get's missed. With millions of iPhones around the world, and billions of apps being sold, surely there must be some interesting conclusions to be drawn from all that daily sales data? Well, without access to it we'll just have to keep wondering, but what I can show you instead is some analysis of my data. Let's take a look at what's been going on the past few days.

First of all, we have an app called BeerTracker. Whilst this app was never expected to become too popular, it was quick to develop and becomes a fun little point of conversation when enjoying a few drinks. Sales are generally fairly constant, but we recently had a large spike in sales which lasted for just one day. See if you can figure out why:

Now, this is probably not so interesting all on it's own, so let's keep looking.

A second application we are selling is called iEatHealthy. This is somewhat the opposite of BeerTracker, in that it encourages you to eat well and keep track of your health, rather than, well...not doing that. Let's look at the sales data for a similar period:

If we even out the kinks, it's pretty clear that iEatHealthy has had a fairly decent increase in sales over the past few days.

So, what to conclude from this? Well, people like to drink beer on New Year's Eve, so the first graph makes sense. There's bound to be an increased interest in drinking on December 31, which explains the five-fold increase. And what do many people typically do on New Year's Day? Once they're feeling a little better after drinking so much the night before, they make new year's resolutions, and I can pretty much guarantee that a large number of these resolutions would be about diet and exercise - in other words, being healthy. Take a look at this list of popular resolutions on the US Governments website - lose weight, get fit, drink less alcohol. It's all there, and again reflected in the data.

Sometimes graphs and charts are all about measuring how well you are doing, but sometimes you can have a little fun with them too. Can you can spot any interesting trends in the data in your life?