The Hopometer - Visualising beer strength and bitterness

This week's blog post is a team effort and is all about beer! My wife Heather (@highline_online) is, like me, a big craft beer fan so we decided to collaborate on this viz all about beer strength and bitterness. Plus Heather has much better design skills than me.....

Below are a bunch of mostly very hoppy beers (I love me some hops) plotted by their alcohol content and bitterness as measured in International Bittering Units (or IBUs). Introducing The Hopometer.....

Learn About Tableau

Most of the beers come from a list of the top 100 most bitter beers in the world compiled by beertutor.com http://www.beertutor.com/beers/index.php?t=highest_ibu. And to give some perspective we've also added some of favourite slightly less hoppy beers, along with some popular mass market 'beers'. Are any of your favourites on the viz?

We had to strip out some beers from the top 100 because the massive amount of clustering between 8% and 10% alcohol and 100 and 130 IBU's was making things a bit crowded. And we used a log scale for the same reason. You'll see in this range the beers are mostly from the US, and Double or Triple IPA's dominate in that section.

Here's what About.com says about IBU, I particularly like the Example...

Definition:

IBU - International Bittering Units

This is a measure of the actual bitterness of a beer as contributed by the alpha acid from hops. Because the apparent bitterness of a beer is subjective to the taste of the drinker and the balancing malt sweetness of the beer this is not always an accurate measure of the "hoppiness" of a beer. But, generally speaking, beers with IBUs of less than 20 have little to no apparent hops presence. Beers with IBUs from 20 to 45 are the most common and have mild to pronounced hops presence. Beers with IBUs greater than 45 are heavily hopped and can be quite bitter.

Examples:

Not knowing that the barleywine had an IBU of 68, Rachel took a big swig from the glass then twisted up her face as the hops assaulted her taste buds.

For more info on IBU's the are loads of places to look on the web, but this is a good start http://www.popsci.com/science/article/2013-04/beersci-ibus-explained
All that vizing has made me thirsty.....

Sources: beertutor.com, draftmag.com, general googling....



Quick shameless plug. Heather runs a record label Highline Records, and this is the latest release by The Ralfe Band:

A handy use of Attributes in Tableau - colouring waterfall charts

For a long time I've noticed the choice of making a Tableau field an 'Attribute' (as below, between Dimension and Measure) once it is in the view and not really known what to do with it, or had the need.

This week I found myself in a situation where I needed to use a Dimension in Colour, without that Dimension splitting up the view, and discovered one example where the 'Attribute' really comes into effective use. So here's the story:

I was making a waterfall chart at work based on some sub categories and needed to add the category one level up as colour. Since I can't divulge the actual data set I was working on I thought it might be useful to show a similar example using Superstore Sales. If you haven't made a waterfall chart yet in Tableau I'm not going to describe the process here but the online training video is very clear http://www.tableausoftware.com/learn/tutorials/on-demand/waterfall-charts-chart-type-8 . Below is the basic waterfall chart of profit split by product sub-category from Superstore Sales, just as shown in the video. Only I've sorted the categories by ascending profit.

Now in the video they go one step further and colour each bar red or green depending on whether the profit is positive or negative. In my case however I wanted to colour the bars by the categorisation level one level up, in the case of Superstore Sales simply Category. So the obvious thing to do is to drag Category into Colour on the marks card. But then this happens.....

....Eeeek! That's not what I wanted. So what's going on here is that the running total calculation is now being separated for each Category. In other words placing Category into Colour didn't just change the colours of the bars, it also added a an extra dimension by which the calculated fields would be based. So how do we get out of this conundrum? Well it turns out the easiest way is to change Category from a Dimension to an Attribute. Just right click on the marks card and select Attribute.

And that solves the problem, see below, and everybody's happy! The sub categories are coloured by category, but the structure of the original waterfall chart stays intact.

 Now I don't think I've fully realised the potential of how Attribute can be used, but this has certainly opened my eyes to how I might be able to use it effectively in future. Essentially any time where adding a Dimension to add visual clarity is also going to split the data set in way you don't desire, changing that Dimension to an Attribute might solve the problem. I'd suggest if you are interested in this then have a play with the function using all the different chart types, for example see what it does to packed bubbles: