Graphical Tables – An Alternative to Treemaps

Sean blogged the other day about using a treemap to visualize the drivers of the Australian Inflation. He got inspired to create a treemap by an NYT article that used an interactive version of the following treemap:


This chart looks nice on the first view. It makes nice use of muted colors, the shapes look well balanced and certainly the graphic designer did a good job. However, from a data visualization perspective this chart has a couple of flaws.

Ben Shneiderman designed Treemaps to visualize deep directory tree structures.

Ben explained treemaps in an article as:

“Among the growing family of visual analytic tools, treemap are flourishing in organizations that require daily monitoring of complex activities with thousands of products, projects, or salespeople. Tabular reports, bar charts, line graphs, and scattergrams are important tools, but for complex activities where there are numerous sales regions, manufacturing plants, or product lines the hierarchical structures provided by treemaps can be helpful. While tabular displays and spreadsheets can show 30-60 rows at a time on typical displays, the colorful presentations in treemaps can accommodate hundreds or thousands of items in a meaningfully organized display that allows patterns and exceptions to be spotted in seconds.[…] Treemaps are a space-filling approach to showing hierarchies in which the rectangular screen space is divided into regions, and then each region is divided again for each level in the hierarchy.”

The first problem the NYT chart has is that it does not visualize the hierarchy as rectangular areas. The inflation drivers are visualized as asymmetric round shapes. It is difficult to compare the relative size of rectangular shapes but it gets almost impossible for asymmetric shapes. Also does this treemap lack labels for the smaller inflation drivers.

Sean published in his blog post a treemap which does not have the problems mentioned above:image












Ben designed treemaps to visualize thousands of regions, products, etc ; but the Inflation chart only comprises 20 Inflation Drivers grouped into 7 categories. A simple sorted table would do a better job communicating the numbers as Kaiser Fung from Junk Junks wrote in his post.

Inspired by this post and my comment Sean came up with this graphical sparkline table designed with Excel and MicroCharts.


This is already quite an improvement on the treemap, as we can see increasing and decreasing inflation trends and sparklines rather than traffic light colors as in the tree map version. Also it is much easier to read for non expert users.

Some minor things we can improve in Sean’s chart are:

  • We can sort the inflation drivers by Weight, to have the most important ones at the top
  • Changing the area to the sparkline puts emphasis on the trend rather than the absolute value of the values (as the area chart does)
  • Inline deviation charts allow us to visualize the MoM and YoY % changes















Small charts are beautiful

Well, since you are reading this, I’ll assume that you took the red pill, so let’s keep moving and find out how deep the rabbit hole goes.

We saw that people usually design charts larger than they need to be. Why? Is it because we can’t fit the data into a smaller space? No, it isn’t. It is because in smaller charts there is no room for non-data elements, like title, legend, grid lines. In the dominant “Excel chart defaults” school of thinking data is not a priority.

This is a simple exercise that you can try safely at home and demonstrates it clearly. Start by creating a line chart in Excel, like this one:

Excel line chart

You can see the data, right? Now make the chart smaller:

Excel line chart

Here is a fierce territorial competition, and guess who’s winning? Make the chart a little smaller:

Excel line chart

The title and the legend win, as usual. The data must be here somewhere, but who cares?

This chart size is not large enough. Or so it seems. But what happens when we remove some non-data elements? Since we don’t need the legend, and we can put the title somewhere else, we can remove both:

Excel line chart

We are getting our data back! Let’s just leave the data and a simple grid line:

Excel line chart

I used MicroCharts to display the same data using both a line and a column chart:


With MicroCharts, you can add a “normal band” or a reference line that helps you to understand how the data departs from the expected values.

The above charts show percentage change on previous period GDP at market prices in the US (1980-2009). Here is the same data for some selected countries in the EU:


Michelangelo said: “I saw the angel in the marble and carved until I set him free“. Like him, keep carving your chart until you set your data free. The essence of a chart is the patterns you discover, buried under all the junk. By making your charts smaller you are force to remove that junk.

Finding this “essence” is what sparklines is all about.

Information visualization: take the red pill

“To clarify, add detail”, says Edward Tufte.

A richer, more detailed picture, is a solid foundation for your decision-making processes. But to add detail you need a higher resolution display device (be that a computer screen or a sheet of paper), as we saw in the previous post.

Now, regarding the use of resolution, you have a “take the red/blue pill” kind of choice:

  • You take the red pill, accept Tufte’s advice and you’ll get more insights from your data
    • You take the blue pill, buy the stuff most vendors want you to buy and you stay under the illusion of the “professional looking chart”;

Let me detail the blue pill option. According to a large majority of vendors, we should get higher and higher resolutions, yes, but only to admire how eye-catching their products are, how well rendered, even if they display less and less actual data points. For the untrained eye, they may look like a Ferrari, but there’s a Tata underneath.

In reality, vendors and knowledgeable users have different agendas. Users want higher screen resolution to accommodate more data, while vendors want it because it makes they products look… “cool”? Apparently, in the mass market, form and function are strange to each other.
Let me exemplify the problem with a typical pie chart. I already gave my two cents for the never ending discussion around the sins and virtues of pie charts, so I will not do it again soon.

What I want to emphasize is that you can’t have more than five or six data points in a pie chart, but if you add texture to make it glow you will need to remove some data points and enlarge the chart. You need more space (= larger charts) in order for texture to be noticed, and there goes better (for efficient) information visualizations.

Unlike scientific visualization (that usually creates digital models of objects), information visualization focus on abstract concepts, like “inflation rate” or “market share”. You can’t add texture to market share. A chart is a “metaphoric space” where some objects (points, lines, rectangles) stand for an abstract concept, and we infer something from their relative positions in space.

So, you have a large, high-resolution computer monitor and also a high end color printer. You have the option between texture and detail. You can’t have both. Choosing detail you are focusing on the data and how to squeeze the juice out of it. Choosing texture you are adopting a marketing posture whereby you are not selling insights, you are selling yourself (it is an option, and some times you’ll need it). Or worse, in your naivety, you believe that information visualization is just a glowing 3D pie chart. Believe me, it is not.

So, what color is your pill?

More Information per Pixel

This blog is about most widely used BI tool in the world, Microsoft Excel!

Our mission is to connect business users to data such that an average Excel user can build his budgeting application, enterprise dashboard or data warehouse reporting with Excel. Such a solution can span from a simple Excel reporting that pulls data from a sheet database using lookup functions to a full fledged enterprise dashboard that sources data from an OLAP cube & can be browsed interactively in the web.

When it comes to dashboard visualization, we are not of the whistles, bells and gauges school of visualization, we advocate best practice in data visualization and effective dashboard charts like sparklines and bullet graphs.

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