Now, change the viewing angle, remove gaps and you get this:

I’m shamelessly copying the first image in Robert Kosara’s Square Pie Charts (I don’t know how Robert made his). Check his post. He makes some square pie charts like this:

I’m still using the 3D column charts, with a 3D rotation of 0º (Y), 90º (Y) and 0º (perspective). We can have some fun and use circles instead of squares:

Or fill the columns with pictures:

Or we can make a panel to display alerts:

No, I really can’t fall in love with 3D column charts, but seen from above they don’t look that bad, do they? And now you know how to make a square in Excel…

[Upadate: Forgot to mention that Juice Analytics discusses other ways to make square pie charts here and has a screencast here.]

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Post from: Excel Charts Blog.

I love 3D bar charts

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The original post is titled I love 3D bar charts , and it came from The Excel Charts Blog .

To: All Staff

Re: Changes in internal data analysis and reporting

Consistent with current efforts to streamline our operations, management team has decided to change the way the company analyses and communicates business data. Recent assessments made clear that we are using just a small fraction of the available data, many decisions are not supported by enough data and we react too slowly to changing market conditions because our monitoring tools are not adequate. The ROI we are getting from the data is definitely too low.

There is much to be done, but it would be ludicrous to assume that we can revamp everything at a moment’s notice. We are aware of the need for better tools and serious training in key areas, but the real roadblock is in our minds.

The new plan outlines several steps towards a data-driven company. This memo discusses the first one, code-named The Awakening. It contains a set of simple and practical guidelines that you are expected to follow from now on. You can read the details in the intranet, together with the rational behind each guideline.

The Awakening was designed to make us all more aware of how we manage the data and how we can get more insights out of it. Again, no special skills or training are needed at this stage, just a few changes in our routines. Here are the guidelines.

Regarding presentations:

• Slides and presenter notes should be made available to all attendees; attendees are expected to read them before the presentation starts;
• A presentation should not need more than 50 slides;
• If you are using PowerPoint, animation and other effects are not allowed;
• Branding should not take more than 5% of slide real estate;
• Each slide must not contain more than a single sentence; if you need more, write them in plain English in the notes;
• If the audience is required to compare images (including charts), place them in the same slide;
• You must be able to refresh the data in your presentation.

Regarding the use of charts:

• The use of 3D effects is strictly forbidden;
• The use of pie charts is strongly dis-encouraged;
• No chart should contain less than five data points;
• There is a standard color code for each of our products and major competitor products: use them;
• If possible, use a time series;
• Don’t label data points but annotate outliers;
• Scales should always start at zero when using bar charts and single-series line charts;
• If a pattern cannot be easily identified consider removing the chart, remove or mute data or use a different chart type;
• Consider using the main takeaway as the chart title.

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Post from: Excel Charts Blog.

Memo regarding data management and reporting

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No related posts.

The original post is titled Memo regarding data management and reporting , and it came from The Excel Charts Blog .

Redistricting should be done with data & open source software, not by humans.

Let me be completely honest: I don’t like golden calves and I can spot two in this single sentence: technology and data. Yes, redistricting should be done with data and technology, but the moment you add “not by humans” you ruin everything. The right sentence is:

Redistricting should be done by humans, using data and open source software.

Data-driven redistricting can prevent basic and shameless gerrymandering, but you can’t ask the computer to discover the “right” district structure because there is none.

If you want to algorithmitize everything you end up with a 1:1 map (remember Borges’ On Exactitude in Science?). And if you don’t, how do you select the “right” data? Meta-data? Meta-meta-data? Factor analysis? Cluster analysis? And what if the other people don’t agree with you? Don’t be naïve: you can’t remove the “human factor”, you’re just moving it around.

Data and open source software can add a layer of rationality and legitimacy to your decisions but you can’t ask the computer to decide for you. Be human, decide, and fight for what you believe in.

Pro tip: never use default formats.

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Post from: Excel Charts Blog.

Data cannot save us from ourselves

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The original post is titled Data cannot save us from ourselves , and it came from The Excel Charts Blog .

Thanks for your answers. If there are reasons lot listed above please discuss them in the comments.

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Post from: Excel Charts Blog.

Why do people make bad charts? [POLL]

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Post from: Excel Charts Blog.

Data Visualization for Excel Users – How to Make a Chart, Part I: Asking Questions

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The original post is titled Data Visualization for Excel Users – How to Make a Chart, Part I: Asking Questions , and it came from The Excel Charts Blog .

Are they?

Let me tell you about a little experiment. I call it the scatterplot pie just for fun, and the idea is to display proportions using a scatterplot.

A traditional pie chart with two data points can be reduced to an angle:

The same message, no fat. And because there are no textures and arcs to deal with we can now superimpose many pies.

These are percentages of the age group 65+ in 1996 (left) and 2050 (right) for 220 countries (data from the US Census Bureau). This comparison clearly shows that the World is getting older.

One of the problems with pie charts is that you can compare proportions but you can’t compare wholes. In the images above we are comparing very different country sizes (Tuvalu and China?). With the scatterplot pie we can add this dimension:

China and India are not helping resolution, but it would happen to any other chart. We can focus on a detail:

Other things we could do:

• Group series (in this example, color-coding by continent would show us the significant differences between Europe and Africa);
• Add axis and circular grid lines to improve readability;
• Set line transparency to 50%;
• Remove the vertical line or make it look like a grid line;
• Label the more significant data points.

I actually like this idea and I’ll test it a bit further. I’ll try to decide if it is a good alternative to stacked bar charts. It should also work with three or more slices, but just because it works it doesn’t mean we should use it (like most chart options in Excel…).

So, what do you think? Would you use it?

This is not entirely mine: I was inspired by this comment. And I’m sure someone must have though about this first. If it rings a bell please let me know…)

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Post from: Excel Charts Blog.

The best of two worlds: the scatterplot pie

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The original post is titled The best of two worlds: the scatterplot pie , and it came from The Excel Charts Blog .

(…)

On the top of the mountain was a plain. There stood an old stone house, and in front of the house lay a great fish-pond, but behind it was a dark forest. He saw neither men nor animals, everything was quiet; only the wind rustled among the trees, and the clouds moved by quite close above his head.

He went to the door and knocked. When he had knocked for the third time, an old woman with a brown face and red eyes opened the door. She had spectacles on her long nose, and looked sharply at him; then she asked what he wanted. “Entrance, food, and a bed for the night,” replied the drummer. “That thou shalt have,” said the old woman, “if thou wilt perform three services in return.” “Why not?” he answered, “I am not afraid of any kind of work, however hard it may be.”

The old woman let him go in, and gave him some food and a good bed at night. The next morning when he had had his sleep out, she took a thimble from her wrinkled finger, reached it to the drummer, and said, “Go to work now, and empty out the pond with this thimble; but thou must have it done before night, and must have sought out all the fishes which are in the water and laid them side by side, according to their kind and size.” “That is strange work,” said the drummer, but he went to the pond, and began to empty it.

He bailed the whole morning; but what can any one do to a great lake with a thimble, even if he were to bail for a thousand years? When it was noon, he thought, “It is all useless, and whether I work or not it will come to the same thing.” So he gave it up and sat down.

(…)

Stay here, said the maiden, I will help you out of your difficulty. You are tired, lay your head in my lap, and sleep. When you awake again, your work will be done. The drummer did not need to be told that twice. As soon as his eyes were shut, she turned a wishing-ring and said, rise, water. Fishes, come out. Instantly the water rose on high like a white mist, and moved away with the other clouds, and the fishes sprang on the shore and laid themselves side by side each according to his size and kind. When the drummer awoke, he saw with amazement that all was done.

(…)

This was one of my favorite Brothers Grimm bedtime stories when I was a kid. I still like it. And the drummer looks a lot like you and me. Like him, we have our great fish-ponds of data. Like him, we have clueless managers, impossible deadlines, the wrong tools and the wrong training. We try hard and sometimes we fail. And yes, I like to see data visualization as a beautiful maiden that will help me seek out all the fishes in my pounds of data.

nite-nite.

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Post from: Excel Charts Blog.

The drummer – a data visualization bedtime story

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The original post is titled The drummer – a data visualization bedtime story , and it came from The Excel Charts Blog .

Enjoy and comment, please…

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Post from: Excel Charts Blog.

The Unbearable Lightness of Pie Charts [Data Visualization for Excel Users]

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The original post is titled The Unbearable Lightness of Pie Charts [Data Visualization for Excel Users] , and it came from The Excel Charts Blog .

I started writing my Data Visualization for Excel Users series because I have an unhealthy number of open questions. I’d like to go beyond it depends but there are no right answers, only my answers (and, with your help, our answers). These are practical questions (from a business user perspective) that, once answered, will surely trigger new ones. Here is a sample, with a few starting points:

1. Reason or Emotion?

This is the big one. We’ve been discussing reason vs. emotion over the last 2,500 years, and we still disagree. The right answer would be reason and emotion (easier said than done). When applied to data visualization, this translates into charts that respect the data, attracts readers attention because they are beautiful and keeps it because they are interesting and insightful. And contain no cheap emotional tricks. This filters out 99,9% of all  infographics published nowadays.

2. Pies or No Pies?

No self-respecting data visualization expert likes pie charts. And there seems to be a daily contest to find the “worst pie chart ever”. And people keep making them, relentlessly… Why?

3. Are there interchangeable charts?

Everyone tells you that you should use bar charts instead of pies. Well, I think you should. Not because pie charts are bad, but because you’ll have to ask better questions. But that’s not the point. The point is that there are no interchangeable charts. Different charts tell us different stories. You cannot tell a part-of-a-whole story with a bar chart. You have to have a pie.

4. Should I use logarithmic scales?

I’m still trying to find a simple way to implement a logarithmic perspective in my eyes… Logarithmic scales are important to look at growth from a different perspective, but if you can’t find a way to tell the readers how to read the chart you should consider not to use them.

5. Should origin start at zero?

Yes, by default. If you need to improve resolution set the scale to 20% below minimum and 20% above maximum values . Don’t do it with bar charts (origin should always be set to zero).

I would consider this rule: to improve resolution you must have more than one series (see this example). In a line chart, comparing slopes is often more interesting than the slope itself.

6. What kind of data visualization skills the information worker needs?

Above all, know your business. Learn how to use a database (table structures, basic SQL). Refresh what you know about descriptive statistics. Choose a tool and be an advanced user or hire someone who is. Learn the basics on how human perception works. Understand how perception impacts design choices and the other ways around. Learn what each chart type is used for. Find your charting style. Spread this knowledge across your organization. Know your business (again).

7. What is the role of design in data visualization?

We saw that a chart is a visual representation of distances between data points. Everything else is design. The first role of design in data visualization is to improve cognition. The second role is to provide aesthetic consistency. The third role is to grab users attention.

8. How to design a dashboard?

I think we owe Tufte and Bertin a consistent approach to data visualization, at the chart level. We still need something similar for dashboard design.

9. How to sell data visualization?

Find a sponsor and make a lot of bad chart/(good chart comparisons. Compress a 100-slide presentation into 50 slides. They will get it, sooner or later.

10. Should I use animation?

You probably shouldn’t. Try small multiples first. Try animation if you have too many series, if the animation defines clear patterns and if it is consistent with the law of common fate. But remember: are no interchangeable charts.

11. Do I need to code?

No, but you should at least be able to understand what a recorded macro is and how to improve it with simple changes.

12. What tools should I use?

Learn everything in Excel then switch to Tableau/Qlikview/Spotfire.

How would you respond to these questions? Please share your thoughts in the comments below…

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Post from: Excel Charts Blog.

12 Data Visualization Questions I Have No Answers For

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Post from: Excel Charts Blog.

Data Visualization for Excel Users: Gestalt Laws

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The original post is titled Data Visualization for Excel Users: Gestalt Laws , and it came from The Excel Charts Blog .