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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.

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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.

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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?

12-17-08: I have added some titles to go with my chart numbers, as well as, pointing out the good and bad in each chart.  Please feel free to add your own comments.

From USA Today inspired by the Tableau blog, check out these interesting charts.  Some of these charts are so over-the-top that I laughed out loud.

#1 - Waddayoulookingat?

Bad – 3-D effect puts these two images at about the same size.  One is set back farther and doesn’t start at zero.  Intended to send and will actually send are two completely different actions.

Good – Data labels.  Would a better depiction of the 2008 card be one where the person had a black eye, disheveled hat and a few other bruises simulating the economy lately?  Possibly a foreclosure sign in the background?

#2 MMMM Chips

Bad – where does the data start from (zero on x-axis).  The use of chips for data referring to fruit and fruit cup. 

Good – I’m not alone… value labels and not much else.

#3 Guitar Hero – Chart Edition

Bad – Is he wearing a dress or is there a 6th series? I would have to say the shading of the bars from light to dark.

Good – It’s a decent bar chart with good label use and starts at zero. This is one of the better ones.  Where would laziness fall?

#4 Who’s Smarter (it’s a joke people)

Bad – The grid lines on the paper.  They should have gone with blank white construction paper. 

Good – I actually like this one.  I think the reader can quickly see the difference and understand the point.

#5 Definitely Cheese Head

Bad – Tilted bar chart.  The shading of the streaking ball which was obviously overthrown. The color use is not good.  Definition of “Hot” may need to be a footnote.

Good – Data/value labels both inside and outside the bar aren’t too bad.

#6 ….Ummm….Pass….Next.

Bad – Just about everything from the font color to the cylinder bars.  Could they be more specific or at least have sub categories?

Good – Easy to understand title. The value labels.

#7 Darn Kids These Days…

Bad – Do you even need to ask?  Seriously, just about everything. 

Good – The value labels.

#8 Guns Shooting Sparklines

Bad – There appears to be fluctuations from zero to the value.  Should there be time across the bottom?  Sun background images behind the values labels.  Can they define Smartphone?

Good – The chart title is easy to understand.

#9 Poll Done by Unbiased Gravy Producer

Bad – Does the area count towards the value?  Shadow of the “bars”.  Jumbled labels that are hard to read.  Poor title choice.

Good – Good contrast with the title font. The value labels are easy to read.

#10 Obviously These Parents Haven’t Seen The Game – Vice City

Bad – Beside being a pie chart (I think), the title is poor.  The value labels are hard to read.  It took me a long time to figure out the image is of a video game controller (again, I think).

Good – At least the values add up to 100%.

#11 Whole New Meaning to Split Ends

Bad – Just about everything including, but not limited to the title, attempt at bars, highlighting at the end and starting point.

Good – Somebody thinks outside the box at USA Today. 

Which one is your most/least favorite? My picks are #4 / #6 (really all of them)

Do you think any of these are actually good and would be effective?  I would go with #4, if I had to pick one.  Also, I am definitely guilty (and in the majority) on #2.

I received an email from the service ShareThis with the image below embedded.  The pie chart shows the top sites by category on ShareThis.  On a positive note, at least the labels are clear and pretty easy to read.

Anyone else see similar colors in the slices?  Poor choice or just the popular and most common choice?

Below is a chart that I would not recommend trying to copy for a few reasons.  First, using the little person icon instead of a bar chart distorts the data and adds to the confusion of the chart. 

Next, the sort also adds to the confusion.  The chart is sorted by change in the number of jobs from the previous year and in ascending order.  I would probably have created the chart so the sort was the percentage of people in each sector and in descending order.  Visually, this would have made the chart more organized.  Optimally, in an interactive version, there would be a sort button to toggle between the change in number and percent of jobs.

Finally, I would have dropped the ,000 and just noted that the changes are in thousands.  Better yet, I may have stuck with percentages all around by going with the percentage change in jobs from the previous year.

Source: BusinessWeek, September 8th Issue

Instead of calling them pie charts, we’ll just call them donut (doughnut) charts and make them magically delicious.  Wrong.  These two charts, which appeared in the July 14th issue of BusinessWeek, are some of the worst charts I’ve seen in a while.  Note: in the print version, the legend doesn’t cover up the actual chart.  I’m not sure why this wasn’t fixed in the online graphic. 

There have been many articles and blog posts written on the ineffectiveness of pie charts, so I won’t belabor the point more.  For more information about why pie charts (donut charts with the center filled in) are not a good data visualization option, see the links below.  There’s no point in saying the same thing in a different way.  The timing of this post is good being that Seth Godin recently created a lot of stir about bar charts, which led to more pie chart discussions.

Related books:

Creating More Effective Graphs by Naomi B. Robbins

Show Me the Numbers: Designing Tables and Graphs to Enlighten by Stephen Few

Related links on discussion of Bar and Pie charts:

DSA Insights

Jon Peltier

Peltier Technical Services

Jorge Camoes – Charts

Juice Analytics Original

Juice Analytics

Stephen Few

Edward Tufte

Junk Charts

Note: the first pie chart is credited to William Playfair roughly 200 years ago.

I just can’t seem to help myself when it comes to sharing beauties like the pie chart below with my readers.  The pie chart was found here.  Yes, it’s colorful.  Yes, it’s an example of pimping your chart.  And finally, yes, it’s extremely ineffective.  Just recreating this chart accurately was nearly impossible because of the small slices that are not even visible.

It takes entirely too long to go from legend to chart, legend to chart, legend to chart, (you get the point) to cross reference the two.  A simple bar/column chart would have been a much better choice.

Here is my version that took me longer to figure out which values referenced which slice percentages than creating the actual chart.

Suggested Reading:

The Visual Display of Quantitative Information, 2nd edition

Visualizing Data

Show Me the Numbers: Designing Tables and Graphs to Enlighten

Creating More Effective Graphs

A few months ago, I wrote about an alternative way to present fractions (parts of a whole) instead of using a typical and flawed pie chart.  The first graphic below comes from BusinessWeek and the second one is DSA’s Excel created version.

Jon Peltier (Microsoft MVP) of Peltier Technical Services and PTS Blog, recently wrote me to tell me about a workbook in Excel, which contains VBA code to create something similar to our dollar visualization.  The results, which only took me a few minutes using Jon’s workbook, are below in the third graphic.  It’s a fairly useful tool to do something different for your audience.

Finally, the last graphic was created from a similar workbook in Excel by Andy Pope, Microsoft MVP.  The workbook (link below) contains instructions regarding how Andy was able to accomplish splitting the image.

In the related section at the end of this post are links to the workbooks and web sites of the creators.  Feel free to check them out!  If you are interested in how I created the DSA Insights version, feel free to contact me and I can walk you through it.

Thank you Jon and Andy!

BusinessWeek Version:

DSA Insights Excel Version:

Jon Peltier Excel Version with Easy Macro:

Andy Pope Excel Version (different Picture) with instructions:

Original Post:

Spending InfoVis, DSA Insights

Resources:

Jon’s Workbook, Jon Peltier

PTS Blog, Jon Peltier

Version of splitting a graphic, Andy Pope

Andy’s Workbook, Andy Pope

The Back of the Napkin: Solving Problems and Selling Ideas with Pictures at Amazon.com

The old stack ‘em up trick…

This graph is renders beautifully. From the x-axis labels being shortened to the lack of chartjunk in the form of gridlines and excessive tick marks. The colors definitely make the chart stand out. I don’t think many would argue that point.

If you take a look at an earlier post, I featured another visualization taken from the same page of BusinessWeek’s January 28th issue. As you will see, the color scheme for the whole page was green and yellow.

This graph shows two points very well!

1. The first point is the trend of “The Detroit Three” shown in green below. I can quickly and accurately see the initial jump, plateau and then gradual decline.
2. The second point that is definitive is the total for both the Foreign series and The Detroit Three series. The total sharply rises until 2000 and then starts a gradual decline over the next seven years.

What is almost impossible to determine is the change in Foreign sales from year to year and over the entire sixteen years. Intuitively, I can see that after about year 2000 the yellow portion is larger because the total is about the same while the green section gets smaller. Simply put, the reason a stacked bar chart is a poor choice when comparing more than one series over time is due to the baseline not being the same for the second (yellow) series.

For this example, the point isn’t what the total sales were over sixteen years. The point is how one compare to the other. I know this from the title of the page being, Detroit is still behind, despite hard-won gains.

Point: When showing more than one series over time (time being the key here) the most logical choice should be a line graph. I’ve seen some horrid stacked bar charts with many more segments. On a rare occasion, I may use a stacked bar chart only when time or trending is not a factor.