Makeover Monday 2019 Week 1: NHL Attendance

If you've not heard of Makeover Monday before, it's a weekly social data project run by Andy Kriebel and Eva Murray. They've recently released a book, and the assorted blogs over the last 3 years are an excellent repository of knowledge.

Here's some notes on my take on this weeks data.

Data can be complicatedly simple.

When approaching a dataset, I always find myself zipping around to try and find out what's interesting to me. In a project such as Makeover Monday, this is as important as creating something insightful, or beautiful, or interesting. As ever, understanding the data and what's what played a big part in the first moments of playing around with this dataset.

Highlighted in blue are the original fields in the dataset. The rest are bits I've calculated. As you may note, after creating one calculation (Weighted Total Attendance), I got lazy and duplicated, then renamed the fields in this dataset.

But - at a row level, the data is each team, each season with seven data points.

Tableau Shuffle.

My approach of the Tableau Shuffle ended up leading me to a connected scatter plot - I was going to try an approach which looked at home and away attendances, and how they've changed season on season. However - two issues here. One, Vegas' team has only existed for a season and two, the overall league level view was a straight line. Not useful at all.

Maybe one to revisit another time.

So I reverted back to one of my favourite dashboard types - the one chart dashboard. Colour, ordering and visual cues were to be my ally here.
Here's what I ended up with.

Here are some notes on what we see.

• The colour scheme was a random choice - I picked a colour I liked then fiddled with the colour wheel (I used this https://color.adobe.com/create/color-wheel/) until I had a few which I liked. The font is Tableau which works fine.
• Sorting in this case is the average total attendance (both home and away) for the each team, highest to lowest. I used the subtitle to indicate the colour legend in this case, highlighting the red as the 2017-18 value.
• Given I'm a fan of context, the natural next question if you only have the most recent data is, 'how does this compare to previous seasons?' - so they're also visible, but in a less light format.
• The other piece of information I've added is the average of averages - showing the average attendance for all attendances in the data set for each team.

Finally, one part which Mark Edwards liked was the labelling of the maximum and minimum values. This was a bit fiddly - Tableau allows you to only label the maximum and minimum like so:

But, it only allows you align each one way. So if I wanted the top to align to the right of the mark, and the bottom to align to the left - I can't do that. Well, not easily.

I had two options.. I could add in reference lines and make them invisible (this is a trick I've used previously to give breathing room), or in this case I simply used a dual axis.

So each axis is identical, but the top mark section (the collapsed one) shows the maximum value, and is aligned Middle Right, whilst this one which you can see above, the bottom mark section shows the minimum value, aligned Middle Left.

The reason for this is so that I don't have to have a visible axis - so at a glance, the user can quickly see the diverging axis range.

Is this the best way? It depends. View the full viz here: http://tabsoft.co/2R13aXG

Would love to hear any thoughts & feedback! Drop a comment or tweet me, @Scribblr_42.

Thanks for reading!

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Makeover Monday - FiveThirtyEight

I've agreed to partake in the Makeover Monday series which Andy Kriebel and Cotgreave will be doing, which hopefully will encourage me to work with different datasets as well as hone the way I think about data visualisation as a whole. 

If you're also interested in the project, check out Andy's blog post about it here

Accepting this challenge, I took it one step further and also attempted to 'blog' my approach to this week's makeover using story points - I've not used story points at all really, and recently was tweeting wondering what ideas people had for good uses.

I've come to explain the pro's of using a Story Points system over standalone dashboards and tabbing across as Story Points allowing the user to choose one dashboard and cycle through it, highlighting different aspects as the presenter, well, tells a story.

I think this is where Story Points can be powerful - However, I think there's definitely aspects of it which can be honed and amended to ensure that people;

a) use it properly and
b) are able to harness the full power of Story Points.

Andy's post challenges everyone to see what they can do in just an hour; I'll admit I spent just over 2 on this - with about 20-30 more minutes tweaking and then setting up the story points. The formatting itself was the part which took the longest - tidying up tooltips, making sure none of the visuals were overlapping or intruding upon one and other.

I'd love to hear and get some feedback on this makeover - Hopefully the first of many to come!
Oh, a sidenote - I know jack all about baseball.

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