Flowing Data: Visual Representation of Tabular Information – How to Fix the Uncommunicative Table



Visual Representation of Tabular Information - How to Fix the Uncommunicative Table

This is a guest post by Martin Krzywinski who develops Circos, a GPL-licensed (free) visualization tool that can help you show relationships in data. This article is based on a longer writeup which you can find here.

Suppose that you are reading an article and the text refers you to a table on the next page. Before you turn the page, what are your expectations of the table? Chances are, you would like it to communicate trends and patterns. Chances are, too, that it will fail and simply deliver numerical minutiae. You are left hunting around the numbers for a while, only to return to the text in hopes that the table’s data trends will be communicated elsewhere.

Imagine if, instead, the table were replaced by a visual representation that was agnostic to the data domain, sufficiently quantitative to identify patterns and descriptive statistics, and made no assumptions about the kind of patterns that might exist. In this article, I outline one such representation.

Tables are Visual Obstacles

As the saying goes – it’s not the table, it’s you. We are notoriously bad at evaluating quantitative information when it is presented in its raw numerical form. We reach our limit in the ability to glean trends from a table very quickly. Consider the five tables below – the 1×1 table is trivial to interpret and the 5×5 table impossible. Somewhere in between is where you reach numerical overload.

Unfortunately, most published tables are larger than these examples. Due to their size, many fail to effectively communicate their information. They provide the numerical minutiae from which visual representations can be genreated, but on their own they make opaque any patterns that might arise in such representations.

An Uninterpretable Table (read more)

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