For week 33, we look at the episodes of all of Anthony Bourdain’s TV shows. I need to start with two thank yous:

  1. Christine Zhang for creating the data and creating the viz to makeover.
  2. Ann Jackson for co-hosting Viz Review with me; I learned a lot from hearing her critiques.

The original visualization was a simple map, so naturally we saw a lot of maps this week. We’ve written many lessons on mapping before, so this week I’ll focus on something else.



Since he’s started participating in Makeover Monday, Rodrigo Calloni has made very impressive improvements and his designs, to me at least, are easy to distinguish as his; he sort of has a signature. This week, I could again tell the viz was his by its style, however, as he said in his tweet, it’s big. In fact, it’s too big a too complicated, which for me, made it distracting.

I find that listing every single day across all of these years to be way too much detail, and it’s detail that does not add to the understanding of the viz. These were obviously weekly shows, so having all of the days is superfluous detail. In addition, the title states that the viz is about Bordain’s shows first aired. If that’s the case, then why show every episode; again, the additional detail is distracting.

I’m quite certain Rodrigo learned a lot creating this, which is fantastic. However, it’s important to understand the audience (i.e., anyone who sees his viz) and to ensure they understand the data as quickly as possible.



Even the best analysts and visualization experts struggle at times. This week, Iron Viz Europe finalist Daniel Caroli tweeted:

Last week, there was lots of positive feedback for Eva’s pre-publication checklist, so this week I’m providing you with my approach when I’m stuck or don’t understand the data.

  1. Identify the Challenges – Start by reading the article that we link to. Read about the topic. Write down keywords, definitions, acronyms, anything you can think of about the topic. Literally write it down on paper.
  2. Examine the Metadata – What are the data types? What’s the range of the data in each field and what do those mean? Is the data complete?
  3. Explore the Data – Build lots and lots of charts. Try to gain an understanding of the data. How much variety do the fields have? Is there a data hierarchy? What happens when you compare data across fields? Does one field affect another? What do the metrics mean? How much distribution is there in each metric? How can you aggregate the data?
  4. Remove Unnecessary Fields – Once you’ve explored the data, remove the fields you don’t need. This will help focus you on the data that is important and relevant to the questions you are trying to answer.
  5. Focus on a Subset of the Data – Filter or limit the data to reduce the complexity
  6. Create a Sketch – You should now have context for what you want to create. Step away from the computer and sketch some charts on sticky notes. These should be very rough sketches. Move them around on a big piece of paper until they form a cohesive message.
  7. Turn the Sketch into Reality – Get back on the computer and recreate what you sketched in your data viz tool. I promise you that sketching first will speed up this process significantly.

Hopefully those are tips that will help you next time you are stuck. They’ve worked for me for years and years. Now onto this week’s favorites.



Author: Staticum
Link: Tableau Public