Have you ever had one of those “of course I can do that in QlikView” moments? As a Qlik developer it’s not uncommon to find yourself struggling to create a chart or pull off a complex script that nobody asked for, but for some strange reason, you decided to tas a personal challenge. Well, I just had one of those moments.
I couple of days ago I was wandering around my usual blogs when I found a post by Alberto Cairo where he talked about an interactive visualization created by the FiveThirtyEight team regarding the political preferences in the United States. [By the way, if you don’t follow those blogs you are missing a lot of great stuff!]
Besides being a stunning way to present What-If scenarios, I liked the usage of the Tile Grid Maps, which have become a pretty popular visualization lately. What is a Tile Grid Map, you ask? Well, think of it as a mix between a choropleth map and a table heat map. If you want to see more examples, you can visit Bloomberg, The Washington Post or The New York Times.
It is true that most of the times we strive for more accurate charts but ironically, this technique’s boon is that it disregards the actual size of the regions and translates them to equal-sized shapes (in this case, squares) so it becomes easier to see even the smallest areas. Therefore, this solution is excellent when the geographic size is not the most important thing, but maintaining a loose spatial distribution is.
So anyways… In today’s tutorial we’ll build something like this:
Hello everyone and welcome to our first post of the year. Today, we’re going to work with a simple data set from the Barclays Premier League and see how number formats, simple visual cues and other chart options can help us present better rankings:
But before that, let me take a minute to share a couple of things I’m really looking forward in 2016. As Qlik fans and data enthusiasts, maybe you will relate to some of them:
- Masters Summit @ Milan: The dream team will be offering new workshops with the Qlik platform in one of the most iconic cities of the world… Am I the only one excited?
- Three long-awaited book titles in my list are finally coming out this year:
- Data Visualisation: A Handbook for Data Driven Design, by Andy Kirk
- The Truthful Art: Data, Charts, and Maps for Communication, by Alberto Cairo
- Mastering QlikView Data Visualization, by Karl Pover
- Deploying more projects with QlikView and R: I’ve been working in small apps that mix QV with machine learning, predictive models and text mining in R and the results have been amazing (more posts about this topic in the following weeks). However, I’m pretty excited about implementing them in large scale.
- Seeing how Qlik Sense evolves: I have to admit that my inner System Administrator fell in love with Sense from the very first minute. However, as a developer, data analyst and especially as a designer, I think that it still has room to grow. Nevertheless, I’m eager to see how this platform matures. I think 2016 will be a crucial year for Sense.
Becoming a Qlik Luminary: Ok, we can take this one out of the list already. It looks like my blog, my Twitter account (which you should totally follow) and writing a book about QlikView while selling and deploying projects for all the Master Resellers in the country for the last 6 years are not reason enough to get that title. Man, I’ve trained over 250 students in the art of developing QV apps! But maybe next year…
C’mon, maybe even Leo might get an Oscar this year! But anyways, on to the post. Today’s data set is pretty simple, we have the best 6 teams of the Premier League and how many points they scored in the last two seasons. The idea is to display the rankings of both tournaments and highlight the movements between them. [Download all the materials here].
Even though the number of points is a valuable metric by itself, the way this competition works makes the rankings (the way one team compares to the rest in the current season) more relevant. For instance, let’s focus on Arsenal for a minute. As you can see, even though they scored less points in the most recent tournament (75 against 79 from last year), they improved their position by going from the fourth to the third place.
‘Just Qlik it’ is a new section of our blog that focuses on sharing useful components… that kind of objects that are not incredibly complex, but are easy on the eye and convenient to have around.
On our first delivery, I’d like to share a double gauge that gets along pretty well with comparisons between ratios (for example, net and gross margins).
You can easily copy, paste and configure this component by modifying the colors and formulas in the Presentation tab. Just remember that there are two independent gauges and that you should include your formula in the Lower Bound of the second segment.
You might also want to change the Min and Max values allowed. If your numbers are usually between 0% and 30% there’s no need for a gauge that goes all the way to 100%.
[ Download File ]
I often use this kind of representation to highlight the main KPIs of the tab and reinforce them with a detailed table in the lower part of the screen. In the downloadable file, most of the objects are dummies created only to Continue reading