Blog Post, week 10

For some reason, I cannot get the embedded link to work. Here is a link to the website. If you cannot see it send me an email and I will happily get it to you somehow.


My Expiercne Building the Visualization: I had a good time building this visualization. I thought it was cool using flourish again. My major, data science, has a heavy dose of data visualization so it was cool to incorporate my prior knowledge for this project. Doing data visualization in flourish is a much different experience than in my major. We have to code a visualization (sounds more complicated than it is) in R or Python.

Deciding on a Topic:

When starting this visualization, I really did not know what I wanted to do. All I knew was that I wanted to use Census Data from 1840. After playing around in flourish I decided that I would visualize a male slave’s age based on the state where they were from. I thought this was a good topic because it would show the states that had the most slaves and the age distribution of slaves. 

The choice of Visualization: 

Originally I was going to use the standard line graph but it did not look as good as I hoped, then I switched the plot or a grid of charts, which looked better but not great. I was then scrolling through the types of charts and I clicked on column chart and thought it looked perfect for what I was trying to show. The final graph I decided on was a Column Chart (stacked0 with a grid of charts. The main issue with the line graph was that there would be a line even for a value of 0, and I did not like that, the column chart fixed that.

Reflection on Visualization

I thought the visualization that I created was pretty cool. The first thing that I noticed after the creation was that the state with the most slaves (by far) was South Carolina. This was surprising to me because I thought the state that had the most slaves would have been Georgia or Louisiana. The next thing that I notice, was that sadly, the ages increase to decrease based on age. Meaning that most slaves were aged under 10 to 23.  The last thing that I noticed was that there were not very many slaves aged 55-90. I just assumed that it would be higher. 

One thought on “Blog Post, week 10

  1. Thank you for sharing this fantastic visualization! I really like how you chose to represent and compare several states across different age groups. I agree that the column chart looks the best for this data. I think it clearly conveys distinctions in the data based on age and location– in many ways, this offers a different perspective compared to the data map construction assignment.

    I am also glad to hear that you enjoyed using flourish to construct this visual– it is definitely the faster option compared to R and Python (although those tools have so much to offer!) but that’s a bit outside of the “intro” scope of the course. You should definitely connect with the other scholars who are doing this kind of work in the Digital Humanities community at MSU: there is a emailing list you could join for updates and schedules of cool (now online) events. There is a DH conference in the spring as well!

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