About Slopegraphs and Bumps Charts

Hey everyone! Today’s post answers a request from one of our readers and features two not-so-common visualizations that you can use to make time comparisons: slopegraphs and bumps charts. Although these objects have a very simple nature, they’re also quite elegant and intuitive, so there’s a good chance that they will help you get some unexpected insights in your analyses.

We’ll also discuss one or two tips that can help you improve their readability and make them more meaningful by adding extra context to the data. As requested, the football dataset that we’ve been using lately will give life to our examples! 😉


Slopegraphs are a great way to compare two points in time. However, instead of describing the ups and downs along the way like traditional line charts, they focus on how the journey started and how it ended. This visualization is the perfect candidate for “then and now” analyses (much like that TV show that presents celebrities and how they looked 30 years ago). * Note to self: stop making that kind of references, people will laugh at you. You should recommend Cole’s blog instead. *

When working with these charts, our brain can easily spot patterns and recognize the distinctive slopes of certain elements in terms of direction or magnitude. It is also an intuitive way of showing how the rankings changed from a point in time to another, as the lines will intersect each other and end up in a different order.


In this example, we can visualize the performance of all the teams in the Premier League over the last two seasons. Each squad is portrayed by a line and its position and slope depend on the rank achieved in both the 2015 and 2016 tournaments. In order to improve the chart’s readability, you can highlight the selected team by adding some color and changing its line’s width.


* Fun Fact: This chart is so cool that it made it to the cover of one of my favorite books about data visualization, The Functional Art by Alberto Cairo. Continue reading


Threshold Bar Chart + Christmas Card

One of the biggest problems about being a QlikView Developer is that every time you see an interesting visualization, you immediately start wondering how you can use it in your own dashboards. For instance, a couple of days ago, I was wandering around in Twitter when I saw a message which, apparently, had something to do with the quality of the air in Berlin (sorry, but my German is not very good).


As you can see, the structure of this chart is not overly complex: classic bar chart using a time dimension and a standard expression. However, a simple visual cue composed by a reference line and a different color makes it easier to identify where (of in this case, when) an element surpasses the threshold. In my opinion, it is an elegant and useful way to present data.

Since I didn’t have access to this particular data set, I decided to work with a sales QVD from one of the projects I’m currently working on and, after spending a few minutes in QlikView, this was the result:


I don’t know if this kind of representation has an official name, but I called it “Threshold Bar Chart” <<Patent pending>>. I know… I’m awful at naming things so, if you have a better title, be sure to share it in the comments section! As usual, you can download the QVW with the final chart here. The recipe is simple:

Continue reading