Changing the message without changing the data

Two formats, two messages. Time for a new example?

If you’ve seen me present in the last 3 years, you’ll probably have seen me show the Iraq Bloody Toll chart. Then you’ve seen me turn it upside down to create an entirely different message (full post here).

I still love showing this example to new audiences. I love seeing the light bulb go off as they realise that a data and a chart is just a method of communicating a message: facts are not neutral.

But it’s time to find a new example and for that I turn to you for help.

Have you got any other great examples of charts where the message can be transformed in as simple a way as this one? 

(Note: I’m only looking for examples that stay true to good practice. Truncating the y-axis doesn’t count!)

There are some older examples. Obama’s bikini chart was a cracker, described very well by Robert Kosara in 2012.

Do you know any others? If I can find enough, we could turn this into an entire blog post or webinar. Let me know in the comments or on Twitter.

It’s the small dataviz things: Paragraph Legends

How do you communicate what the dots, marks, and lines on your chart show? Most often, you’ll use a legend. They work well, but check out the this from the Huffington Post. They created a Paragraph Legend (as I’m going to call it).


Why’s this great? I mocked up what this might look like if we used a regular legend. Try and decipher the chart using the “traditional” approach:


In order to decipher the chart you need to read the paragraph. Then the chart. Then go to the legend. Then back to the paragraph. Then back to the chart. Finally you might understand what’s on show.

Now look at the Paragraph Legend. Read the paragraph, look at the chart, and then maybe back to the paragraph once more. I found it much much easier to decode the chart with the Paragraph Legend. Like all small things, this is harder for the designer, but an improved experience for the audience.

[This is the second time I’ve reused Andy Kirk’s amazing idea to blog short posts on great things they see in dataviz. All credit goes to Andy for the idea. I’m going to call my series “It’s the small things….”]

Tableau quick tip: turn your column headers into filters

nobody looks over here

A perennial problem with filters: how do you make your users aware they are there ? How do you wrench their eyes away from the marks and headers and over to the filters on the right?

To fix this, I stumbled across another potential method: replace the Column Headers with Filters. I say stumbled because I wasn’t consciously trying to solve the problem when I implemented it. It’s only afterwards that I realised what I’d done!


What’s the advantage of doing it this way?

  • People are looking at the top left of your chart, so they are more likely to register that they can filter the dimensions.
  • It’s a cleaner view. The top banner is freed to have just my dashboard title. The right hand side doesn’t have that unusual blank space beneath the filters.

To implement this, it was simply a case of floating the filters over the column headers. For a design aspect, I ensured they were the same width as the columns in the view itself. I also tweaked the colours to bring attention to the dropdown itself.

BTW – go check the interactive Script Wars viz here. Or go check out what others have done with #StarWarsData.

“Match mark colour” allows for some nice effects

Coloured labels

Tableau 9.2 was released this week, along with some amazing new features. One nice feature is “Match Mark Colour.” I believe it has all sorts of creative possibilities for your views. For example, above you can see I’ve got two labels on a bar chart. One shows the numbers, while the other, aligned left, shows the categories themselves, nicely using Tableau’s algorithm for matching useful colours.

"Match Mark Colour" is found on the Font drop down in the Label menu.
“Match Mark Colour” is found on the Font drop down in the Label menu.

How do you make the labelled chart above?

To make this labelled bar example, I created a dual axis bar chart, duplicating the SUM([Number]) measure, and synchronizing the axes.

Both measures were labelled. One Measure was labelled with [Colour], aligned to the left. The other was labelled with [Number], aligned to the right. Finally, right click on the [Colour] dimension on the Row shelf and untick “Show Header”

Setting up the dual axis
Setting up the dual axis

Simple! What other nice design tricks can you do with colour matching?


How to drive the message home with the right dashboard

Today (Thu 16 April) I did a Webinar for Tableau, “How to drive the message home with the right dashboard.” (the webinar recording will be available on that page very soon).

The slides are available here.

And here are the links to the resources I shared:

Design books and projects

Ranking UK political parties according to mentions on twitter by the media
Ranking UK political parties according to mentions on twitter by the media

Tableau Dashboards

How come we see bigfoot fewer times, despite us all now having smartphones?
How come we see bigfoot fewer times, despite us all now having smartphones?

Inspiration and further use cases

Viz of the Day: great messages, every day
Viz of the Day: great messages, every day

Tableau Design Month, post 12 of 12: the big recap

Over the past month, I’ve deconstructed a dashboard I made for Tableau’s internal VizWhiz competition. Below is an attempt to quantify the Impact and Difficulty of each of the design choices I made. You can click on each one to go read the post describing the design choice:

If you’ve enjoyed these posts and want to continue reading my blog, please subscribe to my RSS feed or connect with me on Twitter (@acotgreave)

Why did I bother changing a dashboard that looked pretty fine in the first place? Why did I write 14 posts about this single dashboard?

Simple: I wanted to really think about the design choices and share the process of taking a perfectly functional dashboard and trying to make it into a thing of beauty.

The original (top) to the final result (bottom)
The original (top) to the final result (bottom)

Stepping back made me realise how many and what type of choices I make. Each choice has a highor low impact and is easy or hard. I quantified that in the viz above. As Michael Mixon pointed out in a comment, as we become experts we take this stuff for granted.

Take note: my posts are not a manifesto for all visualisations. As I’ve written elsewhere, there’s no right answer when designing visualisations.

I recommend you download the final workbook. There’s lots of extra views that didn’t make the final version. You’ll be able to see for yourself how I did everything.

Note the vertical lines
The end result

For reference, here’s the full list of posts:

Which design features should I implement
Click the image to see an interactive version

Titles, tooltips and annotations : 4 neglected design considerations

I don’t consider this an encyclopedic post. Instead, I want to cover the text-based choices in the dashboard I’ve been dissecting as part of Tableau Design Month. This is 14th of 15 posts in the series.

Titles: the unsung hero of your visualization

You are fighting for viewers’ attention with any visualization you produce. One of the few things you can guarantee they will look at and process is the main title. Therefore you better be 100% sure this is both:

  • Enticing
  • Relevant
  • Explains the chart or asks a question

Your title is your one chance to grab the reader and convince them it is worth focusing on. This is not a new lesson: Willard Brinton was talking about this 100 years ago:

A 100yr old viz with an illustration to entice the user

Subtitles are just as important. Consider the titles on each view:

Titles convey the message
Titles convey the message
  • I’ve numbered them. This helps guide the user through the view. Sure, the left-to-right nature determines the flow but numbering the titles helps.
  • I bolded the pertinent data-related facts. I’m using the title to communicate the data itself.
  • I’ve also added contextual text. Notice the “All” in the second view title. If you filter down to a single year in the highlight table (you can do this in the interactive version), “All” changes to the relevant year:
    ALL in a title To learn  how to make dynamic titles in Tableau, click here to see a post on The Information Lab’s blog.

Annotate marks to add context

No annotations: a tease not an insight
No annotations: a tease not an insight

Imagine I’d left the annotations off the charts. You can see the effect above. What are you left with? A chart with a really interesting trend that gives no clues as to what causes it. The viewer is left with their interest piqued but with no answer. This is a serious failure. Adding the annotations answers those initial questions.

My first iterations of this dashboard did not have any annotations. It was only when I got feedback from people that they pointed out the problem. That’s the importance of getting feedback!

Below is the annotated time series: it’s much more useful:

Annotations help me understand the chart
Annotations help me understand the chart

My final word on these annotations – I deliberately aligned the annotation arrows to be vertical to give them consistency

Tooltips – ALWAYS be customizing your tooltips

Tooltips explain the mark right next to the mouse, where the viewer's eyes are.
Tooltips explain the mark right next to the mouse, where the viewer’s eyes are.

Followers of this blog will not be surprised that all the tooltips are customized. If you want to know more about the importance of tooltips, and techniques to use them in Tableau, check out this series of posts. Summary: ALWAYS customise your tooltips; it is the easiest way to improve your dashboard.

Finally, don’t forget to turn off the command buttons: these are great for exploration in Tableau but a distraction for end users.

Command buttons: great for analytics. Not great for published dashboards.
Command buttons: great for analytics. Not great for published dashboards.


I’ve only considered a tiny set of considerations when using text in your visualizations. What else do you consider important for text on your visualizations?

Come back tomorrow for the final post in the Tableau Design Month series – a big wrap up of everything I’ve covered.

Choosing the right colours for your visualizations

Colour in data visualisation: apparently easy but filled with pitfalls. There are volumes of posts about colour on the web. I’ve written about it before when discussing the Iraq’s Bloody Toll chart. And here’s a recent post about exploring and choosing potential palettes.

My entry - click to see it bigger
There were no accidents in the colour choices for this dashboard (click to see the interactive version)

For this post, one of a series supporting Tableau Design Month, I’ll explain the colour choices made in design the dashboard above. There are three points I will highlight in this post:

  1. Simplify the colour scheme as much as you can
  2. Choose a colour that relates to your topic
  3. Soften the darker tones

Simplify the colour scheme

Let’s see what Tableau’s default colour scheme would have been:

100% default formatting
100% default formatting

Tableau, or any visualisation tool, cannot know what the purpose of your vizualisation is. Therefore its choices should be appropriate to the chart being built. But in the above, the end result is overwhelming. There are colours everywhere.

It turns out that using just 2 colours: red and grey, you can tell the exact same story more clearly. You can even test your dashboard by trying it in greyscale: is the story still visible in the version below:

Get it right in black and white
Get it right in black and white

Choose a colour that represents your topic

I chose red to evoke the emotional aspect of this dataset. Red is powerful and emphasises the reality of fatalities. What if I’d have chosen a different colour? Blue, for example:

Going for neutrality
Going for neutrality

In this case the dashboard is much more neutral. It’s less provocative. It’s less opinionated.

Your colour choice should depend on your audience and your goal.

Soften the darker tones

You can choose palettes to emphasise just the parts of the data you want to.  Tableau defaults to a perfectly serviceable green gradient palette.

My goal was to make the 3 most lethal seasons (Jan 1, Jul 4, Dec 25) pop out. A simple red palette didn’t do it so I tried red-black, but the black was too prominent. I settled on a red-white diverging as this really popped the days I wanted to focus on. All my choices can be seen below:

Iterating through different colour choices
Iterating through different colour choices

I went a lot further in this dashboard to soften the dark tones. For example, all the fonts are softened from black to a lighter grey. As I write this post, I’m unsure now whether that was a successful choice. Check out the image below. Which do you think is more successful – the dark font or the light font?

Which do you prefer? The lighter tones on the left or the darker ones on the right?
Which do you prefer? The lighter tones on the left or the darker ones on the right?


Colour isn’t easy. In this post I’ve covered just 3 choices. You also need to consider cultural implications, colour-blidness, publication type, and much much more. As always, I am very interested in your thoughts – let me know in the comments.

How do you communicate that people can interact with your designs?

If you publish something interactive to the web, how is your audience supposed to know it is interactive? And how do you instruct them what to do to interact?

what you write and what they read

When a user sees a dashboard for the first time, they need to learn how to read it and how to interact with it.

You can do this in many ways. Often I see people put the instructions somewhere on the viz or on an instructional tooltip. Here’s an example from a recent Viz of the Day:

"Click on a party" (click here to see the original)
“Click on a party” (click here to see the original)

That’s fine but there is one major problem: most people don’t read the text on your viz. They’ll probably read the title but not much else.

One way you can inform a user they can interact is through tooltips and that’s what I will cover here.

Interactivity can be divided into 3 types, all of which are available in Tableau. Something can be triggered when a user:

  • …hovers their mouse over something (how does this replicate on mobile? That’s a question for another post)
  • …clicks on a data point
  • …lassos and selects some marks of the interactive

In Tableau, these are defined a “Hover”, “Select” and “Menu”. If you’re new to actions, I recommend this post by Peter Gilks.

The menu action is always in Hyerlink blue
The menu action is always in Hyerlink blue (click to see interactive version)

For my Design Month dashboard, I chose to go with a Menu action. I like the fact that when a user hovers their mouse over a mark, a nice customised tooltip with a call to action appears right where their eyes are looking.

I used a Menu action but a similar trick can be achieved with a Select action. Using a Select action gives you more control over the format of the Call to Action. I like this example from another recent Viz of the Day:

Select as Menu

This technique is not perfect:

  • There isn’t a Hover equivalent on a mobile interface.
  • What if the user DOESN’T move their mouse over the viz?

Which actions do you prefer in your dashboards? What else do you consider when instructing people about interactivity?

Less is more: improve chart clarity by removing borders and lines

Lines reduced as far as possible.
Lines reduced as far as possible. Click to see and interact with the full dashboard.

When you design a chart, just how many borders and lines can you remove to maintain clarity? Do you improve clarity by removal?

Could I have gone any further? Sometimes I will hide the y-axis completely and just label the max value but I think that’s pushing it a little too far:

tick mark too far
Removing the y-axis completely: a step too far?

That’s what we’ll look at in this post. I’ll cover axis ranges and tick marks separately. In this post, I’m going to focus on what’s available from the formatting pane.

In the image above, you can see that my formatting approach is to reduce the lines as far as possible while retaining the meaning.  Did I go too far? I think I got it about right.

Let’s look at how my end result compares with the defaults: Default formats on the right, extreme reduction on the left.

Default formats on the right, extreme reduction on the left. There’s nothing wrong with the defaults – the gridlines and borders are very sensible choices for a default setting. I do think I have emphasised the data more by reducing the lines.

Here’s how you can reduce the borders and grid lines in Tableau:


Remove all of the outer borders by selecting Format…Borders from the menu and then turning off all dividers at the sheet level:

How to remove outer borders
How to remove outer borders

 Grid lines

I owe a hat-tip to Nelson Davis (@nelsondavis) for suggesting that it’s great to show only the horizontal grid lines in a view.

To achieve the effect, just go to the Format…Lines pane and set the Columns Grid Lines to None:

This setting leaves horizontal gridlines only
This setting leaves horizontal grid lines only


I like the end result, it’s very crisp. One bonus is that because there’s no border at the bottom, it makes it less likely someone will think the y-axes start at zero.

You can see and download the full Fatalities dashboard here.

My entry - click to see it bigger
My entry – click to see it bigger