Experimenting with Tableau, I created and uploaded three different data visualization using two different data sets. The first data visualization, presented above, is a simple representation of the US population since 1790. It draws on data from the US Census Bureau, which has been performing the national census since 1902. Using Tableau Public I was able to create an easy-to-understand graph which provides an ample visual representation of the US population. The only data that can’t be extracted is data that isn’t the national population (no surprise there).
The second data set was the Death Rates by State. It is a large and intricate dataset covering the major causes of death by state such as suicide, accidents, homicide, flu, AIDS, and more. It contains a lot of data drawn from Statistical Abstract of the United States but, without the actual abstract from which it was drawn from, there is no way to know what any of the numbers actually mean. There is no “per 100,000 population” or “per year” or any sort of information like that included within the basic data set so it’s difficult to determine what is actually being represented. Even more confusing is the AIDS and Homicide rates which are usually 1 or 2 digit numbers and I can only assume it’s a ratio of some sort but without looking it up further I have no way to know. So, to sum it up: Tableau good, dataset bad.
Just for fun and out of curiosity, I decided to make a poorly represented data set, purposefully disregarding the recommendations given by Nathan Yau. I represented the US population as a number of increasingly large circles which represent the decade the census information was drawn from. While ultimately a poor representation, in retrospect, I could have made it far better by arranging each bubble linearly. While not nearly as useful as the simple line graph, it would have still provided a decent visual representation of the data. As it stands, though, it’s pretty inadequate at giving users an idea of the differences and changes in size of the US population since the 1790’s.