This week's data set only contained one measure, two years, and country names. This meant that I had to focus on charts that help visualize comparisons.

This week's data set was pretty simple. We had 21 baseball seasons and a column for each pitch type. Pivoting the metrics made it much easier to work with for me as I could then split the view by pitch type.

During #WatchMeViz (below), I create a trellis view, showed how to create groups, sets, set actions, sparklines, LODs, custom number formatting, creating a mobile view, and more.

Thank you for tuning in. Here's the video and below is my visualization.

My goal this week was to correct my failures from last week, so I focused almost exclusively on building the starburst/sunburst chart. As promised to the viewers, I will also record a separate tip video for how to build them.

Here's the WatchMeViz and the viz is below that.

Well, this was a pretty epic fail. No, it was a really big fail. Those that tuned in to Watch Me Viz will be well aware of my struggles with this data set. I don't know why. Maybe it was a concentration issue. I hope it was still useful to everyone, and I hope it was good to see someone with so much experience still struggle.

UCAS is a service that helps people find open placements universities in the UK (and hopefully place them). I found this particular data set quite confusing until I looked at this viz from UCAS. I then understood that we were basically looking at the number of applications from UCAS based on the time that has elapsed since exam results days. That probably took me a couple hours to wrap my head around.

The original viz for this week was so good that I struggled to come up with something different. In the end, I wanted to learn by recreating the original. Check out #WatchMeViz and interact with the viz below.

This week's Makeover Monday was about representation of women in national parliaments and governments in the EU. 

Trellis charts are a version of a small multiples chart that organizes the dimensions in the view across a grid. In this tip, I show you how to create a trellis chart that will work even when you are missing data.

Trellis / Panel Chart Calculations

//Columns
(index()-1)%(round(sqrt(size())))

//Rows
int( (index()-1)/(round(sqrt(size()))))

Steps

1. Create the column and row calcs
2. Create a custom date
3. Place custom date on columns, measure on rows and dimension on detail
4. Place column on columns, row on rows, and custom date on detail
5. Ensure dimension is above date on detail shelf
6. Change custom date on columns to ATTR
7. Configure table calcs
1. Check both the Dimension and the date field date in order
2. Ensure the dimension is above the date field in the Specific Dimensions section
3. Set "At the level" to the dimension

I found this week's data set super interesting. There was so much to explore. I could probably have gone for hours trying different charts and making lots of comparisons. Here's the video from the Watch Me Viz session.

ORIGINAL CHART

WHAT WORKS WELL?

WHAT COULD BE IMPROVED?

MY VERSION

This was a tough one. For Workout Wednesday week 22, Lorna set out the challenge of reproducing a trellis chart with each pane being a separate Pareto chart or sales vs. number of orders.

Great! That part was pretty straightforward. I've done a Pareto tons of times. I've done a trellis tons of times.

Then there was the coloring of the line. That is, the line needed to be colored in each pane up to the point where two reference lines meet. I got that right way...so I thought.

Lastly, there was the little detail (i.e., not so little) of creating dynamic reference lines that update based on both the parameter selected and the point which you hover over. The fact that these are two conditions should have been my first clue.

I spent quite a while on the reference lines trying to make one reference line act upon two calculations. Well...that's not how reference lines work. Then it hit me that I actually needed four reference lines. Two of them will always hide based on the option selected in the parameter.

PROGRESS!!!!

The calcs were fiddly. I got lost in the logic a couple times because what you have to do is a bit counterintuitive, kind of like double negatives. I wrote down the four scenarios so that I could approach them one by one.

My calculation names are a mess, which drives me insane and actually made getting to the solution much harder. I'm normally very good about making sure I have clear names, but in this case I had several with almost the same name, so I kept mixing them up, hence why writing things down helped.

Once I got that figured out, I was done. A bit of tidying, then I downloaded Lorna's solution to compare mine too. We had taken a nearly identical approach (it must be that teacher she had at The Data School that set her on her way).

Thanks for the challenge Lorna! I enjoyed the struggle and always love the eureka moments. This was another viz that I could easily see used in a business context.

Ok, part 2 of this week's challenge, the Jedi version, really sucked (requirements here). It took me FOREVER! I used table calcs for all of the calculations and getting them just right took a really long time and a lot of experimenting. Surely Tableau can make this easier for us.

Some thoughts:

1. Getting the subcategories to layout correctly in a trellis plot was easy.
2. Getting the labels above each grid was easy.
3. Getting 10 dots across each pane was easy.
4. Getting the stacking of the dots in rows was a pain!
5. Luke has an evil side.

Luke is back and he has posted two challenges this week. First, create a pictogram of the top 5 subcategories that have sold the most products. They should be represented in 100 dot sections and colored depending on the section they are in. Get the requirements here.

There were two requires that I didn't need to use to make it work:

1. Set the minimum and maximum values on the columns axis (x-axis) to -3 and 12, respectively.
2. Set the minimum and maximum values on the rows axis (y-axis) to -1 and 32, respectively.

That Emma! She's quite the sneaky stinker! For Workout Wednesday Week 26, she asked us to build a trellis chart full of slope charts that compares election results by political party by constituency for 2015 vs. 2017.

Fortunately, I have my trellis chart calcs safely saved in my notes, so I didn't have to Google those. The tricky bit for me was the sorting. I'm not going to spoil how I did it for you, but you can download my workbook to see how I did it. As usual, Emma and I took very different approaches for the calculations required for the sorting. She used LODs for all of her calcs, I only used one. They both work though! It all depends on how your brain works I suppose.

The data prep parts were pretty straight forward (thank you Emma for alerting us to the need to do this). Emma loves little tricks in the formatting, but I didn't see any this week.

One thing I did different was to provide a "buffer" for the year labels. I place them 10% above the highest value so that they don't overlap the slope chart lines. Emma's year labels sometimes overlap with the slope chart lines. Just a personal preference for me.

Great fun Emma! Thanks! Took me about 90 minutes including this blog post on the train from Frankfurt to Hamburg. Great use of my time! #AlwaysLearning

Click on the image for the interactive version and to download.

For Workout Wednesday week 7, I challenge you to build this dynamic trellis chart. Special thanks to Chris Love for explaining to me why the trellis works the way it does. He has a great blog post series over on The Information Lab blog.

In this example, I'm using the same Superstore Sales I've used in previous Workout Wednesdays. Here are the guidelines:

1. Match my colors.
2. The user should be able to choose the level of detail they want for the date.
3. The date axis format should not change, irrespective of the date level chosen.
4. The user should be able to pick from the list of dimensions shown.
5. The dimensions should be sorted from upper left to lower right based on the sales in the most recent time period.
6. Match my tooltips. Note that they change based on the options the user selects. Pay attention to the date formats in particular.
7. The title should update dynamically based on the date level and dimension selected.
8. The end of each line should be labeled to the right of the last point. 
9. There should be a little circle on the end of each line.
10. Each section of the trellis should include a label for the value of the dimension for that section. E.g., California should be on the upper left when you selected quarters by state.
11. The dimension labels should be centered in each section.
12. There should be no gridlines, but the zero line should be included.
13. Each row should should have a light divider between them.
14. My final view is 900x700.

If this post turns into a bit of rant, bear with me. Let's start with the Tweet that got me worked up:

Interesting @OECD chart on alcohol consumption. By country & trend. E.g Austrians drink twice as much as Italians pic.twitter.com/OOGYJ3BpAq

— Paul Kirby (@paul1kirby) October 19, 2016

You might think "It's just a chart Andy, relax!" True. It's a chart. It's not changing the world or anything. There are several things that have me a bit upset:

1. Paul Kirby calls the chart "interesting" and maybe the CONTENT is interesting, but the chart is terrible.
2. He says "Austrians drink twice as much as Italians", a fact that is simply not true. They drink 61% more than Italians. You can't just spout facts like that.
3. Paul is visiting professor at the London School of Economics. I can only assume that his students follow him on Twitter. When he tweets things like this, his student will assume that this is how charts should be made, which only proliferates the number of poor charts we'll continue to see.