https://midtermtyfolks.folkst.sites.carleton.edu/blog/
This is the link to my blog post for my midterm using R with on one of the X-Men data sets.
3 thoughts on “Ty Folks’ Midterm”
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I like how you used R for your data cleaning and visualization, while it has a learning curve it’s a very powerful tool for data cleaning and visualizations. The visualization is very clean as well, I can understand it without knowing the context of your project. I completely agree that the fields of data science and digital humanities can be intertwined to benefit both fields; nice job!
Your analysis is very detailed and on point, showing the intuitiveness that’s suitable for a humanities project. Something that I think you can improve on is the format of your labels. Some of them has the country at the end, some are in the middle and one of them “Yellowstone Wyoming” is even lacking a comma where the other locations of similar format have one. This would greatly improve the understanding of people who are not very proficient in geography reading your graph.
I think your process method was pretty unique, I didn’t even think about using R at first. However, I do see one potential caveat in your approach, and that is that there are a lot of labels that represent the same location but have different kinds of spellings. I also worked on this same dataset, and after running the data through a re-cluster algorithm using Open Refine, there were a lot of labels that had question marks, commas, asterisks, and more, so I’m curious to know if there is a method in R that you used to account for this?