Using Tableau Public: first thoughts

I am currently beta testing Tableau Public. Essentially Tableau Public let you bring the power of Tableau analysis online. With Tableau public, your audience doesn’t need to download a workbook file that they can see in an offline, software client – they can see and interact with your work directly on a web page.

There are quite a few examples of the things you can do with Tableau public. These are the examples you are given when you start the product:

Tracking Economic Indicators by FreakalyticsA Tale of 100 Entrepreneurs by Christian ChabotBird strikes by airport by CrankyflierInteractive Running Back Selector by CBS sports

And there are always more on Tableau’s own blog. I’ve done quite a few which I’ll share progressively on this blog and on my OECD blog, http://www.oecd.blog/statistics/factblog.

So that’s the context. What’s the verdict?

1. There is no comparable data visualization platform out there.

There are many ways to communicate data visually. Count them: 1320, 2875… and many more.

However these tools have a narrower focus than Tableau, or require the user some programming ability. For instance, Many Eyes uses a certain number of types of data visualization which can be set up in seconds, but which cannot be customized. Conversely, Protovis is very flexible but requires some knowledge of Javascript. And even for a skilled developer, coding an interactive data visualization from scratch takes time.

By contrast, Tableau is a fully-featured solution which doesn’t require programming. It has many representation types which can be deeply customized: every visual characteristic of a chart (colour, size, position, etc.) can depend on your data. Several charts can also be combined as one dashboard. On top of that, data visualization done in Tableau comes with many built-in controls, with an interface to highlight and filter data, or to get more details on demand. For dashboards, it is also possible to link charts, so that actions done on one chart (highlighting records, for instance) affect other charts.

2. The solution is not limitless.

Tableau enables you to do things which are not possible using other packages. But it doesn’t allow you to do anything. That’s for your own good – it won’t allow you to do things that don’t make sense.

There are many safety nets in Tableau, which you may or may not run into. For instance, you can’t make a line chart for data which don’t have a temporal dimension – so much for parallel coordinates. However, the system is not fool-proof. Manipulating aggregates, for instance, can lead to errors that you wouldn’t have to worry about in plain old Excel, where the various steps through which data are computed to create a graph are more transparent (and more manual). Compared to Excel, you have to worry less about formatting – the default options for colours, fonts and positions are sterling – and be more vigilant about calculations.

3. Strength is in numbers.

Over the years, many of us grew frustrated with Excel visual capacities. Others firmly believed that anything could be done with the venerable spreadsheet and have shown the world that nothing is impossible.

The same applies to Tableau. The vibrant Tableau community provides excellent advice. “Historic” Tableau users are not only proficient with the tool, but also have a better knowledge of data visualization practices than the average Excel user. Like any fully-featured product, there is a learning curve to Tableau, which means that there are experts (the proper in-house term is Jedis) which find hacks to make Tableau even more versatile. So of course, it is possible to do parallel coordinates with Tableau.

The forum, like the abundant training, available as videos, manuals, list of tips,or online sessions with an instructor, doesn’t only help the user to solve their problems, but it also a fantastic source of inspiration.

With the introduction of Tableau Public, the forum will become even more helpful, as there will be more questions, more problems and more examples.

 

 

Plotter: a tool to create bitmap charts for the web

In the past couple of months, I have been busy maintaining a blog for OECD: Factblog.

The idea is to illustrate topics on which we work by a chart which we’ll change regularly. So in order to do that, I’d have to be able to create charts of publishable quality.

Excel screenshots: not a good option

There are quite a few tools to create charts on the net. Despite this, the de facto standard is still a screenshot of Excel, a solution which is even used by the most reputable blogs.

excelinblog

This is taken from http://theappleblog.com/2009/12/18/iphone-and-ipod-touch-see-international-surge/

But alas, Excel is not fit for web publishing. First, you have to rely on Excel’s choice of colours and fonts, which won’t necessarily agree to those of your website. Second, you can’t control key characteristics of your output, such as its dimensions. And if your chart has to be resized, it will get pixelated. Clearly, there is a better way to do this.

That's a detail of the chart on the link I showed above. The letters and the data bars are not as crisp as they could have been.

That's a detail of the chart on the link I showed above. The letters and the data bars are not as crisp as they could have been.

How about interactive charts?

Then again, the most sensible way to present a chart on the web is by making it interactive. And there is no shortage of tools for that. But there are just as many issues.
Some come from the content management system or blogging environment. Many CMS don’t allow you to use javascript and/or java and/or flash. So you’ll have to use a technology which is tolerated by your system.

Most javascript charting solutions rely on the <CANVAS> element.  Canvas is supported by most major browsers, with the exception of the Internet Explorer family. IE users still represent roughly 40% of the internet, but much more in the case of my OECD blog, so I can’t afford to use a non-IE friendly solution. There is at least one library which works well with IE, RaphaelJS.
Using java cause two problems. First, the hiccup caused by the plug-in loading is enough to discourage some users. Second, it may not be understood well by readers:

This is how one of my post reads in google reader.

This is how one of my posts reads in google reader.

And it’s futile to believe that readers will read blogs from their home pages. So if all readers can’t show it well it’s a show-stopper.

A tool to create good bitmap charts

So, in a variety of situations the good old bitmap image is still the most appropriate thing to post. That’s why I created my own tools with Processing.

plotter windows

plotter mac OS X

plotter linux

Here’s how it works.

when you unzip the files, you have a file called “mychart.txt” which is a set of parameters. Edit the file according to the instructions in “instructions.txt” to your liking, then launch the tool (plotter application). It will generate an image, called “mychart.png”.

The zip files contain the source code, which is also found here on my openprocessing account.

With my tools, I wanted to address two things. First, I wanted to be able to create a chart and to have a precise control of all of its components, especially the size. In Excel, by contrast, it’s difficult to control the size of the plotting area, or the placement of the title – all of this things are done automatically and are difficult to correct (when it’s possible). Second, I wanted to be able to create functional thumbnails.

If you have to create smaller versions of a chart from a bigger image, the easiest solution is to resize the chart using an image editing software. But that’s what you’d get:

That's the original chart.

That's the original chart.

And that's the resized version. Legible? nah.

And that's the resized version. Legible? nah.

But what if it were just as easy to re-render the chart in a smaller size, than to resize it with an external program? My tool can do that, too.

Left: resized, right: re-rendered.

Left: resized, right: re-rendered.

Here’s a gallery of various charts done with the tool. The tool supports: line charts, bar charts (both stacked and clustered), dots charts and area charts. No pie charts included. It’s best suited for simple charts with few series and relatively few data points.

Impact of energy subsidies on CO2 emissions

Impact of energy subsidies on CO2 emissions

Temperature and emission forecasts

Temperature and emission forecasts

Greenhouse gas emission projections

Greenhouse gas emission projections

I hope you find it useful, tell me if you do and let me know if you find bugs.