This week’s #MakeoverMonday viz takes a look at polling results in each state leading up to the U.S. Presidential election. The original viz is this interactive “Votamatic” tool at Daily Kos.
This is honestly an awesome visualization. The filter allows you to view the results for each state individually. And the interactive chart lets you hover and view the polling numbers at any point during the race.
So, I decided to look at the data in a slightly different way.
Here’s my Tableau #ElectionViz:
With the start of a new NHL season upon us, I thought I would visualize the historical performance of each NHL team. I used a format similar to my NHL Barcode Viz, except this time it’s not binary; rather, it charts Points Percentage above and below the .500 mark.
I took my inspiration from similar vizzes created by Chris Jones (MLB Franchise Performance) and Matt Chambers (The History of the NFL). I also took some pointers from Andy Kriebel in this blog post.
I have focused on seasons from 1967 to the present, i.e. the NHL’s “Expansion Era”, as only the Original Six teams were in existence prior to ’67. The franchises are ordered alphabetically within their current divisions, and with their current team names. Winning seasons are shown in the team’s colour, while losing seasons are in grey.
Here’s my first attempt at a Makeover Monday viz.
This week’s featured graphic is from the Financial Times. It displays the results of a public transit satisfaction survey conducted across Europe. Respondents were asked to rate their satisfaction with public transit in their city.
So how can we improve this viz? Let’s find out.
Here’s my version:
What improvements did I make?
- Taking a hint from Zen Master Andy Kriebel, I centred the bars around a central axis, showing positive sentiment to the right and negative to the left. This makes is easier to judge the overall response.
- I used an orange-green colour palette, with positive responses in green and negative responses in orange.
- Instead of a traditional colour legend, I used colour-coded text labels along the top of the chart. I also aligned the city labels immediately beside the data bars. And I added data labels on the bars, instead of using a horizonal axis. The intent of these changes is to make the chart easier to read by more directly labeling the data.
Prior to this past summer’s Olympic Games in Rio, I came across an interesting graphic from Reuters titled Precious Medals. It displays the all-time medal standings of the Summer Olympics, and allows you to drill into each country to view its performance over time.
I was impressed with the simplicity, yet sophistication of this presentation. The clean bar charts and appropriate use of colour keep the viz uncluttered. Yet, the interactivity allows a lot of information to be embedded within the graphic.
Naturally, I decided I would try to replicate this visualization myself with Tableau.
The result of my efforts is below:
The “barcode” chart has been used to great effect for visualizing the performance of sports teams over the course of a season. After seeing the work of Peter Gilks (BallCode) and Craig Wortman (MLB Bar Code Chart), I decided to take a run at creating my own barcode viz using the results of the most recent NHL season.
If barcodes can work for basketball and baseball, then why not hockey?
My interactive viz below represents the final standings of the 2015-16 NHL regular season.
The barcode chart shows the win-loss record of each team. I used custom shapes to add the team logos and a custom colour scheme for the barcodes.
I’m generally a proponent of using colour in a chart only when it serves a purpose. In this case, the logos and corresponding colours enable any hockey fan to easily find a team based on these visual cues alone.
To fit my vertical blog format, this version allows you to view one division at a time, which you can choose from the drop-down filter at the top of the viz:
To see all teams at once, check out the full version on Tableau Public.