19th century African American war pensions in Albany, NY

My initial goal entering this project with this data set was to create a visual that would show how pensions progressed over the century (1806-1883). While I was unable to accomplish this for my initial “rough draft,” I do believe it is possible. I encountered issues immediately as the dates are not in chronological order within the spreadsheet. Instead, the data had been entered in alphabetical order based on the recipient’s name. While this is the correct way to do this for official documentation, it poses an issue for someone like me that hopes to find trends in the data. Another problem that was readily apparent was the lack of explanation describing the wound or reason for receiving a pension. While most of the descriptions are easy to interpret, some are difficult to discern and makes analysis a bit more troublesome.

 

For my first visualization, I decided to keep things simple. On the left hand side you will find the various wounds and reasons for receiving a pension. The columns represent the average amount that was paid out on a monthly basis. I also sorted the data from the highest monthly payment through the lowest. By looking at the data this way we can see that a soldier who, as a result of either a combat injury or other military related accident, came to become fully blind. He received, on average, $72. This of course fluctuates when looking at each individual case but what I am interested in is the average. To put this into perspective, using an inflation calculator, we can see that in 1845 (using this as a mid-point), $72 would have the same buying power today as $1849.28. It is important to take this with a grain of salt as statistics are not readily available pre-1913.

 

By looking at the various dates of allowance, we can conclude that most of the injuries sustained were a direct result of the Civil War (1861-1865). The many different gunshot wounds received shows that not only were African-Americans involved in the war in some capacity, but that they were actively involved in harsh fighting on the front lines. The people listed in this census are only ones that live in the Albany, NY region and who actually submitted a formal request for a government pension for their injuries. 921 names are represented on this census. Imagine the number of African Americans that did not sustain injuries and are from other locations scattered across the many states. Just by thinking of this, we can conclude that not only did African Americans fight in the war, but they made a large contribution to it as well.

 

As a final note, in my final project I hope to have my copy of the census worked out to be organized in chronological order rather than alphabetical. I believe this will help paint an interesting picture that will help show how one injury may receive less, or more, compensation than that of one reported decades later.

Various types of Visualization methods

Remember the good ‘ole days of sitting in your third grade classroom and drawing bar graphs and pie chart? The information that we were recording were fun things such as the number of boys versus girls in the class or the various hair colors. Since then, the amount of information we have learned to work with and analyze has expanded exponentially. We literally have a world of information available with a simple Google search. But with all this wild and crazy information that we are so fortunate to look at, a problem arises when there is simply too much. Who wants to sift through pages and pages of surveys to find relationships when you could simply graph them. Maybe a pie chart or a bar graph will be sufficient enough. What if I was to tell you that there are hundreds and thousands of various graphing models available, each specializing in certain fields?

First thing’s first, why do we like to graph information? Research has shown that humans are more keen to identify patterns and relationships visually through color, shape and style, to name a few. This is why graphs play such an important function of data analysis. Unfortunately, not all graphing techniques are ideal for every field of study. While a pie chart and bar graph work great for finding relationships between the population of Albany, a stem-and-leaf plot might not be a good choice. Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky of Stanford University conveniently compiled a list of the more interesting and complex graphing styles. I won’t explore each graph but will instead discuss the few we are all familiar with and a couple of the wild ones.

let us first look at the stock market! We can all recognize that iconic rising and plunging chart that displays the growth and decline of various stocks. This particular chart allows the user to scroll through time and watch how various stocks saw immense growth or loss periods. For example we can see that Apple, in a single month, from June to July in 2006 had a loss factor of over one hundred percent. Protovis is one such program that allows a user to create an interactive, “live”, graph. Unfortunately, it is no longer in development as of 2011, shortly after this article was written.

Out of all the various types of graphs and charts, maps are probably what most of us feel the most comfortable with. If you have ever watched your local six o’clock news you probably have seen Choropleth Maps. These are useful to display the various temperatures across a country using light and dark colors. In this particular map we can look at the obesity rates in the United States. Flow Maps are useful in visualizing a number of important statistics on a map. In this case we are looking at Napoleon’s march on Moscow in 1812. Not only can a large visual be created to overlap the map to depict the route used to travel, but also troop sizes, temperatures, latitudes and longitudes and recurring lesson of never to invade Russia during the winter.

I would like to pose the following questions for us to consider:

1.) Which type of visualization represented in this article, or others not mentioned, do you feel is ideal for historians?

2.) How can we effectively use any of the visualizations mentioned to expand our Walking Tour projects?

3.) As a follow-up question to the previous one: Thinking of our intended audience, how would one particular graph be clearer than another?