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).

Last Friday I had the pleasure of attending Andy Kirk’s full-day ‘Introduction to Data Visualisation’ training course with four of my colleagues from Facebook.  If you don’t know Andy, he’s the person behind the excellent data viz website Visualising Data and author of the new book ‘Data Visualization: a successful design process’ (I get my hands on a copy sometime next week).  If Andy’s ever in your area (or your company is ok with a bit of travel expense), I highly recommend his course.

In the course, Andy outlines an five-step design methodology:

1. Establishing purpose and identifying parameters
2. Acquire, prepare and explore your data to begin familiarisation
3. Establish editorial focus about your subject matter
4. Conceive your visualisation design
5. Construct, launch and evaluate your visualisation solution

After each of these steps there’s a hands-on group exercise to put each methodology into practice.  The final exercise, “Develop a visualisation concept solution”, required us to take a set of data that was a bit messy (I think Andy did this intentionally but he wouldn’t admit to it), and apply all of the lessons we learned to improve this viz (click on it to make it larger).

The idea was to start with a blank slate, intentionally walk through each step of the design methodology and see what you can build in 45 minutes.  Each team then presented back to the class.

Our team consisted of a MicroStrategy trainer, a data engineer, a BI engineer and myself.  It was such a great experience to build something together and talk through our design…BEFORE we built anything.  Here’s what we came up with:

Andy’s design methodology worked perfectly!  I was amazed at how simple it was to create a usable design, in a short period of time, by slowing down and asking questions that help organize your thoughts.  When I teach, I recommend asking questions as well, but the way Andy recommended asking questions was a bit different than I had done it before.  I can’t wait to use it on a real project.

Thanks Andy, not only for this fabulous course, but for coming to speak to us at Facebook as well.

We’re all familiar with the blockbuster movies from our own generation, but what about all time?  I downloaded the data from Box Office Mojo to find out.  The data I’m using is inflation adjusted.

Immediately jumping out to me:

• There was a large increase in the number of movies in the top 100 from the 1930s to the 1970s.  This isn’t very surprising given the growth of the industry as a whole.  Click on the 1970s on the bottom-right bar chart; there were some awesome movies that decade.
• There was a big dip in the 1980s.  Did the awful music of the decade play a part?  It’s a good thing Steven Spielberg and George Lucas were pumping out movies.  They basically owned the decade.
• Interesting in the 2000s is that most of the movies in the top 100 have lots of special effects
• From the sparkline I see that all but five years between 1963 and 1984 are below the average gross earnings.  But, what’s most surprising to me is that this list of five includes "The Empire Strikes Back”, “Return of the Jedi” and “Raiders of the Lost Ark”.  I would have never guessed those would be below the average.
• In the top 5, I still haven’t seen “Gone with the Wind”, “The Sound of Music” or “The Ten Commandments”.  I fall asleep every time I start watching them.

What do you see?

NOTE: See a similar post by Ross Perez on Tableau’s blog for the highest grossing movies since 2001.