This week's Makeover Monday was about representation of women in national parliaments and governments in the EU. 

As a second take on the Makeover Monday topic this week of what legislators spoke about after the Orlando mass shooting, I thought a better view might be the proportion of representatives who spoke about each topic. Presenting the data this way help provide better context for the overall picture while allowing you to compare both across the parties and within a party.

I think a donut chart works well here because we only have two parts to each donut and the number call out the amount that’s of interest. In addition, this enabled me to design a static visualisation that doesn’t require interactivity. For me, it’s much hard to design static, mobile-friendly visualisations than any other type at the moment.

This week’s Makeover Monday is a bit of a dark topic that gives us a glimmer into the how politicians in the US respond to a tragedy. Yes, this is a single mass shooting, but they occur nearly every day in America and the responses from politicians are now all too standard. The Orlando mass shooting likely got more attention because it happened at a LGBT club. This and other tragedies beg the question: When will America get its act together?

The chart that we’re reviewing this week is by the grapics team at The Washington Post.

What works well?

• It’s neatly organised in a 3x3 grid.
• The semi-circles are all sized relative to each other.
• It’s very easy to understand.
• They used colors that are automatically associated with the two political parties
• Everything is clearly labeled.
• It’s not over-cluttered.

What could be improved?

• The chart implies that there are equal representatives in both parties. However, Republicans have 247 seats while Democrats have 187.
  
• Using semi-circles makes the shapes hard to compare.
  
• It's difficult to compare across the topics.
  
• There should be an easier way to which party talks more about each topic
  

Given these changes I would like to see, I’ve create this version that shows how many representatives talked about each topic in a tornado chart format. I then included a circle with a number inside to show which party talked about the topic more and by how many representatives. Lastly, I added lots of summary details in the tooltips.

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Yes, it’s Sunday, but there are weeks when I simply don’t have the time for Makeover Monday on Monday. This is one of those weeks. For Makeover Monday this week, we are reviewing a visualisation created by the National Conference on State Legislatures. According to the NCSL:

"Approximately 1,809 women serve in the 50 state legislatures at the beginning of the 2016 legislative session. Women make up 24.5 percent of all state legislators nationwide."

Wow! Only 24.5%…that’s sad America. We need to do something about it. Those figures are accompanied by this map that shows the percentage of women in state legislatures in 2016.

This viz is definitely not terrible. There are several things that this map does well:

• Using four distinct bins for the colouring makes it easy to see concentrations like all of the yellow in the middle of the U.S. and all of the green on the west coast and northeast
  
• Making the extra squares for the small states that would be tough to click on
• Nice interactivity on hover
• Good tool tips

But I feel like this is so much more to this story. So when I created the data, I included population rates by state. This way I could look at thedisparity between the female population in each U.S. state and the percentage of women in state legislatures.

What would I do differently?

• Get rid of the filled map; while they included the extra callouts for the small states, it add more to the viz than is needed
  
• There’s no sense of how under-represented women are. Are we supposed to just assume each state is 50% female then do the math in our head? I think that’s too much work for the reader.
• No mobile version
• Not enough distinction in the colours. Why not use a continuous colour scale?
• Need a more impactful title
• Need a better way to make comparisons
• There’s no ranking of the states. How do I identify the best and the worst?

Given these recommendations, I’ve create the viz below. I also made this device responsive, so you will see a different viz depending on whether you’re on a computer, tablet or phone. I did this because I want to learn to design for mobile first, something John Burn-Murdoch has recommended to us when he’s come to chat with us at the Data School.

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 October 26, 2010 the Guardian published the latest Corruption Perceptions Index from Transparency International which is the world's most credible source for measuring corruption.

According to Transparency International:

The 2010 Corruption Perceptions Index shows that nearly three quarters of the 178 countries in the index score below five, on a scale from 10 (highly clean) to 0 (highly corrupt). These results indicate a serious corruption problem.

Download the data here.

To summarize the 2010 results:

• Denmark, New Zealand and Singapore are tied at the top of the list with a score of 9.3, followed closely by Finland and Sweden at 9.2.
• The most corrupt country is Somalia with a score of 1.1. Only slightly less corrupt are Myanmar and Afghanistan, with a score of 1.4, and Iraq at 1.5.

View the map produced by Transparency International here. While their version only contains data for 2010, my version of the map allows you to filter by continent, country or year.

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Immediately obvious to me are that:

• The rankings haven't changed much over the past three years.
• You should avoid nearly all of Africa and Asia.
• Western Europe, particularly the Scandinavian countries, are relatively devoid of corruption.

I suspect that the level of corruption could be related to poverty levels, but would need to prove it with the data.

If you want to see a horribly create bubble chart from which you cannot infer anything, go to Many Eyes.

Have you heard of the Tea Party? Interested to know how many people in your area are members?

The Tableau Public blog focused recently on a map of Tea Party membership created by IREHR. Find the original post here.

Naturally when I see a map like this the first thing I do is zoom into my area. However, the IREHR visualization makes it difficult to do so quickly. The city and state data are already available, so I put it to use.

Notes:

1. The map is slow to load and update. I suspect this is due to number of points the map is drawing.
2. The IREHR viz did not include Alaska, Hawaii and Guam, while it did included lots of members that did not have a location listed. I have filtered out the unknown locations and grouped the rest of the data more logically.

I made the following changes/improvements in my visualization:

• Added filtering by Region, State or City to allow you to quickly zoom into an area of interest
• Removed the size legend and replaced it with a caption on the map
• Add a link to the data source instead of just listing it
• Changed the membership numbers you see when you hover over a point to a whole number
• Changed the Faction filter to a slider instead of a single select option (saves space)
• Washed out the Faction color legend so that it's easier to see overlapping points

Which visualization is easier for you to use? I think it is easier and quicker to find what you need in my viz, but then again, I'm biased.

Jon Bruner from Forbes published a pretty cool interactive map that shows the comings and goings of Americans. The map you see below is from my home county. Given that I meet people from all over the country here, I'm not surprised in the least at the flow of people.

Click on the map and you can interact with it yourself. If you want to do any further research, the outbound data can be found here and the inflow data can be found here.

Before you judge my political views, let me first say that I think ALL politicians are frauds and that few of them represent anyone except the special interest groups that support their campaigns.

I received the following message from Congressman Tom Price on Monday (10/5/09): "Last week we received more bad news in the job market. 263,000 jobs were lost during the month of September and the unemployment rate is now at 9.8%. The verdict is in and the economic policies of President Obama and Democrats in Congress have become a massive failure."

I understand Congressman Price's position, but it bothers me that he has taken the lead of talk show hosts to use scare tactics to spread his message. I would, for once, like to hear his opinion. His entire rant can be found here.

In addition, my friend Dan Murray posted a link to a Wall Street Journal article on his Facebook page that essentially said the "Cash For Clunkers" program failed.

I wanted to see if I could draw any sort of correlation, or at least possibly provide the specific details.

Here is my visualization:

First, to Congressman Price's accusations. The rise in unemployment started around January 2007. Obviously President Obama was not yet in office. So what happened that could have sparked the sudden rise? This is precisely when President Bush announced the surge in troops for the Iraq War during his State of the Union address. I can't say that was the exact cause, but I do find the timing neatly coincidental.

Now, onto the WSJ's claims that Cash for Clunkers failed to help the economy. Yes, there was a huge decline in new car sales in September, but this is not unprecedented if you look at historical sales.

Back in October 2001, the "0% interest" programs were introduced by the Big 3. This program was a HUGE boost to sales (35% over prior month), but it resulted in a decline of 18% in November and 25% over the following two months.

The Big 3 introduced the "Employee Pricing" programs in July 2005. This program was another HUGE "success" (sales increased 15% over prior month and 22% over May), but it resulted in a decline of 18% in August, 20% through September, and 28% through October.

The Cash For Clunkers program (August 2009), resulted in a 4.4M units increase in sales over June or 45%. That increase has never been approached in the last 10 years. The results, however, was a decreased in sales in September of 4.9M units or 35%. If this program follows the behavior of the previous two, we should see a decrease of an additional ~7% over the next 1-2 months at which time sales should stabilize.

I read a story recently about Halliburton and the incredible number of contracts and money they scored from Hurricane Katrina. Oh by the way, George Bush was President, Dick Cheney was VP and Cheney was CEO of Halliburton from 1995-2000.

That led me to finding how Katrina contracts were being awarded by government Department. It's been tough to identify just which contracts were awarded to Halliburton since most of them are to subsidiaries. I'm working to gather all of those. The data was gathered from the Federal Procurement Data System (FPDS).

This is a very simple analysis, well not really much analysis at all, but in this instance, given the amount of information I want to display, I actually think the pie chart works better. Thoughts?