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Below you will see a stacked column (vertical bars) chart that has nine different segments covering eight months.  I have absolutely nothing against HubSpot and actually think they have some great services, tools and products.  I am simply using their chart to illustrate the problems with stacked bar charts and some alternatives.

I can think of a few reasons off the top of my head as to why people would use stacked bar charts. 

1. To show how each segment changes over time
2. To illustrate parts of the whole at any given time
3. A combination of 1 and 2 above

The problem is that a stacked column chart is not good for either of these requirements.  My feelings on these charts is not really anything new, as I’ve stated before on this post and also this post.  In my opinion, after you get beyond two series with like scales, a stacked column chart is pretty and pretty useless. 

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A special thank you goes to Elissa Fink of Tableau for providing me with a demo of Tableau Public.  With being a big fan of Tableau desktop, it should be no surprise that Tableau Public impressed me for many of the same reasons I like the desktop version.

Today is the official release of Tableau Public and the latest version of Tableau Desktop 5.1.  Below you will find some quotes from today’s press release:

SEATTLE, WA, February 11, 2010 – Tableau Software today launched a new product that brings public data to life on the web. Tableau Public, available for free, lets anyone who posts content to the web easily create interactive visualizations and publish them to blogs, web sites, Twitter feeds or anywhere online. Instead of viewing static charts or tables, Tableau Public lets people answer questions and share data interactively on the web.

Current alternatives for sharing data online are clumsy. Typically, data is pasted into tables and lists, or posted as files or catalogs that are difficult to use. Available at Tableaupublic.com, Tableau Public is helping to solve this challenge – bringing data to life on the web for ordinary people. With its interactive visualizations and dashboards, Tableau Public helps people start conversations based on data that is useful, beautiful and shareable. No special plug-ins are required, all that’s needed to see and use the data is a web browser.

In conjunction with the general availability of Tableau Public, the company is also releasing today Version 5.1 of its Tableau Desktop and Tableau Server product suite. Version 5.1 provides more analytic richness, better publishing, and increased scalability and performance. Analytical features include reference bands that provide context to a user’s analysis, bullet charts to evaluate related data, and intelligent data labels to call out the most critical data. New publishing features include rich formatting, streamlined toolbar design, more filter options, and a flexible layout.

I have yet to try out the newest version, 5.1, but I did see that it will have the ability to produce Stephen Few’s famous Bullet Charts without any tricky workarounds.  I can tell you that I’m excited to start using version 5.1.

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In the February 1, 2010 edition of BusinessWeek, I found the illustration shown below.  It certainly contains some good information and data that can be easily read.  My question is, would you consider this a Information Visualization, Data Visualization, Information Graphic, Statistical Graphic, Chart/Graph or something else and why?

Sorry about all the polls lately, but I think this is an easy way to respond without having to comment. 

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Also, please feel free to comment with additional insights.

Note: RSS readers have to go to the website to view the poll.

Not too long ago, I got a tip from someone on Twitter with a link to a site called Verifiable.com.  Upon further investigation, I learned that this site is similar to Manyeyes.com in that you can upload a data set and, using the tools on the site, create data visualizations. 

At first glance, the site seems somewhat plain.  After digging into what the site is about, I quickly learned that they utilize sound and popular theory in the data visualization field.  On their about page, the first line that explains the features is:

“A clean, low-chartjunk philosophy — no shadows, no pie charts, no 3-D bar graphs, just the ink you need. [verifable.com]”

Well, simply reading that peaked my interest because they use similar principles that I follow when creating charts/graphs.  No frills.  I like the fact that you can create charts that don’t have excessive grid lines, shadows, weak labeling and limited charting options.  Below you will see a few examples from their site.  You can also follow the links to see the visualizations in an interactive environment.  As you will see, there is a lot of data (hover over), many different options and some good visuals.  Granted some of the charts I had no idea what they were trying to show, but in general this site gives you a seemingly good tool to apply charting/graphing best practices.

[Interactive version]

[Interactive version]

Verifiable also offers a Pro version of their tool where you can keep your data and visualizations private and receive premium support.  The cost is minimal with the Pro version going for $29.95/year. 

I didn’t try to upload a data set to give the site a full trial, but it definitely looks interesting.  I am not sure how much demand there is for online data visualization using a tool like Verifiable.

Below is a great example of the wrong use of color in a column chart.  Use color to differentiate between segments, but don’t use it when time is on the x-axis for the different days.

A better use of color may be for each quarter within the year.  Using the chart below, it would make more sense to have every first week of the month always in one color, like blue.  Then, at least you could easily compare the first week of each month quickly.  I’m not even going to touch the chart title not matching to what is actually being displayed in the graph – days vs. weeks.

You really can’t make the color mistake if you used a line graph, just saying.

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The most recent copy of Information Management had the image below on page 8.  What’s funny is the person figure on the left looks like it’s wearing pants.  Oh wait, those aren’t pants, the blue is part of the data visualization.  The person on the right looks to be wearing orange work boots or ski boots for that matter.  The article by Julie Langenkamp is interesting and discusses how small vendors tend to rank much higher than large vendors in product support and other areas.

[image source]

[image source]

It appears that small vendors scored better than large vendors in every single category of complaints as shown in the chart above.  In the chart below, you will see that small vendors appeared to provide more benefit to the customer/client than large or medium vendors.

[image source]

There’s a lot more to the article if you are interested in business intelligence. 

One of the benefits I truly enjoy is having USAA as my insurance company.  It only took me one phone call to their customer service center to know why they consistently rank in the top of companies for customer service.  I can think of a few big companies that could learn a lot from how USAA treats their customers/policy holders. 

In their recent magazine, I quickly noticed the chart below that is called, "The Snowball Effect" while flipping through.  The heading that was cut off states the following:

"What’s the hardest-working investment tool you can use? The power of time. Beth, Bob and Bridget all invested $2,500 at the same 6 percent rate of return.  But see how compounding made Beth’s account grow? That’s the value of starting early."

Going back to high school and college one of the first lessons one learns is the time value of money and compounding effect.  I won’t get into that, but what I did want to touch on is the chart below that left me speechless for a bit.  There are so many things wrong with it that it wasn’t even worth taking out my red pen.  

I recreated the data from the chart in Excel (shown below) and used fictitious numbers for the middle of the graph.  Each person starts with the same money and each has an end amount.  So I basically filled in the blanks.   I know my chart doesn’t have Beth with her arms raised in celebration or decimals, but it’s definitely a lot cleaner and easy to understand.  This isn’t rocket science, is it?

Below you will see a column chart that appeared in the weekend’s print edition of the Baltimore Sun.  It’s no secret that they used a gradient fill on the columns to give it the fading appearance.  I’m not a big fan of the gradient fill on the 2009 columns, but this could work for the previous year’s numbers (2008) if the intent was to minimize the prior year.  I doubt that was the case as I’m sure they were trying to make the chart "pretty" or different than the default setup.

Below you will see a replica that I made using Excel and the fill effects formatting option.  It looks alright, but something still isn’t right.  What is the problem with this chart?

The problem is the y-axis and the scale that was used.  I don’t think this is a straight out misrepresentation in order to mislead, but it could be.  That’s the risk you face when manipulating the axis.  Yes, the columns take up a lot of space when the axis starts at zero, but that’s the correct method here.  To help illustrate my point, check out the exact same chart (below) with the y-axis starting at zero.

This version using the correct axis setting accurately shows that October, year-over-year, is not three times as much, but only about 1.5 times greater.  Also, look at the trend of the first replica chart.  The upward trend definitely has a greater slope compared to the replica with the correct axis.  To help prove this visually, check out the side-by-side comparison below using a trendline in the chart.  The slope of the chart on the left is much greater than the one on the right.  If you were presenting this data in something like PowerPoint or SlideShare, and quickly went to the next slide, the audience might not catch the axis starting at 5 and the steep trendline would be the point taken from the data.

Furthermore, forget the gradient fill and go with something like the chart below if you want to highlight the current year.

I recently came across a few iPhone applications (Apps) that allow a user to view or edit spreadsheets in Excel.  Some have pretty good reviews and others, well, not so good.  I think there is some benefit to being able to view data visualizations, charts, graphs, spreadsheets and reports on your phone.  I think the capability is probably limited as it would be near impossible to do large scale spreadsheets on a phone.  Also, the screen size would limit the size and amount of data that could be displayed. 

Here are a few spreadsheet type apps for the iPhone:

• Quick Office
• ispreadsheet
• Mariner Calc

In my opinion, the best option is still to view web-published visualizations from a company like Spotfire or Tableau to see near real-time data, trends and visualizations.  Let’s forget about trying to build spreadsheets on your phone, because that isn’t going to happen.

A little while back I featured the stacked column chart below in a post that discussed the ineffectiveness of its design.  More often than not, a simple multi-series line graph can do a better job at visualizing data compared to a stacked column chart.  The other option is to go with is a panel chart, also known as small multiples. In the R program, this type of visualization is more formally called a Trellis Display. 

Besides the overpowering and inconsistent labels, I think the Baltimore Sun did a good job with its recent display of the percent change in the number of passengers from 2008 to 2009.  It may have been better to stick with the airport codes, like BWI, instead of writing out the airport names, but let’s not nit pick.  I bring this topic up again because I think small multiples or panel charts can be much more effective at visualizing data and, in my opinion, are under utilized in the business world.

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There has been some great work done by a few experts in the Excel and R fields on creating panel charts.  Here are a few resources that have examples and information on how to create panel charts in Excel and Trellis Displays in R.

• Peltier Tech Services
• Process Trends
• Charts & Graphs