September 19, 2016
Several people have recommended Makeover Monday for the Project of the Year in the Kantar Information is Beautiful Awards, which I must admit is quite stunning and flattering at the same time. The suggestion for this week’s makeover came from Andy Cotgreave. We intentionally picked something from Information is Beautiful with the hope that it gets a bit more exposure. Shameless perhaps, but what can it hurt? This viz from David McCandless certainly deserves a makeover.
- The viz is eye-catching and definitely draws you in. There’s something to say for that.
- The interactivity is fantastic.
- Good filtering, colouring and sizing options
- The bubbles move all around for no apparent reason.
- There’s way too much overlapping, making it hard to identify any insights.
- Whether something is interesting is extremely subjective. I wouldn’t make these same choices.
- The viz doesn’t fit in a single view, requiring too much scrolling.
- Not all records are included. I guess this was done for artistic purposes as David is known to do, but it distorts the message.
|Click to view interactive version|
September 13, 2016
In this week’s tip, I look back at one of my most popular posts - 7 easy steps to create a combination chart with overlapping bars & a line. The tip hasn’t changed much, however, this time there’s a video.
September 12, 2016
What works well?
- It’s eye-catching and draws you in.
- The method for labelling ensures you only see the largest (as they names won’t fit otherwise).
- The color helps identify the largest companies.
What doesn’t work?
- Ranking is nearly impossible
- Are the depth of color and the size of the bubble for the same metric? The viz doesn’t tell us, so we’re left to guess.
- Is big good or bad?
- There’s no focus or context.
I started by changing it to a bar chart, but found that to be too boring, though effective. Then I saw an example by Shawn Levin which shows looks at the TEU per ship. That adds much more context to the visualisation. Shawn compared Total TEU to TEU per ship.
For me, I thought it was more meaningful to look at TEU per ship for both the total shipments and for the ships each company owns. This led me to the slope graph you see below which tells a much more meaningful story.
September 6, 2016
September 4, 2016
This week’s Makeover Monday subject was sent to me by incoming Data Schooler Anna Noble. Nothing like kissing up to the coach before you even start. 😋
The viz in question is from The Slow Journalism Company:
What works well?
- It’s obviously a timeline.
- It’s clearly about Alan Rickman.
What doesn’t work?
- It took me a while to figure out what the being on each side of the timeline meant.
- Horrific colour choices; apparently the colours identify the genre. You can see that in the microscopic font on the lower left.
- Colours with zig zagged lines are always a bad choice
- The pointy things
- The pie chart
- The annotations aren’t near the data they represent.
- You have to use the zoom feature to read anything.
- It makes me dizzy.
For my makeover, I wanted to do something very simple. This data set calls out for something simple and clear, especially after you spend time trying to understand the original. I have no idea who Alan Rickman is as I’ve never read any Harry Potter books nor seen the movies. Yes, I’m a terrible father! I once again used 100% floating objects to create this. I’m really loving the precise control that lets me have.
Click on the image for the interactive version (but really there’s no need as there nothing more to the live version other than a mobile view).
September 2, 2016
This week I challenged The Data Duo to a #VizOff of sorts. I provided them with a data set of 8.5M ozone level readings from stations spread all throughout the U.S. I started looking at this data a few weeks ago because I was thinking about the smog in Atlanta and wondering if it had gotten any better since I left. This led me to the master data set or all cities that are measured.
Once I started exploring the data, I noticed that Southern California consistently had the most cities with high ozone levels. So I filtered the data set down to the 25 worst cities.
This helped me focus on a single story with multiple parts, as seen in the long-form visualisation below. Enjoy!
August 30, 2016
In this week’s tip, I walk you through how to create a two-color Pareto chart, a dynamic title, and customised tooltips based on my recent Makeover Monday about U.S. companies hoarding money offshore.
August 29, 2016
First, I must give credit for finding this week’s Makeover Monday to Jade Le Van. She’s a massive supporter of the work everyone has been doing in this project. Thank you Jade for finding this beauty from CNBC.
There are so many problems with this visualisation. However, the most egregious mistake is that the data is completely wrong. The author took the original data set, which has the total money held offshore by a company and allocated that same amount to every country that each country has an affiliate in. For example, General Electric has $199B stored in 18 offshore subsidiaries spread across seven countries. The author allocated $199B to EACH of those seven countries. That’s simply wrong!
What doesn’t work?
- The data is inaccurate.
- The pie charts are a ridiculous choice, especially when you show every single company in each country.
- The companies aren’t sorted.
- The size of the pies isn’t proportionate across the difference columns. In other words, they aren’t all based on the same range.
- It’s impossible to find a company you might be interested in investigating.
What works well?
- Nothing; the whole visualisation is a complete disaster.
I had a few minutes to explore this data set while on the bus home, so I opened up the data in Vizable. Within about 20 seconds I had two views that were far superior to the original.
Quickly and easily, I have a view of just how much money companies are keeping offshore and who they are in a nice, simple ranked list. Great! I already have something much better than the original.
Two more swipes in Vizable and I’m now looking at the companies with the most offshore subsidiaries.
At this point, I felt I basically had all I needed to tell the story in Tableau. I quickly reproduced the two charts from Vizable, then added a Pareto chart for more context. Lastly, I added some headers above each chart to tell a synchronous story.
August 24, 2016
After publishing my viz earlier today that used Google Sheets, Zen Master Chris Love posted this question on our collaboration tool:
So I told him I’d create a video that shows three things:
- How to scrape data from a web page into Google Sheets
- How to import that data into Tableau with the Google Sheets connector
- Ensuring it refreshes when you publish the viz to Tableau Public
UPDATE: Zen Master Jeffrey Shaffer sent me a link to this post on his blog. It’s important to note that the IMPORTHTML function does not seem to auto-refresh. You can force an auto-refresh in your Google Sheet by making the first cell an IF statement like this following -
Then you need to update your spreadsheet settings. Click "File" -> "Spreadsheet setting" and set the "recalculate" to "On change and every hour". This will keep the data refreshed.
It’s election time, so time for an election viz. You will notice this is very similar to the RealClearPolitics version the difference being that I am calculating the 2-week average of all polls in their data set.
This little project also provided me a chance to try out the new Google Sheets connector in Tableau 10 and allow the extract to refresh on Tableau Public. In addition, I learned how to scrape a table from the web in a Google Sheet via this blog post, which should (if I did it right) update automatically.
This was also another chance for me to test out the Device Designer that came with Tableau 10. Enjoy!
August 23, 2016
August 22, 2016
This week for Makeover Monday we are tackling the malaria epidemic. The fact that countries still have to worry about malaria despite the prevention measures available is quite sad. Fortunately, the Tableau Foundation is helping and you can help too. Please visit visualizenomalaria.org to help.
Let’s look at the original visualisation on the World Health Organization website.
What works well?
- Really nice interactivity with both hover and click actions
- You can make any are full screen
- Consistent color palette
- Easy to understand
What doesn’t work well?
- Map is way too wide
- List of countries doesn’t aid in understanding
- Time series and bar chart don’t adjust for the data that is filtered
- Timeline is missing several years, even though the data exists
- Time series doesn’t display anything until you click on a country
I wanted my visualisation to fix the issues listed above, but also to be more focused on Africa. I also wanted it to serve as a call to action. I start with a summary and background information, dig a bit into some insights I found, and wrap it up with a way people can help.
August 17, 2016
This Data School Gym challenge is nothing more than a remake of an existing chart. I was reading Andy Kirk’s great series “The Little of Visualisation Design” and he showcased a chart from The Economist. From Andy’s blog:
"Typically, charts like this would have categorical value labels right-aligned to the left of the vertical axis. However, in this case, the labels are positioned with immediate proximity just to the right of the highest value - which is the value used to order the categories vertically. This approach aids readability, making it just that little bit more efficient to perceive the values and their associated categories."
According to The Economist, this chart shows:
"In every state where exit polling from this year’s primaries is comparable with the previous competitive cycle (2012 for the Republicans and 2008 for the Democrats), more voters have described themselves as “conservative” on the Republican side and “liberal” on the Democratic one."
I thought this would be a fun chart to try to rebuild in Tableau. I recreated the data manually, which you can download here. Note that the data probably isn’t 100% accurate to the original chart; I did the best I could and that’s not the point anyway. The point is to practice, practice, practice.
- This is three charts.
- I used 100% floating objects.
- The vertical and horizontal lines were added manually.
- Each event has its own sort: The top is sorted by Conservatives, the second by Liberals and the third by Moderates.
- The shading must span from the smallest to largest value for each event and state.
Give it a shot. I didn’t think this one was too terribly difficult. The toughest parts for me were getting the layout just right.
August 16, 2016
August 15, 2016
Several of the ladies that participate in Makeover Monday have been asking for a while now to look at a data set and viz that related to the original #MakeoverMonday hashtag. That is, something to do with beauty, make-up or hair.
This week, we look at this infographic from Raconteur Media, a publishing house and content marketing agency. Raconteur has a whole section devoted to their infographics if you’re looking to do more makeovers on your own and need interesting data sets, or if you’re looking for some creative inspiration.
In particular, the focus on this Makeover Monday is on the radial chart in center of the graphic. This chart attemps to show the year-over-year change in the UK market for various makeup products.
What works well?
- Each of the sections is sorted from largest to smallest
- Each bar has a clear label for the 2014 value and the change vs. 2013
- Design catches and retains your attention
- Simple summary in the middle
- Really crisp font that is easy to read
- Good color choices that contrast well
- Consistent decimal formatting
What doesn’t work well?
- The categories are not sorted, so it takes a lot of work to see which category is the largest.
- Comparing products across categories is basically impossible.
- Originally, I thought the white T-line extended out to the value for 2014, but it doesn’t mean anything. It’s simply to fit the text.
- This led me to think that the bars themselves were 2013 values, but they aren’t. So I’m not totally sure what the white line and bars represent.
- Some of the bars are cut off with squiggly lines to show they go farther than the viz shows. This can be misleading.
- At a glance, it’s very hard to tell which products are growing and which have declined.
For my version, I decided to go 100% floating in Tableau for the first time ever. I now understand why people design in Tableau this way. I can make my dashboard look EXACTLY the way I want and it’ll render exactly the same way on Public. Previously I would try to float only parts of the dashboard and they would shift a few pixels in Public. Not so with 100% floating. So, what I’ve learned is design Tableau dashboards 100% tiled or 100% floating, but don’t mix the two. This is the beauty (pardon the pun) of Makeover Monday; it gives me a chance to experiment and learn.
I deliberately chose colors that I thought looked more “make-upy”. I used an orange-to-purple diverging color palette from ColorBrewer and added it to my Tableau preferences file. Lastly, I also incorporated a phone version using Tableau 10’s new Device Designer.
My goals for this dashboard were simple:
- Make a dashboard that makes understanding and compare within and across categories easier
- Create a computer and phone version
- Use colors that represent the topic, but also clearly show products that are increasing or decreasing
Another fun week of Makeover Monday complete and, once again, I learned a TON! Enjoy!
August 12, 2016
Today at the Data School, Amanda Patist was giving an Alteryx demo and she used worldwide population data. That got me thinking about population pyramids; I’ve always wanted to build one. When I create this, it required a few tricks to get it just right. So I thought I’d post it as a Data School Gym challenge.
The small line chart show the % females and % males. The big chart shows the population. Post a link with your solution before you download mine.
Ignore the gray lines that are going across the viz. That’s a bug in Tableau 10.
August 10, 2016
A fun Data School Gym challenge for you today. Using this data source of human height since 1896, create this visualisation:
- Each country should show only 1896 and 1996 and they should be connected
- Label the midpoint with the country name
- Use an orange to blue diverging color palette based on the Avg Height
- Allow the user to filter by sex (no All option)
- Create a parameter to allow the user to pick a country; it should also include an (All) option
- Use the parameter to sort the visualisation; (1) If (All) is chosen then sort from largest to smallest based on the 1996 value. (2) If a specific country is chosen, that should be displayed at the top and the rest should be sorted from largest to smallest.
When the user picks Bermuda, for example, the visualisation should look like this:
Here’s the interactive version. Post a comment with a link to your solution. Good luck!
August 9, 2016
In this week’s tip, I walk you through how I’ve learned to use Tableau 10’s Device Designer feature, which makes it so much easier to create device specific designs.
Note: I ramble a bit at some points in this video as I learn some things along the way and I also hit some wifi issues, so I apologize in advance. Hopefully this helps you see that no one is perfect and we’re all on this journey of learning Tableau together.
August 8, 2016
With the Olympics starting this weekend, I thought we’d take a look at the most classic way that people display Olympic medal counts, as stacked bars. Being an American, I pretty much have only known NBC as the host of the Olympics, so when I went to their website and looked for historical medal counts, I was mortified. This viz is just about as bad as it can get.
What works well?
- The countries are ordered from most medals to least.
- There’s cute little actions when you click on the medals.
- They used appropriate colors for each medal type.
Seriously, that’s all I see that’s any good. This is an incredibly poorly done graphic.
What doesn’t work well?
- There’s no title.
- There aren’t any tooltips, so I have no idea how big each bar is; I’m forced to guess.
- I can only see seven countries at a time, and I can’t even see the name of the seventh country. I mean, who would ever want to compare only the 15th-21st ranked countries?
- When I click on the scroll button, it scrolls by an increment of 2. Why?
- Comparisons are nearly impossible with a stacked bar except for the total medal count and bronze.
Here are some of the changes I made:
- I separated out each medal into a dot plot and chose to show only the top 25.
- I included a summary next to each country to provide the exact medals counts.
- I included a mobile view, but in this view I remove this summary for a better visual look.
- I included informative tooltips.
- I included a title so you know what the chart is about.
- I included filters so the user can decide which Olympic games to include.
- The "sort by" option allows the user to pick the medal count to sort by making comparisons easier.