When we are creating charts, we tend to want to put all the information we possibly can into them, thinking that it will be helpful, but we are relaying on the end-user to see what we see and understand the same things we did from the data, as if it was obvious, but the way people see data changes from person to person, so the best way to convey information is to make it as obvious as possible, so the message is not lost in a jumble of data. To avoid this, we can use a few tips and tricks to make our main point stand out.

When creating charts sometimes due to the nature of the data we have too many details, whenever this happens, it is better to select the most important feature and highlight it with colour, whilst at the same time sending the rest to the background, using colours to convey importance.

Let us explore the following example. We want to see Sales by Month for our customers so we can compare their behaviour.

In this graph we cannot really see the behaviour of the different customers because there are too many to differentiate, it is confusing, and probably useless as it is. So, how do we make it better?

Let’s start by using colour. Colour is a pre-attentive attribute, which mean it can catch our attention subconsciously by just looking at it. Now let’s say we want to highlight the performance of one of our costumers (Sean Miller) for example, we can start by creating a set within the Customer Name field and statically add the member we want to highlight to this set. Then we can use this set in the colour mark (remember sets only show you IN/OUT outputs) to only colour the members of the set.

But naturally it will plot our set member against everything else, which is not what we want to see

Nevertheless, we can expand this again, bringing Customer Name back into details

It is clearer but we can do better! Let us do some polishing by muting some of the background colour to a lighter grey by clicking in the colour legend and changing the group colours, the ‘Out’ in light grey and the ‘In’ in an intense warm colour that commands attention. We can also adjust the size of the lines and make our customer of interest bigger and bolder. Using the same set but dropping it in Size on the Marks card we can change the size of the individual customers in our set.

Now it is looking better, but there are still some details that would make it even clearer for the viewers. We can adjust the title, add subtitles to give more information and even add some annotations, as well as formatting the chart and removing gridlines and redundant information.

Finally, we have used colour in the title to focus our attention on the Customer we are interested in, and we have added annotations to some key points as well as deleting the axis title (redundant) and describing the customers behaviour in the subtitle to drive the point home!



With these few helpful tricks, you can make your charts understandable and easy to read!

The Data School
Author: The Data School