Comment on "Use OpenHeatMap to introduce the world to your data" from April 5th

Once again Mr. Shaw has found a simple yet useful program on the internet. OpenHeatMap is free software that can be used to express your data in a visually striking way. If you have data that is geographically dependent, such as unemployment or election results, this is a great program. It will display your data on an extremely detailed world map that is capable of being zoomed. This program may even be used on data that is not necessarily geographically dependent, but may show interesting patterns in the data, such as where it comes from.

I decided to gather the top 100 football recruits based on Rivals.com rankings for the past three years. I wanted to create a map that would show where these recruits came from. While creating this visualization I discovered a few helpful tricks and tools. First I discovered that besides location, this program can use size and color of the markers to display secondary information. I was able to display the players overall rank as dot size in the visualization. The default set the higher ranked players (ie 95^th or 99^th) as the largest dots. In reality, the lower ranked players (ie 3^rd or 5^th) are the best players in the country. I wanted to map to express this idea. I found that you can reverse the ordering in the chart editing section so that the rank goes from 100 to 1 instead of 1 to 100. This fixed the problem. Another great feature is the ability of the program to show changes over time. I have included a map of each year below.

 

There were a few key insights that I found from my visualization. Most of the recruits are found in the southeast, west coast, and mid-Atlantic regions of the United States. The best recruits were spread out pretty evenly throughout these three main regions. The year did not have a significant impact on the geographical distribution of the recruits.  

There are a couple more useful features in this program that I have not mentioned. One nice addition is that you can mouse over each of the points in the map and all the information on that data point will be displayed. Another is that clicking the play button on the lower left corner of the display will run your data chronologically. At first the data was displayed too quickly, but I was able to adjust the speed and slow it down. After this, the visualization ran perfectly.

With more time, more years of data can be gathered and a better understanding of the data can be had. If there was a dynamic shift in location of recruits, this could mean a shift in the general population. Being able to see this shift in a visualization created with a program such as this would be very powerful.