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October 31, 2016

Makeover Monday: Which areas of Scotland suffer the least deprivation?

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Back at it for Makeover Monday week 44 before I head off to the States to run the New York Marathon and go to Austin for the Tableau Conference. This week we look at the Scottish Index of Multiple Deprivation, a viz I've been wanting to have a look at for almost a year now. There are lots of charts on the website; I've asked everyone to focus on this bar code chart.

What works well?

  • Nice headers to help you know what is good and what is bad
  • Alphabetical sort makes it easy to find a specific local authority
  • Shading of the lowest 15% provides nice context
  • Bar code representation makes spotting concentrations really easy

What could be improved?

  • Unless you read the accompanying website, you can't really make sense of the chart on its own as there is now scale and no explanation of how to read it.
  • There's no way to rank the local authorities from best to worst (or vice versa).
  • Interactivity would help with know which datazones are which
  • None of the other ranking metrics are included; this only covers the overall rank

I really like the bar code chart, so I set out to recreate it with a better color scheme. I also include a more meaningful title, explanations via the information icon, and an option to choose different metrics. In addition, I used the score instead of the rank. For me, using the score makes more sense because you're looking at how each datazone is doing instead of how they rank against each other.

Here are two example of the bar code chart I created, one for the overall score and one for education.

What I did notice, though, was that two of the scores are percentages: Employment and Income. So for those metrics, I switch the viz to a dot plot. The more dots that are on top of each other, the dark they are represented, thus showing the concentration. Here's an example of Employment scores.

Here is the full interactive version. Overall, a fun visualisation to re-create.

October 28, 2016

Viz Makeunder - Clinton vs. Trump: The State Battlegrounds

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One of the great benefits of working for The Information Lab is the great team of trainers. Today, André de Vries is at The Data School teaching Alteryx, which frees me up to do another "makeunder" as Matt Francis called it.

Today, let's take a look at this election viz from Rob Radburn.

What doesn't work for me?

  • It's a time series visualisation, yet it's vertical. I prefer time series to be horizontal.
  • I don't care for the grey background.
  • Black text on the dark grey is hard to read
  • Don't need the labels on both side of both axes
  • Gridlines should be for the measure not the time series
  • Too many filters

Here's my 7-step makeunder. Click on the image for the interactive version.

October 27, 2016

America's Biggest Bandwidth Hogs: A Makeover of a Makeover

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After posting my makeover of Santosh's makeover yesterday, Dave Kirk reached out to make and asked me to do the same to any of his Makeover Monday visualisations. For week 8, Dave created this chart about America's bandwidth usage:

What doesn't work?

  • Too many colors
  • The slices aren't sorted
  • The largest slice should start at 12 o'clock and then go in descending order around the clock
  • What's the purpose of the inside ring?
  • Needs a better, more focused title

Below is a step by step makeover, taking Dave's viz from a ringed donut to a simple bar chart. Click on the image to view it on Tableau Public.

Viz Remake: NASA’s Global Land-Temperature Index

This past week I saw this tweet from Elon Musk:

This led me to have a look at the data visualisations on NASA’s website, in particular, their viz of the global land-temperature index which reminded me a lot of all of the great work we saw for Makeover Monday week 20 - Global Warming is Spiraling Out of Control.

There’s so much to like about this visualisation. It has a great summary on the left with a massive number that is the centre piece of their story. Their intentional design of making the large number the focus make the line chart supplementary. The line chart is clear and simple, the legend is out of the way and the beacon on the end captures your attention.

The data is available right there below the viz so I downloaded it so that I could reproduce this in Tableau. I often attempt to recreate visualisations I like as a way to learn and practice. Because in the end, the only way to get better is to practice…A LOT!

I was able to reproduce everything bar the blinking dot on the end of the line. I also chose to fill in the circles on the grey line because I don’t care for the open circles. Lastly, I added a + to the beginning of the large callout number. I think that helps provide a quicker understanding of what the number means.

Click on the image to download and interact

October 26, 2016

US Debt: A Makeover of a Makeover

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Wow! What a day yesterday was! Lots of interaction and debate on Twitter about what is and what is not a makeover. Let me set my position: I think a makeover has to use the data provided and improve upon the original visualisation. Others use Makeover Monday as a playground to work with lots of different data or try new techniques. Those are all fine and dandy, but for me, a real makeover uses the same data as the original.

Part of the discussion yesterday was about critiquing work others have submitted. I've shied away from this because I don't want to discourage anyone from participating. Fortunately, Santosh Patil has agreed to let me give his week 43 submission on US Debt a makeover. thanks Santosh!

Let's first look at his work:

For this makeover, I'm only going to focus on what doesn't work:

  • Does it need a dark blue background? This makes some of the text hard to read.
  • What are the candy stripes for on the donut chart? What value do they add other than decoration?
  • What's the purpose of the globe in the middle other than decoration? What purpose does it serve?
  • Overall, there's just too much going on for me, for what is essentially two data points.

Below is a ten step makeover I did of his work, starting with the original. Hopefully this helps you see how I think about data visualisation and the simplicity I think we should strive for.

October 24, 2016

Makeover Monday: How big is America's debt?

This week's Makeover Monday looks at this infographic from Visual Capitalist:

What works well?

  • The author is at least making an attempt, though a poor one, at putting the US debt into context.
  • Overall, the infographic is visually pleasing.

What doesn't work well?

  • The author uses green for the US in the pie chart, but black everywhere else. This should be consistent as it could lead to confusing the two.
  • The pie chart is 3D and appears to have an extra little white slice that doesn't mean anything.
  • All of the comparisons except the S&P 500 seem to be a real stretch.

When I created the data set for this week, I included only two records. I did this because I wanted to challenge people to work with small data. I'll be writing later this week (hopefully) about how people actually handled it, many not very well.

My initial idea was to create a unit chart that included 1 million dots, but Tableau wouldn't draw them. I then went back to Alteryx and reduced it to 10,000 records. Here's my workflow:

I then created two food themed vizzes. First, I created this candy dots chart. If you don't know what candy dots are, click here.

I think this shows the context of the US vs. the rest of the world well, but I don't love it. Ok, how about a waffle chart:

I like how this is really long, but when I showed it to my son Oscar on the plane, he told me it wasn't very good. Nothing like being told the harsh truth by a 14-year old. 

I had food on my mind, and most importantly, SIMPLICITY! I was making this too complicated. Back to the original data of just two records I went. My only goal was to communicate very clear, very simple message. 

Yes, I know donut charts aren't "best practice". I like them, though, when I only have two segments and I can use the hole to communicate the message.

October 21, 2016

Fix It Friday: Ten Alternatives Methods for Presenting Alcohol Consumption in OECD Countries

If this post turns into a bit of rant, bear with me. Let's start with the Tweet that got me worked up:

You might think "It's just a chart Andy, relax!" True. It's a chart. It's not changing the world or anything. There are several things that have me a bit upset:

  1. Paul Kirby calls the chart "interesting" and maybe the CONTENT is interesting, but the chart is terrible.
  2. He says "Austrians drink twice as much as Italians", a fact that is simply not true. They drink 61% more than Italians. You can't just spout facts like that.
  3. Paul is visiting professor at the London School of Economics. I can only assume that his students follow him on Twitter. When he tweets things like this, his student will assume that this is how charts should be made, which only proliferates the number of poor charts we'll continue to see.

The chart itself has its own set of problems:

  1. It's too dark overall. The dark red bars and dark bottles are hard to see against the blue background.
  2. The flags are unnecessary. What value do they add?
  3. The bottles are cute, but unnecessary decoration.
  4. The legend is in reverse order.
  5. Do the bottle extend beyond the bars or do they start from the same baseline?
  6. It has a weak title. What's the story?

This is chart junk at its best. Don't create charts like this. I went to the OECD website and downloaded the data. Below I present ten alternative charts that all work better than the original. You can download the Tableau workbook with all of these charts here.

October 19, 2016

Tableau Tip Tuesday: How to Create a Diverging Bar Chart with One Measure

This week's tip came about via a question from Bethany Fox of the Data School during our client project. I had previously posted a tip about how to create a diverging bar chart with two measures, but she wanted to create a diverging bar chart based on only one measure.

With a cheeky use of the INDEX table calculation, this was quite straightforward. In the video below, you'll see that the middle of the charts aren't lined up. I fixed this by using the INDEX calc again. You can download the workbook to see how I got it to work.

October 17, 2016

Makeover Monday: A State by State Look at Trump vs. Clinton

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I had an idea as I headed into work this morning for another view for the election data for Makeover Monday week 42. I wanted to look at the latest forecast (i.e., Oct 12) and look at the discrepancy by State. I also really enjoyed this because it went from idea to created in about 15 minutes.

I think this view helps show much better than my last version that gap between Clinton and Trump. I also included a sorting option so you can look at it from different perspectives.

October 16, 2016

Makeover Monday - Trump vs. Clinton: A Race for the Presidency

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This week for Makeover Monday we look at election forecasting data by Drew Linzer and visualised both on his website ( and on Daily Kos Elections. I first met Drew back in 2012 when I asked him to come speak at Facebook. When I tell people who Drew is, I say that he does the same kind of work as Nate Silver, except he's transparent about how his models work.

Given that we're nearing the end of the election cycle (thank god!), we thought it would be a good time to see how the races are stacking up. First, let's look at the viz from Daily Kos:

What works well?

  • The interactivity is amazing!
  • Nice summary on the left
  • The dots for the polls add nice context
  • Simple and easy to understand
  • Great overall design
  • Great use of color

What could be improved?

  • I wish the most recent results would stay on the line chart as I hover over another date. Yes, I know they are on the left, but then my eyes have to move back and forth.

For my version, I wanted to learn how to create small multiple tile maps, so I went straight to Matt Chamber's blog. I added a couple bells and whistles to it too:

  • I added a reference line on each state at 50% to help show if one of the candidates has more than half the vote.
  • I included bar charts in the tooltips.

I really like the line chart by Daily Kos, so I rebuilt that as well. I decided to use a parameter for alternative date because this allowed me to address the issue of not seeing the latest forecast as well. I color coded the lines based on whether they are above or below the date picked by the user.

Once again, I've learned a ton working on Makeover Monday. Click on the image for the interactive version.

October 14, 2016

Join us at #RunData16!

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For the past few Tableau Conferences, members of the Tableau Community have come together for some early morning running. Last year, as you can see above, we had an incredible turnout and we expect this year to be much more of the same.


  • Distances: 5K and 10K (easy enough to make longer or shorter if you'd like)

Yes, a 5:30am start time is early, but in our experience, you HAVE TO start this early if you want time to make the keynotes. Running people are a weird bunch anyway, so 5:30 is never too early for us!

The run leaders will have high visibility bibs and torches for everyone's safety. If you have lights, bring them along. I've run these routes many times and it's a beautiful trail along the river. There are always tons of runners out and about.

NOTE: You may see a meetup list on the conference website, but it doesn't start until 6:30. If you go to that one, you have very, very little chance of making the keynotes. Plus, most of the runners will be at our run. And we'll be done before they even start!

Tableau has informed us that they will not be supporting us this year. However, keep up with the #RunData16 hashtag on Twitter for all of the latest information. See you in Austin!

October 11, 2016

Tableau Tip Tuesday: How to Limit the Number of Marks in a View

In this week’s tip, I show you how to limit the number of marks that are displayed in a visualisation. The example I show will help prevent your users from creating line charts with too many different lines.

October 9, 2016

Makeover Monday: How satisfied are people with public transportation in some of Europe's biggest cities?

This week for #MakeoverMonday, we look at this simple stacked bar chart of public transportation satisfaction survey results from the Financial Times.

I first saw this survey in print at Gatwick airport on my way to Prague, then it appeared in feedly. I know from speaking to John Burn-Murdoch that the print and online graphics standards are different. The print version I actually found easier to understand because it used blue for negative sentiment.

What works well?

  • Clear sorting by very satisfied
  • Sticks to their color guidelines
  • Simple title

What could be done differently?
  • Use different colours for the negative and positive sentiment
  • Add an overall score (like net promoter score)
  • Include 2012 for comparison so that you can see which of these cities improved
  • Add a more descriptive title so it's even more clear what the audience is looking at

I used a few resources to help me create my final visualisation:

First, I recreated the FT viz, but with different colors for negative and positive sentiment. I also included bar charts in the tooltips.

Next, I included 2012 and labeled the bars where they fit.

I don't particularly like the labels on the bars, so I've removed them from the final version. I also changed the bars to a Likert scale, which moves the negative to the left and positive to the right, and helps shows the discrepancy better. I also included the net promoter score.

Last, I added a slope graph to help show the change and included a more descriptive title and subtitle. You can click on any bar and it'll highlight in both places.

October 7, 2016

Tracking Hurricane Matthew

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It's back to Data School week for DS2 and today we were running through the new features of Tableau 10. I was demonstrating the Google Sheets connector and given the terrible storm that is currently battering the Southeast US, we created a connection to the storm path data from Weather Underground and built this storm tracker. We then also looked at Device Designer, which means there a nice mobile version of the viz too.

What's even better is that Tableau Public will refresh this data daily, so we can look back and see how the storm has progressed.

October 6, 2016

Progress for Sci-fi Reviews by Women

Last night I attended the London Data+Women meetup and Emma Cosh gave a fantastic presentation about a project she worked on with Strange Horizons about the change in women reviewers and reviewers in sci-fi magazines. The visualisations she presented worked well because she was there to explain them. On the way home, I got to thinking...would these work well without her explaining what they mean? Maybe, but I think they could be better.

This also got me thinking about the work by Stephanie Evergreen and her focus on effective, impactful titles. I recommend to people that when they are creating visualisations, assume the audience will see a static image. If they can't understand it, then it should be changed.

First, here's the visualisation that Emma created:

Click for the interactive version

There are a few things I would change:

  1. Give it a stronger title that explains the visualisation and the key message
  2. Only label the lines that are increasing
  3. Only show the magazine name on the left label to minimize the text
  4. Make the footer legible (brown on black is too hard to read)

The workbook wasn't downloadable so I recreated all of the data manually. I made the changes noted above, which are all pretty minor. Most importantly, though, the viz now has a stronger title and gives the reader a much clearer message. As Stephanie Evergreen says:

If you do nothing else to improve a weak visualization, you’ll still seriously improve its interpretability by giving it an awesome title.
I certainly wouldn't classify Emma's viz as weak, it merely could be more effective.

October 4, 2016

Tableau Tip Tuesday: How to Label the Top N Points on a Line Chart

For this week’s tip, I go back to an old tip from 2001 and demonstrate how to use a parameter and a rank calculation to display the top N points on a line chart. It’s pretty straight forward and doesn’t require anything complicated. This method is definitely simpler than the original post, which used an INDEX table calculation.

Motor Vehicle Occupant Death Rates in the USA

I was reading through feedly this morning and saw this great viz by The Economist.

I really like this simplicity of the viz, yet the detail and insight it provides. In particular, I like the Gantt chart style they used to compare 2000 to 2013. One of the best way to learn is to recreate charts you find and like.

For my version, I used data from the CDC about motor vehicle deaths by state in the US. Overall I went with a similar Gantt bar style to compare the change in the years. I made these additional enhancements:

  • Removed the line that makes them look like candlesticks
  • Muted the gridlines
  • Moved the labels next to the bars
  • Colour-coded the bars to show whether each state has increased of decreased
  • Moved the United States average to the top to make it easier to compare to

Which version do you prefer? What else would you do differently? You can click on the image below to download the workbook from Tableau Public.

October 3, 2016

Makeover Monday: The World is Becoming Less Peaceful

Last week, the Global Peach Index, this week we fix the typo and look at the Global Peace Index from Vision of Humanity.

What works well?
  • Nice interactivity and tooltips
  • Good filtering capabilities that show additional information
  • Good slider implementation to scroll through the years
  • Dark red and dark green countries are very distinct, drawing my eye to the worst and best

What doesn’t work well?
  • It’s impossible to get a sense of any trends over the years
  • Using a filled map makes it very difficult to see smaller countries
  • It’s hard to get a feel for the overall peacefulness of the world, i.e., what’s the global average?
  • Color palette is hard for color-blind people and doesn’t supply enough range in colors

For my version, I used the text of the summary below their visualisation to help craft my story. Throughout this year, I’ve primarily been creating long vizzes, but I really like the many examples Andy C has created that are wide, so I thought I’d give that a go this week.

You can click on the image for the “live" version, though there’s not really any interactivity. The mobile version will be long though, as I find that makes for a better user experience.