For week 21, I intentionally chose a topic about the Brits because of our Makeover Monday Live in Paris. Why? Because the French love making fun on the Brits and the topic got them immediately engaged. I also found this topic quite interesting because as an American living in London, the pub culture can be quite overwhelming.

The data set itself was pretty simple. People surveyed fell into one of three categories of drinkers, the survey was conducted over several years, and it was split out by gender and age. There were a few traps I thought people might fall into, which I’ll get to in a bit.

MAKEOVER MONDAY LIVE

The more that Eva and I run Makeover Monday Live events, the more we realize how incredibly good the format is for introducing people to Tableau, the Community and the project. Eva has written a recap of the day here, and here are my highlights:

• Only about 2 of the almost 30 people there had previously participated in Makeover Monday, which meant lots of new people getting introduced to the project.
• Splitting people up into teams helps break down boundaries.
• The French are quite funny! They were really excited to present and boy did they deliver!
• Hang out after Live events; it’s a great way to get to know others in the Community.

I only noticed two traps that people fell into this week.

LESSON 1: AGGREGATING DATA THAT’S NOT AGGREGATABLE

This data set contained percentages of survey responses. Since the source did not include the number of responses as well, it means you cannot aggregate the data. I saw a few times when people took the average of all of the responses by gender. And others where people summed up the response rates. This isn’t mathematically accurate. Be careful when working with percentages. Unless you have the numbers that form the percentages and can create the weighted calculation, you should avoid aggregating the data.

On the positive side, everyone that I gave this feedback to realized their mistake and corrected it.

LESSON 2: USING PERCENTS OF PERCENTS

Many people this week looked at the year over year change in drinking habits. Great! Well, mostly. Like I mentioned, the data was percentages, so when you are calculating year over year, you should use the difference, not the percent difference. Let’s look at an example.

I’ve filtered this to one age band and one question. I then applied a difference to first table calc by year. This tells us that 14% fewer people aged 16 to 24 drank alcohol in the last week compared to 2005.

Compare that to this view, where I’ve applied a % difference to first table calc by year. This implies that 23.4% fewer people aged 16 to 24 drank alcohol in the last week compared to 2005.

But this isn’t accurate. This is take the percent change between two percentages. Basically, be careful when working with difference calculations if your measure is a percentage.

I have a ton of favorites to highlight this week. There were a lot of really, really good examples and I think they all deserve recognition. With that, here are my favorites from week 21.

Author: Alex Barday
Link: Tableau Public

What I like:

• Simple design that’s easy to understand
• Good use of one color as a range
• Clearly labeled
• Gridlines to help guide the eye
• Really cool as a GIF

Author: Pablo Gomez
Link: Tableau Public

What I like:

• Consistent use of color
• Dotted lines for each gender on either side of the both genders line
• Small multiples layout
• Summary text for context
• Title in the form of a question

Author: Louise Shorten
Link: Tableau Public

What I like:

• Nice overall layout
• Using a different color for each gender to separate the viz
• Small multiple area charts with a line on top look pretty slick!
• Visually engaging
• Nice use of icons

Author: Paul Albert
Link: Tableau Public

What I like:

• Great use of directional lollipops
• Simple design that’s easy to understand
• Subtitle that tells me how to read the viz
• Minimal use of color
• Good axis title

Author: Geoffrey Felix
Link: Tableau Public

What I like:

• Using a separate color for each heat map makes you look at them individually
• Using a question in the title
• Simple layout
• Very clean looking viz
• He built this in under an hour at the Paris TUG

Author: Mark Bradbourne
Link: Tableau Public

What I like:

• Love how Mark iterated on this to make it better and to correct the aggregation mistakes
• Nice annotation
• Lack of color
• Good title that makes the point clear
• Nice footnotes
• Nothing fancy; a simple bar chart works perfectly

Author: Naledi Hollbruegge
Link: Tableau Public

What I like:

• Including text for additional context
• Dotted borders around the charts help frame them
• Consistent use of color across the charts
• Having a summary in the first chart with a more in-depth look below
• Titles on charts are very clear

Author: Sue Grist
Link: Tableau Public

What I like:

• Great use of highlight actions
• Including key notes as callouts
• Simple small multiples design
• Using a question in the title
• Including instructions
• Chart choice shows the trends clearly

Author: Robert Reif
Link: Tableau Public

What I like:

• Engaging design
• Super creative idea!
• Simple title that tells me what I’m seeing
• Excellent description and summary in the sub-title
• Varying the colors behind each bottle to break up the view
• Including the value on the bottle since there isn’t an axis

Author: Tom O’Hara
Link: Tableau Public

What I like:

• Title tells me the story
• Simplifying the view to a single question
• Engaging design; the vertical time works really well
• Nice labels on the ends of the lines
• Using a different color for each dot