Data Viz Done Right

September 26, 2016

Makeover Monday: China is Dominating the Global Peach Index

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This week's Makeover Monday was inspired by a typo in an email exchange with Andy and me. I had thought about doing the Global Peace Index this week, but accidentally typed "Peach" instead of Peace. Andy pointed it out to me, but then I thought, I wonder if there is a viz and data about global peach production.

And thanks to FAOSTAT there is! Who knew?!? Their data set is accompanied by a series of chart. I'm going to focus on their map.

What works well?

  • It's a map, so I can easily understand that it's show geographic distribution.
  • Nice filtering capabilities

What doesn't work well?
  • The color scales don't make sense. Are they ranges? Are they precise values?
  • There are a lot of yellow countries/ What does that mean? 
  • The blue water makes it hard for the blue shading on the map to stand out.
  • The mapp wraps and repeats.
  • Comparing countries on a filled map is nearly impossible. How does China compare to Holland? If you can't answer questions like that, then a filled map is not the answer.

For my version, I wanted to focus on the top peach producers in 2012, so I created a set that only includes to top 10 countries of 2012. I started with a summary, then an view over time, followed by a heatmap to help highlight the differences.

Click on the image for the interactive version.

September 19, 2016

Makeover Monday: Data breaches are getting bigger and more frequent


Several people have recommended Makeover Monday for the Project of the Year in the Kantar Information is Beautiful Awards, which I must admit is quite stunning and flattering at the same time. The suggestion for this week’s makeover came from Andy Cotgreave. We intentionally picked something from Information is Beautiful with the hope that it gets a bit more exposure. Shameless perhaps, but what can it hurt? This viz from David McCandless certainly deserves a makeover.

What works well?
  • The viz is eye-catching and definitely draws you in. There’s something to say for that.
  • The interactivity is fantastic.
  • Good filtering, colouring and sizing options

What doesn’t work well?
  • The bubbles move all around for no apparent reason.
  • There’s way too much overlapping, making it hard to identify any insights.
  • Whether something is interesting is extremely subjective. I wouldn’t make these same choices.
  • The viz doesn’t fit in a single view, requiring too much scrolling.
  • Not all records are included. I guess this was done for artistic purposes as David is known to do, but it distorts the message.

I decided to work on my makeover during my flight to Prague, thus imposing a time limit on me. I started by creating a view that simply shows the number of data breaches by year using circles. This basically flattens out the original.

While this shows the distribution nicely, I don’t love it. Next, I converted the circles to squares, hoping the result would be more visually impactful as the squares take up more space.

This is definitely better, however I don’t like how it doesn’t incorporate the records stolen in each data breach well enough for my liking. So I decided to add a dot for every breach in the data set and change the location of each dot to the number of records stolen.

Getting there…iterating is really helpful. This shows some of the outliers really well, but I feel like I’ve lost the distribution a bit. I decided to quickly open the data in Vizable and when I switch the view to records stolen by year, Vizable presented me this interesting view that shows the median and the distribution.

I really liked this so I decided to build upon it in Tableau. My final viz incorporates the view from Vizable, the distribution of each data breach and allows me to focus the story on data breaches that were hacks versus not hacks.

Click to view interactive version

I find this final view much, much easier to look at than the original and also it provides much better context. For me, context is key. Every visualisation you create should include context somehow. Why? Context makes it much easier for your audience to understand the story.

September 13, 2016

Tableau Tip Tuesday: How to Create a Combination Chart with Overlapping Bars & a Line

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In this week’s tip, I look back at one of my most popular posts - 7 easy steps to create a combination chart with overlapping bars & a line. The tip hasn’t changed much, however, this time there’s a video.

September 12, 2016

Makeover Monday: Which shipping company really makes the most money?

This week’s Makeover Monday looks at the largest shipping container companies of 2016. The article includes this packed bubble chart:

What works well?

  • It’s eye-catching and draws you in.
  • The method for labelling ensures you only see the largest (as they names won’t fit otherwise).
  • The color helps identify the largest companies.

What doesn’t work?

  • Ranking is nearly impossible
  • Are the depth of color and the size of the bubble for the same metric? The viz doesn’t tell us, so we’re left to guess.
  • Is big good or bad?
  • There’s no focus or context.

I started by changing it to a bar chart, but found that to be too boring, though effective. Then I saw an example by Shawn Levin which shows looks at the TEU per ship. That adds much more context to the visualisation. Shawn compared Total TEU to TEU per ship.

For me, I thought it was more meaningful to look at TEU per ship for both the total shipments and for the ships each company owns. This led me to the slope graph you see below which tells a much more meaningful story.

September 6, 2016

Tableau Tip Tuesday: Using a Level of Detail Expression to Summarize Dimensions

This week’s tip goes back to a tip I wrote in 2012 that required table calculations. With the addition of Level of Detail expressions in Tableau 9, the need for a table calc is obsolete.

September 4, 2016

Makeover Monday: Alan Rickman - An Actor’s Life


This week’s Makeover Monday subject was sent to me by incoming Data Schooler Anna Noble. Nothing like kissing up to the coach before you even start. 😋

The viz in question is from The Slow Journalism Company:

What works well?

  • It’s obviously a timeline.
  • It’s clearly about Alan Rickman.

What doesn’t work?

  • It took me a while to figure out what the being on each side of the timeline meant.
  • Horrific colour choices; apparently the colours identify the genre. You can see that in the microscopic font on the lower left.
  • Colours with zig zagged lines are always a bad choice
  • The pointy things
  • The pie chart
  • The annotations aren’t near the data they represent.
  • You have to use the zoom feature to read anything.
  • It makes me dizzy.

For my makeover, I wanted to do something very simple. This data set calls out for something simple and clear, especially after you spend time trying to understand the original. I have no idea who Alan Rickman is as I’ve never read any Harry Potter books nor seen the movies. Yes, I’m a terrible father! I once again used 100% floating objects to create this. I’m really loving the precise control that lets me have.

Click on the image for the interactive version (but really there’s no need as there nothing more to the live version other than a mobile view).

September 2, 2016

The Toxic Twenty Five: An Analysis of Southern California Air Quality

This week I challenged The Data Duo to a #VizOff of sorts. I provided them with a data set of 8.5M ozone level readings from stations spread all throughout the U.S. I started looking at this data a few weeks ago because I was thinking about the smog in Atlanta and wondering if it had gotten any better since I left. This led me to the master data set or all cities that are measured.

Once I started exploring the data, I noticed that Southern California consistently had the most cities with high ozone levels. So I filtered the data set down to the 25 worst cities.

This helped me focus on a single story with multiple parts, as seen in the long-form visualisation below. Enjoy!

August 30, 2016

Tableau Tip Tuesday: How to Create a Two Color Pareto Area Chart


In this week’s tip, I walk you through how to create a two-color Pareto chart, a dynamic title, and customised tooltips based on my recent Makeover Monday about U.S. companies hoarding money offshore.

August 29, 2016

Makeover Monday: U.S. Companies Are Hoarding Trillions Offshore


First, I must give credit for finding this week’s Makeover Monday to Jade Le Van. She’s a massive supporter of the work everyone has been doing in this project. Thank you Jade for finding this beauty from CNBC.

There are so many problems with this visualisation. However, the most egregious mistake is that the data is completely wrong. The author took the original data set, which has the total money held offshore by a company and allocated that same amount to every country that each country has an affiliate in. For example, General Electric has $199B stored in 18 offshore subsidiaries spread across seven countries. The author allocated $199B to EACH of those seven countries. That’s simply wrong!

What doesn’t work?

  • The data is inaccurate.
  • The pie charts are a ridiculous choice, especially when you show every single company in each country.
  • The companies aren’t sorted.
  • The size of the pies isn’t proportionate across the difference columns. In other words, they aren’t all based on the same range.
  • It’s impossible to find a company you might be interested in investigating.

What works well?

  • Nothing; the whole visualisation is a complete disaster.

I had a few minutes to explore this data set while on the bus home, so I opened up the data in Vizable. Within about 20 seconds I had two views that were far superior to the original.

Quickly and easily, I have a view of just how much money companies are keeping offshore and who they are in a nice, simple ranked list. Great! I already have something much better than the original.

Two more swipes in Vizable and I’m now looking at the companies with the most offshore subsidiaries.

At this point, I felt I basically had all I needed to tell the story in Tableau. I quickly reproduced the two charts from Vizable, then added a Pareto chart for more context. Lastly, I added some headers above each chart to tell a synchronous story.

August 24, 2016

Tableau Tip: Connect to Google Sheets with Daily Auto-Refresh

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After publishing my viz earlier today that used Google Sheets, Zen Master Chris Love posted this question on our collaboration tool:

So I told him I’d create a video that shows three things:

  1. How to scrape data from a web page into Google Sheets
  2. How to import that data into Tableau with the Google Sheets connector
  3. Ensuring it refreshes when you publish the viz to Tableau Public


UPDATE: Zen Master Jeffrey Shaffer sent me a link to this post on his blog. It’s important to note that the IMPORTHTML function does not seem to auto-refresh. You can force an auto-refresh in your Google Sheet by making the first cell an IF statement like this following -


Then you need to update your spreadsheet settings. Click "File" -> "Spreadsheet setting" and set the "recalculate" to "On change and every hour". This will keep the data refreshed.

Clinton vs. Trump: The Battle for the Presidency


It’s election time, so time for an election viz. You will notice this is very similar to the RealClearPolitics version the difference being that I am calculating the 2-week average of all polls in their data set.

This little project also provided me a chance to try out the new Google Sheets connector in Tableau 10 and allow the extract to refresh on Tableau Public. In addition, I learned how to scrape a table from the web in a Google Sheet via this blog post, which should (if I did it right) update automatically.

This was also another chance for me to test out the Device Designer that came with Tableau 10. Enjoy!

August 23, 2016

Tableau Tip Tuesday: How to Use Dynamic Grouping & Filtering for Competitor Analytics

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In this week’s tip, I show you how to compare your company to your competitors, but only for products that you both sell. In other words, you only want to compare products where in which you both compete.

August 22, 2016

Makeover Monday: Together We Can Eradicate Malaria in Africa


This week for Makeover Monday we are tackling the malaria epidemic. The fact that countries still have to worry about malaria despite the prevention measures available is quite sad. Fortunately, the Tableau Foundation is helping and you can help too. Please visit to help.

Let’s look at the original visualisation on the World Health Organization website.

What works well?

  • Really nice interactivity with both hover and click actions
  • You can make any are full screen
  • Consistent color palette
  • Easy to understand

What doesn’t work well?

  • Map is way too wide
  • List of countries doesn’t aid in understanding
  • Time series and bar chart don’t adjust for the data that is filtered
  • Timeline is missing several years, even though the data exists
  • Time series doesn’t display anything until you click on a country

I wanted my visualisation to fix the issues listed above, but also to be more focused on Africa. I also wanted it to serve as a call to action. I start with a summary and background information, dig a bit into some insights I found, and wrap it up with a way people can help.

August 17, 2016

The Data School Gym - Running to the middle ground


This Data School Gym challenge is nothing more than a remake of an existing chart. I was reading Andy Kirk’s great series “The Little of Visualisation Design” and he showcased a chart from The Economist. From Andy’s blog:

"Typically, charts like this would have categorical value labels right-aligned to the left of the vertical axis. However, in this case, the labels are positioned with immediate proximity just to the right of the highest value - which is the value used to order the categories vertically. This approach aids readability, making it just that little bit more efficient to perceive the values and their associated categories."

According to The Economist, this chart shows:

"In every state where exit polling from this year’s primaries is comparable with the previous competitive cycle (2012 for the Republicans and 2008 for the Democrats), more voters have described themselves as “conservative” on the Republican side and “liberal” on the Democratic one."

I thought this would be a fun chart to try to rebuild in Tableau. I recreated the data manually, which you can download here. Note that the data probably isn’t 100% accurate to the original chart; I did the best I could and that’s not the point anyway. The point is to practice, practice, practice.

Some hints:

  1. This is three charts.
  2. I used 100% floating objects.
  3. The vertical and horizontal lines were added manually.
  4. Each event has its own sort: The top is sorted by Conservatives, the second by Liberals and the third by Moderates.
  5. The shading must span from the smallest to largest value for each event and state.

Give it a shot. I didn’t think this one was too terribly difficult. The toughest parts for me were getting the layout just right.

August 16, 2016

Tableau Tip Tuesday: How to Shade Under an Area Chart

In this week’s tip, I show you how to shade the area under an area chart, when that are is around some type of baseline. A regular area chart won’t work in this case, so it requires a few simple steps to get it to look just right.

August 15, 2016

Makeover Monday: State of the UK Cosmetics Market

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Several of the ladies that participate in Makeover Monday have been asking for a while now to look at a data set and viz that related to the original #MakeoverMonday hashtag. That is, something to do with beauty, make-up or hair.

This week, we look at this infographic from Raconteur Media, a publishing house and content marketing agency. Raconteur has a whole section devoted to their infographics if you’re looking to do more makeovers on your own and need interesting data sets, or if you’re looking for some creative inspiration.

In particular, the focus on this Makeover Monday is on the radial chart in center of the graphic. This chart attemps to show the year-over-year change in the UK market for various makeup products.

What works well?

  • Each of the sections is sorted from largest to smallest
  • Each bar has a clear label for the 2014 value and the change vs. 2013
  • Design catches and retains your attention
  • Simple summary in the middle
  • Really crisp font that is easy to read
  • Good color choices that contrast well
  • Consistent decimal formatting

What doesn’t work well?

  • The categories are not sorted, so it takes a lot of work to see which category is the largest.
  • Comparing products across categories is basically impossible.
  • Originally, I thought the white T-line extended out to the value for 2014, but it doesn’t mean anything. It’s simply to fit the text.
  • This led me to think that the bars themselves were 2013 values, but they aren’t. So I’m not totally sure what the white line and bars represent.
  • Some of the bars are cut off with squiggly lines to show they go farther than the viz shows. This can be misleading.
  • At a glance, it’s very hard to tell which products are growing and which have declined.

For my version, I decided to go 100% floating in Tableau for the first time ever. I now understand why people design in Tableau this way. I can make my dashboard look EXACTLY the way I want and it’ll render exactly the same way on Public. Previously I would try to float only parts of the dashboard and they would shift a few pixels in Public. Not so with 100% floating. So, what I’ve learned is design Tableau dashboards 100% tiled or 100% floating, but don’t mix the two. This is the beauty (pardon the pun) of Makeover Monday; it gives me a chance to experiment and learn.

I deliberately chose colors that I thought looked more “make-upy”. I used an orange-to-purple diverging color palette from ColorBrewer and added it to my Tableau preferences file. Lastly, I also incorporated a phone version using Tableau 10’s new Device Designer.

My goals for this dashboard were simple:

  • Make a dashboard that makes understanding and compare within and across categories easier
  • Create a computer and phone version
  • Use colors that represent the topic, but also clearly show products that are increasing or decreasing

Another fun week of Makeover Monday complete and, once again, I learned a TON! Enjoy!

August 12, 2016

Michael Phelps vs. The World

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Is Michael Phelps the greatest Olympic athlete of all-time? It’s be tough to argue against that. As of this writing, Michael Phelps was won four more gold medals at the Rio Olympics, only adding to his legend. To give this some context, consider this chart. Yeah, he’s pretty good!

The Data School Gym - Population Pyramids


Today at the Data School, Amanda Patist was giving an Alteryx demo and she used worldwide population data. That got me thinking about population pyramids; I’ve always wanted to build one. When I create this, it required a few tricks to get it just right. So I thought I’d post it as a Data School Gym challenge.

Think you can rebuild it? You can download the XLS or the TDE and give it a go.

The small line chart show the % females and % males. The big chart shows the population. Post a link with your solution before you download mine.

Good luck!

Ignore the gray lines that are going across the viz. That’s a bug in Tableau 10.

August 10, 2016

The Data School Gym - Sorting a Dimension Member to the Top


A fun Data School Gym challenge for you today. Using this data source of human height since 1896, create this visualisation:


  1. Each country should show only 1896 and 1996 and they should be connected
  2. Label the midpoint with the country name
  3. Use an orange to blue diverging color palette based on the Avg Height
  4. Allow the user to filter by sex (no All option)
  5. Create a parameter to allow the user to pick a country; it should also include an (All) option
  6. Use the parameter to sort the visualisation; (1) If (All) is chosen then sort from largest to smallest based on the 1996 value. (2) If a specific country is chosen, that should be displayed at the top and the rest should be sorted from largest to smallest.

When the user picks Bermuda, for example, the visualisation should look like this:

Here’s the interactive version. Post a comment with a link to your solution. Good luck!

August 9, 2016

Tableau Tip Tuesday: An Intro to Device Designer

In this week’s tip, I walk you through how I’ve learned to use Tableau 10’s Device Designer feature, which makes it so much easier to create device specific designs.

Note: I ramble a bit at some points in this video as I learn some things along the way and I also hit some wifi issues, so I apologize in advance. Hopefully this helps you see that no one is perfect and we’re all on this journey of learning Tableau together.