I’m not going to pretend I’m the master of data visualization. I’m also not going to say that I can easily tell the difference between a good chart and a bad chart, sometimes things that work for me don’t work for everyone else and that’s fine. But there are some data visualizations that are just… bad. Like objectively, somebody should feel ashamed that they ever let other living people see these charts. These data visualizations are my favorite to look at because while I may not be the master of data viz, at least I’m not these guys!
Let’s take a lot at some of these examples, shall we? All of the bad data visualizations come from viz.wtf. First up we’ve got my personal favorite, because the trouble with this data visualization is easy to miss unless you’re looking closely.
So, supposedly 1/3rd of the operating budget goes towards financial aid. If the budget is 60 million, like the sign says then 1/3rd of that is 20 million, no problem there. The problem comes from the fact that the 20 million, indicated in yellow, is actually only making up 1/4th of the pie chart. This is an easy fix; just increase the space of the yellow to make it equal 1/3rd of the pie chart, but also in the title they forgot to add the rd to the 1/3rd, which might not even be bothering anybody else but me in all honesty.
How can we fix this? I’ve got a better version above and I think it’s probably 600% better, hey if the first data viz can make up numbers then I can too. In the budgeting pie graph the correct proportions are clearly labeled and most importantly all match up with their respective percentages. In addition to that there are graphics to go along with each percentage and goes into far more detail than the previous chart.
Can you hear the bells? I can’t. My next example of a no-seriously-how-did-anybody-let-this-get-published data visualization looks pretty at first glance but upon closer inspection crumbles like a cheap wedding cake.
The sizes of the bars have no correlation to the number on them, some of the bars are missing icons and the numbers would have been in declining order if they hadn’t decided to stick the 2% additional costs at the bottom. Seriously, why is that there? It makes me so mad.
Additionally, writer for Tableau Andy Cogreave has this to say about using color,
Color is one of the most tempting things to play with when building a dashboard. It feels productive, and it seems like you’re adding value by making things colorful. But get this: unnecessary color does not add value.
Sure those gradients are pretty but they do little to help the visual. Perhaps it would have been more effective if the largest number was the most saturated form of the color green, then became more translucent as the number got smaller. This would inform viewers that less money was being spent as the list continued.
Can we get a wedding planner in here? We need some serious help. Luckily I’ve got an upgrade below, kind of like your high school boyfriend compared to your college boyfriend. Not only does this chart go into more detail about hoe much money you can really expect to spend, the numbers and the size of the bar are perfectly sized! The only problem is that this chart doesn’t keep the numbers in descending numerical order, but your future husband isn’t going to be perfect either so who are we to judge! That’s a saying right? I’m obviously not married.
Lastly I’ve got a data visualization that honestly gives me a headache if I stare at it for too long. So, I’m going to make you look at it too.
The lines are all the same color and pattern, making it almost impossible to distinguish which line is which. Except for the SpaceX line which is, for some unfathomable reason, really thick. Another problem I noticed is that the years jump from 2008 to 2017 so if I wanted to know what was happening in 2010, I wouldn’t really be sure of the correct data because it’s not listed and I’d have to make an educated guess.
I’ve got a great fix below from the Rutgers University Polling Institute. The lines are all different colors, the months easy to distinguish by way of the dots on the lines and having it clearly listed at the bottom and there is a key at the top to further clarify. In addition to that no line ever goes over the top percentage (70%) which happens in the original example, with the Russia Rocket launch number going much higher than the max possibility of 20.
I know earlier I said I wasn’t the master of data visualization but this is actually a really great exercise in becoming more comfortable with what is and what isn’t good data viz. Being able to recognize what looks good and what doesn’t is a great way to subconsciously transfer those good design decision into your own work later. And I know that everybody makes mistakes, but it does feel good to look at some of these examples, because now I’m confident that I will never make those specific mistakes. There’s plenty of other mistakes for me to make!