The dataset that I chose was Slave Sales from 1775 to 1865. I decided to focus more on the sale of children during that time period. I decided to do so because I want to learn more about what it was like being a child growing up during slavery, or being born into slavery. It is estimated that approximately 1/4 of slaves that crossed the Atlantic into slavery were children. Many were forced to move, unwillingly, from plantation to plantation, never truly having a home after being taken from their mothers at a very young age. When learning about slavery in many classes that I have taken, there has never been an emphasis on the children that were involved. My objective is to use this dataset, as well as research, to put an emphasis on children and their experiences during this time period. I took the dataset and condensed it to what I’m more interested in and found some very interesting facts. The first thing I found was that while many children of different ages came from the same states, each individual age tends to come from a specific county in that state. For example, 8, 9, and 10 year olds in this dataset all originate from the county of Anne Arundel, Louisiana. Meanwhile, most of the 15 year olds on the dataset come specifically from the county of Edgecombe, North Carolina. I’m not sure as to why this is, but am interested in finding out more. I would think that every age would originate from every county.
The second interesting finding was that from the ages of 2 years old to 17 years old the prices vary. I thought that the older that the child was, the more valuable that the child would be, and therefor buyers would pay more money. You would believe that the more work that can be done by the child, the more expensive they would be and have more value. Matter of fact, the children that were valued the most were from the ages of 2 years old to 7 years old. After that, 14 and 15 year olds were valued the highest. At the age of 14 many of the children had picked up useful skills, like being a laborer or fieldworker. With skills that were useful to buyers, the age group of 14yrs old was the highest valued, at an average rate of being sold for $540.23. By the age of 16, the average value of children went back down to $199 based on the dataset. The county of Charlestown, South Carolina doesn’t have any listed prices, so that may add to why the average is so low. The visualization below shows all of the average values of different ages of children from the age of 1 to 17 years of age.
All of this information came from the dataset alone. What’s very sad is that many children are at risk for becoming very ill when they’re made to work in terrible conditions. At first, many people avoided having children slaves because they felt at risk because they didn’t want them to become ill. When the demand for more slaves in the Unites States increased, so the beginning of child slavery. The dramatic increase in the need for children slaves didn’t happen until the late 17th/ early 18th century.
Without being able to see how you did your math to pull out the # of children per age group, I can’t say exactly where the error is, but something’s not right with the math. When I try to duplicate this, I’m finding children ages 1-7 in all states and almost all counties. That said, the idea is a very good one, and I think it will be an easy thing to correct.
So first off, open up a new Tableau project and connect it to the original slave sales csv file off Course Resources. In a new sheet, drag “Age Yrs” into the columns, and once you drop it in there, the Show Me pane will have only the buttons for horizontal bars and histogram highlighted–click histogram. A histogram counts the number of things within a numeric range–in your case, how many people are in the age range 1-2, for example. By default Tableau makes ranges which equally divide the total range (looks like about 6.5 years), but if you want to see year-by-year, look over in the Dimensions list, and at the very top there should be a new dimension “Age Yrs (bin)”–right click and select edit, and tell it you want bin size 1 (one year). Or how ever many years you want grouped together (ie, ages 1-2, 3-4, 5-6 would be bin size 2; ages 1-3, 4-6, 7-9 would be bin size 3, etc).
So now you have the number of people who were sold at each age; if you want just children, drag the Age Yrs measure into the filters pane and select 1-17. To get the number of people per state, drag “State Code” up into the Rows area (same thing for counties).
Right now you have average appraised value as the length of each bar; since it sounds like you’re interested in figuring out both the number of children per state and their average appraised value, I’d suggest using color for the average appraised value so that you can see both the number of children per age per state and their average value.