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A Graphical Look at the 2016 Kentucky Derby

The 142nd annual Run for the Roses, better known as the Kentucky Derby, took place this past weekend in Louisville, Kentucky. The race for 3-year-old Thoroughbred horses began in 1875 and takes place annually at Churchill Downs. Each year horses compete in 35 preliminary races for 1 of 20 coveted spots in the Derby.

churchill-downs-location.png

Location of the Kentucky Derby, base map created in Surfer 13.

This year the win went to Nyquist, who is currently undefeated. Nyquist finished with an impressive time of 2:01.31, which is the 14th fastest finish of all time! The graph below shows the top 10 finishers of the Derby and the year of the race next to each bar. I found it interesting that there is no clear correlation of year and time. I was expecting to see a trend of faster times over the years as breeding and training have changed. But, this expectation did not fit the reality of the finish times. The race is commonly called “the most exciting two minutes in sports” and only 2 horses have ever finished in less than 2 minutes, and only 1 was in the last 20 years!

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Ten fastest Derby finishes, created in Grapher 12.

Many great traditions come along with the Kentucky Derby, including eating a stew called burgoo and wearing lavish clothing and hats. The greatest tradition of all, however, may be the imbibing of the mint julep. The mint julep is a simple cocktail consisting of bourbon (native to Kentucky), mint, sugar, water, and crushed ice. For the Derby, it is traditionally served in a silver cup, and the water, sugar, and bourbon are combined in a ready-to-pour cocktail mix from Old Forester. Each year, Churchill Downs serves nearly 120,000 mint juleps to its attendees, and 2016 had the second highest number of attendees at 167,227 people. Just what does it take to serve up so many drinks? See the graph below.

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Ingredients needed for mint juleps at Churchill Downs, step graph created in Grapher 12.

As a Southerner, the Run for the Roses is a big part of ringing in the spring! You can bet I enjoyed a mint julep while wearing my largest, most obnoxious hat this weekend! I hope you’ve also enjoyed this graphical look at the 2016 Kentucky Derby. We’ll have to wait another month to see if Nyquist is able to remain undefeated at Belmont and Preakness to take the Triple Crown!

If you aren’t a horse racing enthusiast, you can still have fun around race time. As you may know, race horses have some interesting names. Nyquist, Exaggerator, and Gun Runner were the top three horses at the Kentucky Derby this year. Continue the Derby spirit, and find out what your derby horse name is here, courtesy of The Des Moines Register! (Mine was Buttermilk Blur!)

 

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21 December 2016
Grapher
MapViewer

Now that Christmas is just days away, I think it’s safe to say that we’ve fully entered into peak holiday travel time. If you’re travelling this holiday season, I don’t have any good advice for how to beat the security lines or what to do if your luggage is lost, but if you’re interested in some fun graphics based on factual data, look no further! I found a gold-mine of data at the U.S. Department of Transportation’s Bureau of Transportation Statistics, and plotted up a few graphs and maps from data that I found interesting.

 

Feeling a money crunch this holiday season? Here’s a comparison of domestic average airfare for the past 21 years.

And here’s how much the airlines are actually pocketing.

Feeling blue that your flight is late? Check out this plot of just how many flights were late, canceled or diverted versus those that were on time for the last 21 years.

 

Notice an increase in the bustle around you over your last flight? Take a look at how many travelers do so during the holidays versus during the rest of the year.

 

And where are all of those people going? Things get a bit busy if we look at all of the data, but here are the top 10 destinations of Coloradans for the 2015 year (with numbers of travelers for each state color-coded in a blue scale).

 

I hope you’ve enjoyed perusing these as much as I’ve enjoyed making them. If you are traveling this holiday season, stay safe, and to all, happy holidays!

19 July 2016
Surfer

As an avid outdoorsman in Colorado, I am always making sure I know what the current local weather pattern is going to do. Whether I’m going into Rocky Mountain National Park for a day hike, attending an outdoor show at Red Rocks amphitheater, or riding in the weekly Denver Cruiser ride, I have learned over the past 17 years that the weather in my colorful state is always unpredictable! I know I need to consult the forecast to see if I need to wear a rain jacket, pack a sweatshirt, cover myself with sunscreen, or a combination of all 3 before I embark on my journey. However, the past weeks and even few months seem to change this mode of thinking. The weather has been more predictable than past years; it’s going to be hot and dry.

There has been a lot of buzz in the media lately about El Niño and the global heatwave this summer. This piqued my interest; I was curious if Colorado was experiencing the same trend locally compared to previous years’ temperatures. My mapping professional side couldn’t balk at the opportunity to create some maps that compare the summer temperatures over past years in hopes to find some obvious temperature-increasing trends.

Mapping Approach:

For this mapping project, I have decided to use Surfer to create contour maps of Colorado’s monthly average temperate in July over the past 7 years to determine if we are seeing the same heatwave trend locally as what is being reported globally. I was able to access data from the NOAA Climate Prediction Center for the maximum daily temperature for July from 2010 through 2016. I downloaded the daily data in TIF grid format and used Surfer’s Grid | Math functionality to combine all of the data into a single, monthly average for each year. The data was also converted from Fahrenheit to Celsius for easier interpretation. To do so I used these steps:

  1. After the data was downloaded, I opened Surfer 13 and clicked Grid | Math.
  2. In the Grid Math dialog, I clicked the Add Grids button.
  3. In the Open Grids dialog, I selected all of the daily temp TIFs and clicked Open.
  4. I used the following equation for the function, named the resulting grid, and clicked OK: (((A+B+C+D+E+F+G+H+I+J+K+L+M+N+O+P+Q+R+S+T+U+V+W+X+Y+Z+AA+AB)/28) * 1.8 ) + 32
  5. I repeated these steps to create average maximum temperature grids for the rest of the years of data I downloaded.

Results:

Now all of the daily data has been averaged over the month of July for their respective years, I can create contour maps in Surfer for comparison. I created a separate contour map for each year, using the same contour interval and color map so that the maps could be easily compared to one another. The maps were scaled the same and posted next to each other to see if Colorado is on the same track as the rest of the globe. The resulting contour maps are below, showing that the monthly average temperature from year-to-year varies, but it is difficult to isolate a spatial trend between the years. I definitely cannot tell that this July is hotter than any other of the years I downloaded data for.

Surfer 2D & 3D Mapping: contour map depicting average maximum temperaturesA comparison of Contour Maps from Surfer that depict the average maximum temperatures in Colorado for July 2010 - 2016.

Mapping Approach, Part 2:

Because I was not able to see a trend across Colorado for the past 7 years from the contour maps, I decided to take a look at the data from another perspective. I wanted to see if there were any spatial temperature trends by differencing the average maximum temperature for this July to the average maximum temperature for the previous 6 years. This can easily be done by, again, using Surfer’s Grid Math feature. The monthly average temperature data can be combined into a single grid that represents the average temperature for July over the previous 6 years. The difference between the July 2016 temperature data and the 6-year average temperature data can be found by subtracting the two grids from one another. This gives me a grid of the temperature departures in July 2016 from the average over the last 6 years that can be visualized using a contour map.

To create the average monthly temperature grids for the previous 6 years:

  1. I clicked Grid | Math.
  2. In the Grid Math dialog, I clicked the Add Grids button.
  3. In Open Grid dialog, I navigated to all of the monthly temp grids and clicked Open.
  4. In the Grid Math dialog, I used (A + B + C + D + E + F) / 6 for the function, named the Output Grid File, and click OK.

To difference the monthly average grid and the July 2016 temperature grid:

  1. I clicked Grid | Math.
  2. In the Grid Math dialog, I clicked the Add Grids button.
  3. In the Open Grids dialog, I navigated to the average July grid and clicked Open.
  4. I clicked the Add Grids button again.
  5. In the Open Grids dialog, I navigate to the 6-year average grid and clicked Open.
  6. I clicked Grid | Math.
  7. In the Function box I entered A- B, I named the Output Grid File, and clicked OK.

Results, Part 2:

A contour map was generated in Surfer that shows the temperature departures for this July compared to the previous 6-year average; shown below. This map shows that the temperature in July has remained relatively unchanged for most of the central mountain region (central portion of the map) and the only notable temperature increases are in the southwest portion and on the eastern planes of Colorado.

Surfer 2D & 3D mapping software: contour map showing temperature differencesA contour map showing the degree departure in July 2016 from a 6-year average of maximum temperatures in July in Colorado.

Wrap-up:

As you can see, utilizing the differencing technique from Surfer’s Grid Math feature proved to be a better analysis approach for determining what areas in Colorado are seeing the same heatwave trend that is being reported across the US and globally than comparing contour maps. Surfer is developed by Golden Software, please feel free to take a look at the free demo version and place your orders at http://shop.goldensoftware.com.

07 July 2016
Real Life Applications

The United Kingdom (UK) voted on the United Kingdom European Union membership referendum, commonly referred to as the Brexit vote, on June 23, 2016. This referendum was to gauge citizen support for whether or not to remain a member of the European Union (EU), an economic and political partnership involving 28 European countries. Overall, the UK voted 51.9% to leave the EU, with 71.8% turnout. The world reacted when the news was announced on June 24. I've spent the last two weeks reading about this historic vote and what it means for the people of the UK, the EU, and the rest of the globe. It has already had some effects on international economic markets. It remains to be determined how it will affect the future, but I find this to be a fascinating time for trade, politics, economics, and international relations.

The first thing that interested me was the demographic breakdown of the vote. Various exit and other polls were done with information about how different demographics voted. I sifted through the information available at Lord Ashcroft Polls, and noticed some clear correlations between education level and age and how an individual in the poll voted. Older voters, less educated voters, and less employed voters were more likely to vote to leave the EU. I wondered if those in less-than-ideal socioeconomic situations were looking for anything different that may help provide a higher quality of life. Another issue that caught my attention was when voters made their decisions. Nearly 25% of those polled made their decision within the week before casting their votes! Just over 1/3 always knew how they would vote. The remaining ~40% made their minds up in the last 6+ months. To me, this shows some uncertainty about how to vote or perhaps uncertainty about what the effects of the vote would be on the individual and UK.

demographics4.png

Graphs showing the Brexit vote according to age, education level, employment level, and when the vote was decided. All graphs created in Grapher 12.

Another interesting aftershock of the Brexit vote is the economic repercussions. The day that the results of the referendum vote were released, Britain's pound took a nosedive. The pound has seen a few small climb attempts since the announcement, but the value has remained relatively low. I've created two different visualizations of the same data below: a 3D ribbon graph and a temporal map. I used a process similar to one used by Surfer user Richard Koehler to create the temporal map, based on months rather than years as Richard’s maps are. In the 3D ribbon plot, the large drop around June 23 is very noticeable. Other smaller dips are also noticeable, as is the long term drop that has been occurring since December 2015, when the official documents enabling the referendum was announced. In the image map, it's easy to see how changes happened day by day over the entire course of the months since December. It's easy to see the color change that took place from December to January in the image map that correlates with a dip in the 3D ribbon graph, when these key documents were filed.

Changes in the value of the British pound, as compared to the US dollar. 3D ribbon graph created in Grapher 12; temporal image map created in Surfer 13.

Changes in the value of the British pound, as compared to the US dollar. 3D ribbon graph created in Grapher 12; temporal image map created in Surfer 13.

I'm still not sure I fully understand the extents of this referendum's global effects, but I am eager to watch what happens in the world over the next few years as the UK exits the EU. Will the UK vote again to confirm the referendum? Will the UK move forward to actually exit, following Article 50 of the Lisbon Treaty? Will other nations follow the UK in leaving the EU? Will the pound recover? Will Northern Ireland leave the UK and rejoin Ireland? Will Scotland leave the UK? What worldwide economic effects will come? How will trade be affected? These are historic times we live in, and I'm excited to see what happens next! What are your thoughts on the UK's Brexit vote?

Like the graphs and maps you see in this blog? Download the free Grapher 12 and Surfer 13 demos to start creating your visualizations today!

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