Day 7: Sparklines
I’m writing from my favourite cafe in Cologne, Germany. As I walked in, the owner greeted me with a crisp German hello, as he always does. Then he started making my latte macchiato – without me even having to order. It’s the sort of local cafe where everyone knows the owner, the owner knows everyone, and half the customers know each other. There’s free wireless too, and a laser printer for the customers to use. For a bit of authentic Europe-ness, the street the cafe is on is a 2000-year-old road built by the Romans, although it has been modernised considerably since then. They’ve been digging up the road lately to create a new subway line, and they keep finding centuries-old artifacts and buildings underneath.
Looks good, right? It’s a positive number, which means currently I am making money, instead of losing it the way I normally do.
But what if I normally win $5 per 100 hands? Then this number is bad. It indicates that either I am playing worse or my current opponents are better than usual. What we need is to see that number in context. Enter the sparkline. It’s a tiny graph reduced of all the usual graph paraphernalia. No labels, no title, no axes, simply a line showing the ups, downs, and tendencies.
Here’s the same statistic with a sparkline:
The “spark” in the word “sparkline” refers to the glowing red ember at the end. This is important, because it gives the user a visual clue that the value “$1.82” is the latest value. Without this red spark, the user might think the value is an average.
The sparkline in the example above shows me not only that I’m currently winning $1.82 per 100 hands. It also shows me that this is an improvement. It also shows me that I’ve have an ongoing tendency to improve my winnings per 100 hands. All this is shown in a small space.
I’m trying hard with my poker app to make the data easy-to-understand. Without care, I could easily overwhelm users with too much indecipherable information. Sparklines play an important role in achieving that.