Data Viz Done Right

April 13, 2015

Makeover Monday: David Cameron's Overseas Trips

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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.

April 12, 2015

English Football Stadium Tracker

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Today is Sunday, which means it’s Sunday Long Run. Those of you that are runners know what I mean. I moved to London last Saturday and my goal for my runs is to use them as a way to explore new places. Yesterday, I went to see Leeds United play with a friend from Atlanta who grew up a Leeds fan.

Today, I set out to see some football stadiums. I mapped a route that took me from Wimbledon, past three iconic football stadiums.

Craven Cottage - home of Fulham FC
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.

April 7, 2015

Tableau Tip Tuesday: How to Create a Moving Reference Line

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.

Over two years ago I wrote about how to create a reference line for today. In this week's tip I take it step farther, by showing you how to create a moving reference line based on user input from a date parameter.


April 6, 2015

Makeover Monday: As the Wheels Turn | 5-yr Change in Percentage of U.S. & Canadian Content in Car Models

Friend Jeffrey Shaffer sent me this tweet for as a makeover candidate:
It’s obvious what the creator of this viz is trying to 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.

March 31, 2015

Makeover Monday: What is Montreal’s Best Gym?

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In the comments to last week’s makeover, reader jorgeluis500 pointed me to this 3D pie chart that needed a quick makeover:

There are a few obvious flaws:

  1. It’s a pie chart.
  2. It’s 3D.
  3. The “Other” category is sorted first, when it should be last.
  4. Sorting “Other” first takes away from the focus of the story.
  5. There are way too many colors/slices.
  6. The amounts are repeated in both the pie and the legend.

Here’s my makeover, a boring bar chart, done with infogram:

March 27, 2015

An Analysis of My Commute on Facebook's Dublin/Castro Valley Shuttle

The irony of it all.
  • I’ve been riding the Facebook shuttle to work for almost a year.
  • I’ve been tracking my commute time via Swarm check-ins.
  • I decided to drive to work yesterday for my last day.
  • I got my first ever speed ticket on my way to work.
I started building the viz below a while ago and decided to finalize it since I had collected all of the data I could. I would like to thank Anya A’hearn for her feedback on my design (note to self: Anya hates lollipop charts). I also need to thank Jonathan Drummey for his help in getting my time calculation formatted correctly (he pointed me to this post).

Anyway, here is my analysis of my commute to work on the shuttle. There are filters for the time of the commute and the schedule. Use the drop down to select various displays: the default is a calendar view and the other views are various dot plots.

Click on the image for the interactive version.

March 25, 2015

Tableau Tip Tuesday: Creating Box Plots in Tableau

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Yes, I know it's Wednesday and I'm a day late with getting this post out, but I kind of having a lot going on right now, so please forgive me. Since Thursday is my last day in the Facebook office, I thought it would be fun to show how to answer a critical question:
How often do I go to the Sweet Stop and when?  HINT: It's not as often as you might think.
To collect the data, I used Swarm to check-in to the Sweet Stop. Each check-in is logged into Google Sheets via this IFTTT recipe:

I then exported the data to Excel and connected it to Tableau.  Download the data here and the workbook used to create this video here (requires Tableau 9).

March 23, 2015

Makeover Monday: Who’s Really Using Social Media in 2015?

Back in January, AdWeek published this infographic with their predictions for growth of various social media platforms in 2015.

Wow! That's quite a bit to digest. So much going on, from the donut/pie charts, to all of the annotations, to the sizing of the pies by overall growth. This infographic has it all.

I recreated the data in Excel, which you can download here, and decided to build a couple of different alternatives because the design choices depend on the question that's trying to be answered. This first version aims to show which social networks are predicted to grow the most in each demographic.

Looking at the data this way, it's clear that Facebook will continue to see the largest growth across all ages. This view also makes the following obvious:

  1. Younger people are using Instagram
  2. Older age groups are using Pinterest
  3. Twitter is a middle of the road platform everywhere, which you could spin as a more diverse audience

The second alternative takes the pie charts and converts them all into more organized bar charts. The question being answered here is how is each app doing?

There's a selector at the top right where you can pick the view you want to see:

  1. The spread of growth across each app separately
  2. The growth estimates for each app

Looking at the data this way allows you to compare within a single app, compare to the total and compare across apps.  Which version do you prefer? What would you do differently?

Download the Tableau workbook here (requires Tableau 9).

March 17, 2015

Tableau Tip Tuesday: Two Techniques for Nested Sorting

Early on in my 2-day Tableau courses, I teach about sorting in Tableau. You would think that teaching about sorting would be a pretty boring topic, but it’s easy to get the students engaged when you talked about nested sorting. Another way to think about nested sorting is to consider it sorting by more than one dimension.

In this week’s tip, I review two techniques for accomplishing nested sorting:

  1. Using combined fields
  2. Using the rank function, which has the additional benefit of allowing top N filtering

Download the workbook used to create this video here.

March 16, 2015

Makeover Monday: Most of the NBA's Highest-Paid Players Aren't Worth It

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From Business Insider:
Below is look at the expected salaries for the 12 highest-paid players in the NBA. A player's expected salary is how much of each team's payroll would go to the player based on their percentage of the team's total production.
This is the chart they created:

This chart only shows the expected vs. actual salaries, yet the whole point of the chart and the accompanying article is to show the difference between these two numbers. The side-by-side bar chart forces you to do the math in your head. Why not make it easier for the readers?

I entered the data into an Excel spreadsheet, which you can download here, and created this alternative in