VizWiz

This week for #MakeoverMonday, Eva was ever so kind to pick a topic that I really enjoy...Arsenal! She did this to coincide with my 800th Tableau Public viz. More about that in a future blog post.

Here's the original viz:

SOURCE: transfermarkt.co.uk

WHAT WORKS WELL?

• A table is a simple way to display stats that serve the purpose of looking up values. That seems to be what the designer had in mind here. This viz isn't for comparing players.
• Being able to sort by the headers
• Including an image of the player; this helps those that are already familiar with them.
• Including links to the player's profile

Week 29 has us analyzing the changing frequency of sex by Americans. Thank you to Pablo Gomez for bringing this chart to my attention.


What works well?

• Overall, the chart is really good. 
• The title and subtitle make it very clear what the viz is about.
• The labels focus you to the topic the creator wants you to focus on.
• I like how the first year is a filled dot and the last year is an open dot.
• Bolding the first and last years on the axis
• Including the % sign on the y-axis for only the top value

In this week's tip, I show you how to create a parallel coordinates plot. If you want some additional practice, this chart type was used in Workout Wednesday 2019 Week 49.
What is a parallel coordinates plot? Here's the definition from The Data Visualisation Catalogue:

This type of visualisation is used for plotting multivariate, numerical data. Parallel Coordinates Plots are ideal for comparing many variables together and seeing the relationships between them. In a Parallel Coordinates Plot, each variable is given its own axis and all the axes are placed in parallel to each other. Each axis can have a different scale, as each variable works off a different unit of measurement, or all the axes can be normalised to keep all the scales uniform. Values are plotted as a series of lines that connected across all the axes.

This workbook uses data from the NBA Stats website. You can get the data by downloading the workbook and unzipping it.

Enjoy!

There's way too much negativity in the news about migrants being terrible people, causing problems in their new countries, being rapists and bringing drugs. Every human being deserves to live a happy and safe life. Period.

This week's topic relates to asylum seekers in the EU.

Source: European Asylum Support Office

What works well?

• Map allows for exploratory analysis
• Using a time series for the years
• Informative tooltips
• Single continuous color scale for the pending cases
• The time series overall clearly show the growing trends.

Dot maps, density maps, round maps, square maps, hexbin maps, emoji maps...this video shows you how to build all of them.

Confession: I have never seen a single second of Game of Thrones.

Now that I've admitted my shortcoming, I would like to thank David Murphy for volunteering his viz and data set for this week's Makeover Monday.

From the perspective of an analyst, this is exactly the kind of data I love; data I know nothing about. This helps me approach the data without any bias and to ask simple questions of the data before deciding on my visualization. More on that after a quick review of David Murphy's viz.


What works well?

• Visually, it captures your attention quickly.
• The person chosen, profile picture, and summary of people killed gives a quick summary before the viz goes into more detail.
• The viz is designed to go into more detail as you scroll down.
• The headers of each section look really cool and break apart the viz well.
• Using a bar chart to rank the killers.

On Saturday, I was catching up on some Workout Wednesday challenges. Week 51 2018 was a challenge from Rody Zakovich to learn about using containers to control the padding on dashboard objects. I love the way this looks so I wanted an excuse to put it into practice.

I received the weekly data.world newsletter on Friday and it contained a data set about the Canadian Consumer Price Index. Given I had just completed the padding challenge, this made for a relatively quick exercise.

In addition to working on the padding, I also incorporated Parameter Actions that allow the user to choose an item to explore.

Here's the lesson: the only way to get good at something is to practice, relentlessly. Find reasons to practice; don't wait for them.

Let me know what you think about this design...thanks! Click on the image for the interactive version (it's too big to fit in a window on this blog).

For week 26, Eva challenged us with making over this visualization from World Atlas:

Source: World Atlas

What works well?

• Clear title
• Countries are listed in decsending order
• Simple color for the bar chart
• Labeling the axis

In preparation for #WorkoutWednesday Live at TC Europe, I wanted to warm up by completing week 24. Luke challenged the community create a "simple" side-by-side bar chart.


While I can understand that this is something that could be used in a work setting, I think the juice you get from building it aren't worth the squeeze. In other words, there are too many hacks to get it to work. Still, though, it was a fun exercise.

1. The calculations are quite simple.
2. You don't need table calculations.
3. I chose the advance option, which I first tried by using another measure to space out the bars, but that didn't work so I created three separate sheets with blank containers for spacing. This hurt my soul, but it got the job done.
4. I don't agree with creating a percent change of percentages. For example, it's hard to comprehend that Home Office has a 28% great contribution to furniture than to the overall. That doesn't make sense to me. When I see the numbers, I view it as 0.7% greater contribution. Maybe I'm misunderstanding the purpose.
5. I don't like having to create a dummy sheet for the footers. That's not Luke's fault though; it's a limitation of Tableau that requires the workaround.

In this week's tip, I show you how to use the makepoint and makeline functions that became available in Tableau 2019.2 to create routes. I show two examples: airline routes, and bus routes. The bus routes also shows you how to use a calculated join to bring one row up to the previous row.

Leave a comment if you have any questions.

This week, the #MakeoverMonday roadshow is in Berlin for TC Europe. We hosted a live event this afternoon with a few hundred of our closest Tableau friends. Since we're in Berlin, I found a data set and visualization about Airbnb listings and reviews from Inside Airbnb for everyone to use.


What works well?

• Since the data is about finding a place to stay, a map is super intuitive for the user.
• The map helps show concentrations of Airbnbs.
• The summary stats on the right help add context.
• There are some good filtering options.

As I continue catching up on WW, I went to week 20, which was a live event at the SFTUG, so I knew it had to be solvable quickly and wouldn't require any crazy calcs. The goal was to create a view that:

1. Groups together the top 10 States, bottom 5 States and all other States based on their total orders.
2. Shows all other States as an average number of orders across the States
3. Display the 2018 value plus the change vs. 2017 on the end of the bar with arrow indicators for the change
4. Show different colored bars for 2018 depending on the groups created in step 1 above

It's #PrideMonth, which makes for perfect timing for this week's makeover. Eva has chosen a simple line chart that allows the user to answer a simple question: "Is it wrong for same-sex adults to have sexual relations?"


What works well?
What I did
I like the overall design of the original, so I decided to clean it up and change the main metric to answer the question differently.

1. I removed all of the dots from the lines.
2. I allow the user to highlight an age via a parameter action.
3. I changed the metric on the change from % of population to the change vs. 1973. For me, this is a more meaningful way to show the change in opinions.
4. I moved the title closer to the chart.
5. I used Benton Sans as the font (Tableau fonts get boring sometimes).

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.

I haven't done a Workout Wednesday in quite some time, in fact, this is the first one I have done this year. However, when I saw Curtis Harris' challenge this week (check it out here), I knew I wanted to give it a try. Why? Because it's a view that is very usable in a business context. I could certainly see this being used on a mobile phone in a real business.

REQUIREMENTS

• Create a bar chart which displays the sub-category label on top of its bar
• Label all bars to the right of the maximum value in view
• Create a parameter that changes the display from a percent of total view to a raw order count view
• Create a progress shadow for every bar
• Show progress to 100% or progress to the maximum value depending on the parameter selection
• Only use one sheet
• Match formatting and colors
• Match tooltips

A couple weeks ago, I finished Matthew Walker's amazing book Why We Sleep. I cannot recommend this book enough. It's both fascinating and terrifying. And if it doesn't change how you look at sleep, I'd be extremely surprised.

Given how this book impacted me, I wanted to find a topic about sleep. I found the American Time Use Survey, the best data I could find on the topic. As it turns out Matthew Walker is hosting an event on London Thursday night that I've bought tickets for. What amazing timing!

Here's the original viz from the ATUS:


What works well?

• It's a simple side-by-side bar chart that makes comparing men to women easy within each age group.
• Clear axis title
• Labeling the bars can help with interpretation
• Ordering the ages chronologically
• The title is simple.
• I like the line that divides the title from the chart.