How to Pick up Right Type of Data Visualisation

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Last times I’m designing mostly tools for working with big data. And of course, there are a lot of cases where is required to show data visually. In most cases, I used just my feeling what kind of type to choose. No really, I read a lot of articles, a little bit from Edward Tufte and even googled “how to choose data visualisation type”. But as more I was searching for it, more I was mixed by all these approaches. So I decided to create my sorting of data visualisation types with blackjack and charts.

So, at first, I decided don’t to sort data visualisation types by categories as distribution, range, relationships and so on. It is too fuzzy and mostly obvious. For me, more interesting was define how many types of data could be represented in one scheme. So I started sorting it by those data dimensions. Of course, it was tricky try to collect all types, but I tried to stop me before I went too far. So I didn’t include any 3d graphs, any visualisations with error bars, and so on. But I was trying to skip maximum as possible, but keep enough to build right wireframe.
So after moving Icons around for a few weeks, I found two ways to make it helpful.

Table of Data Visualisation Types

Types are sorted by type of his data dimensions.

For example, you should find the way to show data about categories that have some value and correlation between each other. The most probably you’ll find it in the third column.

Visual Relationships for Data Representation

Types are connected by similarity.

Practically, it is more helpful when you have some assumption what type to use. For example, you are sure that it should be something kind of bar chart. So everything that you should do just go through all types that are next to bar chart. Amount and type of data dimensions will help to fast evaluate it.

You can download full size images and print version (A1 size) here:

In the end, I want to say that I don’t pretend to be Edvard Tufte or even close. I made it just for myself. And it really helped me to find out a lot of nuances. And I decided that would be great to share it and maybe get feedback. So, let me know whether you think. Your feedback is always appreciated!