Maybe some love or Valentine's Day dataset for #makeovermonday week 7? We love data. It's our day too. @TriMyData @VizWizBI

— Staticum (@staticum) February 11, 2017

• Color choices that match the theme
• Simple title that tells me what I'm about to see
• Proper sourcing
• Nice description that include a question that explains what the viz is about
• Donut chart works well here as it's only 2 slices
• Clear labeling

• 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

For week 44, I tracked all of the things that distracted me. The data I collected included:

1. When did I get distracted?
   
2. What was I doing at the time?
   
3. What distracted me?
4. How long was I distracted?

When doing the analysis in Tableau, I started doing what I always do by building lots of different views. I started with how many, but there weren’t any days that were massive outliers. When looking at how long I was distracted, there was a big outlier on Wednesday. That was because we had Caroline Beavon teaching in amazing data visualisation class at the Data School and she introduced us to an infographics design tool called Piktochart. This is when I distracted myself. It was fun to play with and got me thinking more about design.

I built several more views looking at the different dimensions against the different measures. Nothing particularly exciting…until I built a bubble chart in which I colored the bubbles by whether or not social media was the distraction.

I generally have a disdain for bubble charts, but this particular view helped me easily see how often social media is a distraction. Does this mean I’m on my phone too much? Probably!

The view above simply looks at how often, meanwhile looking at the bubble chart by how long the distractions lasted makes social media distractions look not so awful.

Lastly, I needed to find a view that would allow me to incorporate all of the dimensions along with the length of each distraction into a single view. I came up with this viz:

Here are some of the design decisions I made:

• Show the day of the week left to right
  
• Inside each day, show the distractions in order from first to last going left to right
• To show what I was doing and what distracted me, I wanted to go with the idea of going from something to something else. I ended up with filled circles inside open circles. The open circle is what I was doing; the filled circle is what distracted me.
• Create groups of activities and distractions so that there aren’t too many colors

Lastly, I liked what Stefani did for her week 44 with the lines, so I tried to do something similar with my postcard version while maintaining the view I created in Tableau.

Quick makeover this week (we have a Segway tour of Boston at #Inspire15 in 30 minutes). I saw this graphic on the LA Times about the amount of water it takes to produce a single ounce of food.

It’s cute and it’s interactive, but it’s not very good for making comparisons or ranking. Bubble plots are notoriously difficult this way. For example, tell me quickly which food uses the 3rd most water? Tough to tell, right? I also don’t understand why they grouped fruits and vegetables together.

I manually recreated the data in Excel, which you can download here. Hopefully I recorded everything correctly; if not, please let me know. I then quickly built a chart in Tableau. I’ve addressed the issues that bubbles present, ranking and comparison, by using a bar chart instead.

Going back to the previous question, using my viz, which food uses the 3rd most water? Simple right? How about the 10th most vegetable? That’s simple too; all you need to do is click the color on the right.

I was watching a video from Simon Rogers the other day about data journalism and how he got started.  During his TEDx talk he showed this bubble chart that he created on government spending in the UK.

This reminded me that Tableau 8, the Kraken, now has the ability to create bubble charts.  They’re not quite as sophisticated as what Simon created, they’re more like what you can build with ManyEyes, yet, like most of Tableau’s features, they’re unbelievably simple to build.

I downloaded data about US federal government spending in the 2013 budget from Wikipedia, connected to it with Tableau and within 3 clicks I had my bubble chart.

Clicks 1 & 2 – Select Agency and Total (which is total spending)

Click 3 – Click the packed bubbles option from Show Me

And here’s what you get:

This is pretty boring, so I placed Total on the color shelf and changed the color palette to red-blue diverging and reversed them.

That’s about six clicks and I have something pretty interesting.  But that’s not enough for me.  I wanted some interactivity.  A few minutes later and this is what I created:

Is it perfect?  No.  Give it a whirl.

• Play around with the selectors.  Notice how the sheet colors change from a measure to a dimension.  Download the workbook and see if you can figure out how I did it. 
• Click on a department in the table to highlight it’s bubble. 
• Notice how the table sorts based on the spending type you pick.  This makes finding the top few bubbles much easier.

These new bubble charts are going to be pretty useful, though I can totally see them get wildly misused.

On Tuesday, October 16th, one of my favorite novelists, Nelson Demille, published The Panther.  I’ve read many of Demille’s books, including two of my favorites, Up Country and Wild Fire.  I read Up Country after I was in Vietnam back in 2004 and Wild Fire just a few weeks ago.  Wild Fire was particularly interesting given the current political climate in the United States and the state of hostility by some towards the Middle East.

Demille is currently on a book tour and he’s sticking to the NE part of the US, unfortunately.  I created this viz on the train home last night so that you could go see him in person, buy his book (by clicking on the book cover), and send me a signed copy.

Thanks in advance!

Question: The bubbles are a simple calculated field that compares the date of the event to the current date (if today() > [Date] THEN 'Yes' else 'No' end), however when published, Tableau does not evaluate the expression and the bubble colors are not updating automatically.  Has anyone seen this?

The chart below comes from a recently released study by Nielsen.  With some simple fixes, this data can communicate much more effectively.

I find this chart hard to read and interpret because:

1. The data is not aligned vertically, making comparisons across categories for the same country difficult.  For example, your eyes are constantly pinging left to right to left trying to compare the UK values.  It kind of makes me feel like I’m in a tennis match.
2. The bubbles are not sized according to their percentage, making comparing bubble sizes meaningless and inaccurate.  You can’t tell me that the orange Italy bubble for Downloaded Music is 1/3 the size of the US bubble.
3. There doesn’t seem to be any logic to the order of the categories.  At first I thought they were sized by the US percentages, but that’s not it.  Maybe they’re ordered by the total?  Nope.  I have no idea!

There are two better alternatives for presenting this data.  First, if you like the bubbles, then a viz like this works. 

With this viz, it’s so much easier to compare values both across and down.  It’s easier to compare bubble sizes, you don’t have to lookup the colors since they’re organized in columns, and the bubble sizes are relative to each other.  Look at Downloaded Music in Italy now: 20% now looks like it’s a bit less than 1/3 the size of the US bubble (62%).

Note that I would normally have ordered the categories alphabetically, but I sorted them in the same order as the Nielsen viz so that you could compare the mine and their’s more easily.

A second alternative would be a simple bar chart like this.

This chart also addresses the comparison problems.  The gridlines make it especially easy to compare categories within the same country, though your eyes do have to skip over three other bars before getting to the next one.

Bar lengths are much, much easier to compare than bubble sizes, but the bar chart feels a bit more cluttered to me than the bubble chart.  In this situation, I would use the bubble chart I created. 

This goes to show that there’s more than one way to skin a cat.

Using Tableau is a never-ending journey of learning and today was no exception.  It began with this chart from the Chart of the Day:

Overall, this chart is well executed, except I would have sorted the players in descending order.  But I wanted to take it one step farther, so I downloaded the data from pro-football-reference.com and got to work in Tableau.  I wanted to be able to compare:

• Not only the combined kick returns, but also the top punt returners and kickoff returners separately.  I wanted to know which players were the best in each category. 
• Players that played for one team versus more than one team
• A player’s kick return ability compare to his punt return ability

Finally, I wanted to be able to filter each chart by the Top X Players for that chart.  This is where parameters come in handy.

I started this post by saying I learned a few things.  I learned to:

• Make the user experience easier by creating a list of instructions like Steve Wexler at DataRevelations.com always does. Hover over the NFL logo to see the instructions for this viz.
• Filter by a Top X parameter when there’s more than one item on the color shelf (like on the Total TDs chart).  Check out this discussion on the Tableau forum for an explanation (thanks to Joe Mako for the link and help making it work with a scatter plot).

To answer the question in the title of the viz, Devon Hester is very dangerous…a clear outlier, he’s a player that is “numerically distant” from the rest of the players.

Nielsen is at it again.  Just when I thought they were making strides in the right direction, they bring me back to reality.  As with most Nielsen articles, this one is well written with lots of facts that are explained in an easy to understand manner (kudos to them for writing well).  There’s even a nice bar chart that ranks survey responses.  But then, they throw this junk in there:

Is it just me, or is this screaming out for another bar chart?  Maybe they’re afraid they’ll bore their audience with another bar chart, so they throw in an unnecessary ranked bubble chart to gain your attention.  Are they THAT desperate?  Why not represent it like the bar chart below?

Or better yet, show the data itself.  It tells the same story, but only simpler and you don’t have to try to infer any additional meaning from the size of the bubbles.

My faith and resolve are not shaken though.   Eventually they’ll get annoyed by my emails and write me back.