Twitter follower Sean Trout sent me a link to this tweet from OECD:

The global talent pool has never been larger, will grow to 2030, read http://t.co/aA9AyLEXta (pdf) #education #stats pic.twitter.com/aiIiTDbZt9
— OECD (@OECD) April 24, 2015

These pie charts are part of a larger study conducted by OECD, which you can read here. Some thoughts about these pie charts:

1. The author is trying to show the change from 2013 to 2030. Using two pie charts makes this more difficult than necessary. At least, though, they kept the countries in the same order.
2. The pies do not add up to 100%, I assume due to rounding. The 2013 pie adds up to 101% and the 2030 pie adds up to 102%.
3. The focus is on the top 20 countries, so the “Other” category isn’t needed.
4. The labels on the pies include both the country name and the value. A table would be better than this. Adding all of these labels makes the chart way too busy.
5. There are two key metrics in the data: share of degrees and the number of degrees. The pie chart doesn’t provide enough context for understanding where the number of degrees will be coming from.

Given all of the above, I decided to create a slope graph.

1. I included a parameter which allows you to select the metric. 
2. This option, along with using a slope graph, really helps show how dramatic the change is for China and India. 
3. Switch back and forth between the parameter options and you’ll see quite a different story.

Jeffrey Shaffer and I are two weeks into a year-long weekly hand-drawn data viz project we’re calling Dear Data Two. The project is entirely modeled after the Dear Data project Giorgia Lupi and Stefanie Posavec are doing. Jeffrey and I thought this would be a great way for us to remove ourselves from software and work on being more “artistic”.

The week 2 theme was “Transport”. Jeffrey tracked his step pattern around his office.



While I tracked the places I went all week and how I got to each place. What was different for me this week is that I started with Tableau and then went to hand drawn. Going forward, you can keep up with the project at www.dear-data-two.com, where you can read more about our thoughts and how we created each postcard.

Retired Two-time Alteryx Grand Prix Champ Chris Love put a post on G+ today to the Information Lab team asking us to test a new Alteryx module he’s working on. The gist of it is:

1. You put a bunch of PDFs into a folder (as many as you’d like)
2. Run the Alteryx module
3. Alteryx spits out a Tableau extract and workbook that count how many times each word appears in the PDFs

Keep an eye on The Information Lab Blog for more details. Chris is going to write a post soon on how he built this. It’s genius!

For my testing, I decide to run the module against the PDFs of the course materials that Stephen Few gives you at his Visual Business Intelligence Workshop. These PDFs average 25MB (i.e., that’s a lot of words). Chris provided a simple word cloud output as part of the package he wrote. I took that and added a bar chart and a parameter. Anyone that uses Alteryx is going to love what Chris created, pun intended.

OMG I can’t wait! December can’t get here soon enough! The folks over at Star Wars announced Tuesday that there were over 88M views of the second trailer in the first 24 hours.
What better way to celebrate than with a viz? Picture Star Wars as a country, located precisely where Null Island is today. And assume trailer views = population. The Force Awaken would be the 15th largest country in the World!

Today’s tip is about embedding YouTube videos and Soundcloud audio into a Tableau dashboard. It’s pretty simple. Scroll down below the viz for the instructions. May the Force be with you!

First, let’s get the YouTube video embedded.

1. Drag a Web Page object onto the dashboard.
2. When prompted for the URL, you want to grab the embed code:
3. Copy the string after the “src=“ and add "?rel=0&showinfo=0” onto the end of it. The URL should look like:
   

The process for embedding audio is much the same.

1. Go to the track on Soundcloud.
2. Click on the Share button.
3. When the share window appears, click on Embed at the top.
4. Scroll to the bottom and click on More Options.
5. Choose the size and check the Automatic play box.
6. Copy the embed code.
7. Select the text after the “src=“ and copy it
8. Add a Web Page object onto the dashboard.
9. Paste the copied text in the URL box.

That’s it!

Last week the Premier League published the first (sort of) detailed stats on their Fair Play League table. Quickly thereafter, all of the news outlets reports how Chelsea basically treats the refs like garbage. Anyone that watches the Premier League, even Chelsea fans, knows this is true. Don’t deny it folks!

As I was scouring the various reports, I didn’t see anyone actually create a viz on the subject. The best I found was this table from The Daily Mail:


A table is great for ranking and looking things up, but terrible for doing any sort of analysis. I downloaded the FPL table into Excel (here) and combined it with the BPL standings as of the same date.

In the viz below, I’m using Chelsea as the baseline for comparison, because the story that interested me was how much worse does Chelsea behave compared to the other teams. For example, if you hover over Liverpool, you will see that Chelsea is 14% worse with its respect for referees.

I then added a second tab that allows you to explore the data on your own. Pick a FPL stat, a BPL stat and you can compare and contrast. The question I wanted to answer here was “Is there a relationship between FPL and BPL stats?” I can’t find any interesting relationships, but maybe you can.

It's election season in the UK and The Guardian recently released some data related to Prime Minister David Cameron's travels around the World. They provided a table of all of the data at the bottom of their post, but the only viz they provided was this view aggregated by continent.


First, bubbles make comparisons harder than they need to; bar charts are much better for comparisons. This view also doesn't provide any addition insight. I can't answer a simple question like "Which countries did Cameron visit in Europe and when?"

I only had a few minutes this morning to create an alternative and here's what I came up with in about 15 minutes.

Loftus Road - home of QPR FC

Stamford Bridge - home of Chelsea FC

Shortly after I posted my run on Instagram, someone commented that I had missed a nearby stadium. Naturally I thought I needed a viz to keep track of the stadiums I have visited. I found the geocodes for more stadiums here, but it was missing a few teams. I created this csv to track the stadiums where I’ve seen games. I’m going to do my best to keep up with it. This viz includes the first four divisions in both English and Scottish football (as of the 2014-15 season).



And yes, I know I titled this post "English" and Scotland is not part of England, but UK football stadium tracker doesn't resonate as well with me.

It's my first day on the job with The Information Lab, so what better way to celebrate my first day and the release of Tableau 9 than with a video tip.

Friend Jeffrey Shaffer sent me this tweet for as a makeover candidate:

A pie and donut in one chart for comparing year vs. year? That's a new one for me. #slopegraph http://t.co/TLtx2lYpY8 pic.twitter.com/4Ukd3faH6o
— Jeffrey Shaffer (@HighVizAbility) March 24, 2015

It’s obvious what the creator of this viz is trying to do...show the five year change for each car model. The problem is with their choice of visualizations. They placed a pie inside a donut. Both of these chart types are not only hard to read, they have them in reverse order as well. If they insist on using this type of graph, they should place 2010 on the outside and 2015 on the inside.

However, a much better alternative, as suggested by Jeffrey is a slope graph. I’ve not only included the slope graph, but I also include a bar graph to show the five-year change.


You can download the data here and the Tableau workbook here.