Regular readers know that English is not my mother language , but are kind enough to forgive me for my many mistakes.

I am always willing to learn and today, while researching for an upcoming post, I came across an expression  I never heard before: “spiffy charts”. I felt in love with “spiffy charts” the moment I read it. And I read it straight from the horse’s mouth (I mean Microsoft).

If you don’t know how to make a chart and are keen to preserve that blissful ignorance, I highly recommend Microsoft Office Online Training, specially the module Create a professional looking chart (regular readers also know how I love “professional-looking charts“). You’ll learn how to “customize your charts to make them more attractive, memorable, and effective”. This means useless charts.

So, let’s see how to turn a humdrum (this is a new word, too…) chart into a spiffy one. First, to declutter your chart remove grid lines:

As you know, grid lines are useless, specially if you don’t care about the data. I would remove the gray background and the border around the legend. And I’d give the chart a more descriptive title to tell the users what they are seeing, but that’s my personal taste.

Then you should remove the y-axis and add labels to each column, further “decluttering” the chart. At this point the readers start sighing for a nicely designed chart table.

Want to give your chart a little more “flair” and make them more “professional-looking”? Just add a gradient fill and a subtle shadow:

Now comes the spiffy part. Imagine that you have a 3D column chart with two series, and one obscures the other. What do you do? No, you can’t remove the stupid 3D effect (remember: you want to make t spiffy chart, not a humdrum one). Well, all you have to do is to change the order of the series:

Much better now, don’t you think? They accept that 3D charts “can be more attractive, but sometimes more difficult to read accurately” (surprise, surprise!). Apparently that’s a detail in the grand scheme of things. You are excused from making accurate charts if you are making professional-looking ones.

So, what else can you do to improve your chart? Ah, yes: the y-axis in a humdrum column chart always starts at zero. We don’t want that, do we?

Now you know how to make inaccurate, professional-looking, spiffy-with-a-flair marmalade charts. Please go straight to the kitchen, make some real marmalade and forget all you’ve learned about data visualization in the Microsoft Office Online Training.

(This is not a real Microsoft Office Training site, is it? It must be some kind of spoof site, and I fell for that trick. Right? Right?)

Sigh…

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Post from: Jorge Camoes' Charts.

Spiffy Charts

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Let’s face it: you can’t prove you have a good chart. Unless you can convince your employer to deploy at least two different formats/layouts and are able to compare results, you can say “this is a good chart” but that’s an act of faith, not an act of science.

It’s True Because It Rhymes

Information visualization experts like to evaluate a chart based on its compliance to some more or less accepted standards (Tufte’s data-ink ratio, for example). That’s like saying “it must be true because it rhymes”: the truth is defined by the language itself, not by the real world. Now, please close the curtains of our ivory tower…

I know, it’s not easy to assess the efficiency and effectiveness of good displays. They look natural and obvious, undeserving of praise and, probably, boring and uninspiring. Compare these charts:

This is a true story: users wanted to evaluate sales territories, one at a time. Color-coding each bubble (Example A) was pointless, while Example B provided context without distractions. Guess what chart they would choose if they were allowed to… (happy ending: they reluctantly accepted Example B). (A word of advice: if you are looking for a promotion, a kindergarten chart variety always outperforms a “serious” chart.)

If your chart is doing a good job at helping people, no one will actually be aware of the chart’s role at making sense of the data. That’s why it is so hard to find good examples of data visualization using standard charts. If people actually like them, they like them because of their usability and/or interactive features.

When Stephen Few asks the readers “true stories about the benefits of data visualization” that’s almost an admission of impotence.  He should have hundreds if not thousands of good examples to share with us, right? Well, I know there are many examples out there, but I can give you none, sorry. Is data visualization some kind of astrology? I know it works. Why? Because I have faith. (On second thought, he is not asking for good data visualization examples. It really doesn’t matter if you use Tableau or Xcelsius, and that’s a relief.)

Opening the Pandora Box

Ultimately, what makes a good chart is how it resonates with your audience. Assuming that your are not unethically distorting the data, a chart that forces people to act is better than another one that only makes people aware of the subject.

If a single chart can save the world, it will not be a Few’s or Tufte’s 100% compliant chart. It will be a glossy Xcelsius pie chart.

(Wow, that’s depressing…)

If you read this blog that’s a clear sign of intelligence and sophistication . Unfortunately, you are not representative of the typical data visualization user and/or producer. The real world loves pie charts and doesn’t understand scatter plots.

Here is my Pandora box: give the audience what it expects and understands, even if that hurts your data visualization soul (OK, give it 90% of what it expects and use the remaining 10% to educate it.)

Cultural Relativism? Not So Fast.

Please don’t misrepresent these arguments. I’m not saying that all charts are born equal. There is a reference point. A chart that maximizes insights, removes clutter, uses color wisely and clearly shows the patterns hidden in vast amounts of data, that’s probably a good chart and that’s what you should aim for. And yes, you should avoid pie charts.

If you present some sophisticated charts to your unsophisticated audience you’ll lose it. Relax. Draw a line but don’t forget the candies. You can take a horse to the water, but you can’t make him drink, unless you give him some sugar cubes…

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Post from: Jorge Camoes' Charts.

Is Data Visualization Useful? You’ll Have to Prove It.

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If you want to add animation to your charts that’s a clear sign that you have too much free time. Go out and play with the kids instead.

Yes, animation is a powerful attention-grabber, even more powerful than a glossy 3D pie chart in Crystal Xcelsius. And yes, it can actually be helpful (from time to time). But.

A good example of animation in data visualization is the famous Hans Rosling’s TED presentation, where a long-term pattern is clearly seen (at min 4:00):

This works well because the trend is easily identifiable and you don’t care much about the details. It would be much more difficult to make sense of this data if there were multiple trends and short-term variability. (More on the use of animated charts.)

After watching this presentation people often ask me: “Wow! Can we do that in Excel?” Wrong question. The right question would be “Wow! Can our data do that?”.

You can always create a simple animation in Excel but it’s hard for a non-programmer to get a smooth transition effect. Here is an example:

Although you can see a pattern emerging, you would need to add a complex interpolation routine to make it look better (read Jon’s post to see how a simple interpolation can be used).

Animation is better used if there is a pattern to be discovered, but you need something more: the ability to interact with the data. You must be able to stop, go back, get the details. While you can create a simple animation effect with a for/next loop in VBA, interaction with the chart is much easier using a Google spreadsheet with a motion chart:

(This is just an image. Click here to play with the chart.)

Dynamic Charts in Excel

In Excel, instead of creating a VBA routine, consider using a scroll bar linked to the value you want to change (year, for example):

Using a scroll bar adds some level of interaction because you can scroll back and forth, pause and examine the details for a specific year. Obviously, you need to change the chart data source dynamically.

Let’s recap how to create a dynamic chart in Excel. You can do it by changing values or by changing the data source itself (using a different range).

Option #1: Copying the Data

The range A1:E11 is our data set and we are comparing regions. Moving the scroll bar at the bottom changes the year. Column F is our data source. You can enter this formula there:

=OFFSET($A$1,ROW()-1,MATCH($A$13,$B$1:$E$1,0),1,1)

ROW() gets the current row and MATCH() returns the position of value 2002 (A13) in the range B1:E1. So, the formula in cell F2 reads something like this: start at A1, go down one row, go right three columns and get the data in that cell (range of width 1 and height 1). When the user selects a different year the data is copied to column F.

Option #2: Using a Dynamic Named Range

The second option is to create a dynamic named range. Create a named range an instead of entering a fixed range enter this formula:

=OFFSET(Sheet1!$A$1,1,MATCH(Sheet1!$A$13,Sheet1!$B$1:$E$1,0),10,1)

As you can see, it is very similar to the one above, but now the number of rows down is fixed (1) and it returns a range of 10×1 cells (because we have 10 regions, but if the number of regions varies you may use COUNTA(A:A)-1 to count the number of regions, excluding header – and don’t forget to move the year to a different cell…).

When you verify your range this is what you get:

You just need to use this range in your chart (when entering the range you must add the workbook name: “=Book1!SourceData”). You’ll also need a range for the category axis labels:

=OFFSET(Sheet1!$A$1,1,0,10,1)

You can download the spreadsheet here.

Take Aways

If you want to animate your charts make sure you do it because it adds value, not because you want to show off your skills. You can do it in Excel but it looks much better in Rosling’s Trendalyzer or in the Google spreadsheet gadget.

To create animations your data source must change dynamically, and that requires some work (and skills). I advise you to shift your focus from animation to interaction and use all that work to design a better user experience. Do you prefer a “wow!” (animation) or a “wow, thank you!” (interaction that actually helps the user)?

(If you are interested in dynamic charts consider getting my dashboard tutorial. You’ll find many examples there in the context of dashboard design and implementation.)

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Post from: Jorge Camoes' Charts.

Animation, Interaction and Dynamic Excel Charts

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You need a better color palette for your Excel charts, but you are a mere mortal and your artistic skills are less than stellar. Hell, you can’t even choose the right tie for a suit! So, what do you do? (hint: watch the video below)

Maybe we could ask Edward Tufte for advice. In Envisioning Information, he writes:

What palette of colors should we choose to represent and illuminate information? A grand strategy is to use colors found in nature (…). Nature’s colors are familiar and coherent, possessing a widely accepted harmony to the human eye (…). A palette of nature’s colors helps suppress production of garish and content-empty chartjunk.

Better said than done, right? Well, let me tell you a secret: it’s easier than it seems.

How to create a new Excel color palette

I’m going to show you how to create a palette of colors found in nature ( you can create a palette of colors not found in nature, if that suits you better). Here are the steps:

1. Select a photo you like. If you happen to live in a big city, finding nature can be challenging. Google for “[your location]+park” and you may get lucky. Go there, take some photos and download them to your computer. If that looks like a lot of work, you can try Flickr. Search for “autumn colors” and you’ll get some useful results. I’ve picked the one on the right;
2. Upload it to an online palette generator. There are many, so choose whichever you like. I like Genopal because it is clean (no ads) and extracts exactly the number of colors we need (eight).
3. Convert color codes to RGB. Copy the color codes to Excel and use the HEX2DEC() function to get the RGB values.
4. Create the Excel palette. In Excel 2003, replace the existing colors with the new ones. In Excel 2007 create a new color theme.

This is it. You can try it in your next chart.

A new Excel palette: the making of

If you need the details, here is a step by step tutorial:

Is this good enough?

As you can see, the results are heavily dependent on the photo you choose, so you should try different photos and test the resulting palette in a chart. If you find it hard to come up with a good color scheme, you can use this method to create a basic color palette that you can tweak to meet your needs.

Other Excel and Chart Color Resources

Jon Peltier wrote two interesting posts about managing the Excel color palette (here and here) and Stephen Few shares some Practical Rules for Using Color in Charts (PDF). Bonavista’s Chart Tamer includes a professionally designed palette.

Photo credit: Xavier Fargas

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Post from: Jorge Camoes' Charts.

Better Color Palettes for Your Excel Charts [Video Tutorial]

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I don’t know how to cook and, frankly, I don’t want to learn. But my wife is coming late from work, I’m tired of take-away food and we must feed the kids. So I guess I have to add cooking to my daily routine.

Here in Europe, Thermomix (also known as “Bimby”) is a very popular kitchen appliance (specially among men, so I’m told). You just add ingredients, press three buttons (temperature, speed and time) et voilà, diner is ready (sort of). Follow the recipe  and what you get what you expect. That’s good enough for me.

This is a gadget most people love or hate. A friend of mine hates it and tried to persuade me that I should learn how to cook using the traditional pots and pans. Only ill-informed people buys it, he says.

Yes, but he’s single. No kids, no blog, loves to cook. How can he possibly understand my motives? I just want to get this thing done with minimal fuss, no random results, small learning curve. Some good templates, that’s all I want.

I had to buy one. I just did.

OK, but what about making better charts?

Apparently, most people love making charts as much as I love cooking. Even if they need them on a daily basis, there are so many things fighting for their attention that the need for a better data visualization can easily be overlooked and pushed to the bottom of their list.

Junk food, junk charts. Some times it’s great fun to use them. And it’s very easy to take them for real food, real charts. But they are unhealthy, and if you use them often you and your business will pay a price, sooner or later.

It’s not about food or charts, it’s about business and personal health (or wellness). You don’t have to know the details, you don’t have to know how to use the tools. But you have to have some kind of framework to guide you. Fat is bad, sugar is bad, 3D effects are bad. Then you need to find some templates that implement that framework and tools that use them by default.

We played with the machine over the weekend and I’ve very pleased with the results. We eat better than we usually do and saved money and time. Not bad. Now, do yourself a favor and find your own charting machine. If you’ll excuse me, mine is calling me. Dinner is ready.

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Post from: Jorge Camoes' Charts.

Cooking Better Charts

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