{"id":7,"date":"2023-02-20T03:40:57","date_gmt":"2023-02-20T03:40:57","guid":{"rendered":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/?p=7"},"modified":"2023-02-20T03:40:57","modified_gmt":"2023-02-20T03:40:57","slug":"hacking-the-humanities-midterm","status":"publish","type":"post","link":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/midterm\/hacking-the-humanities-midterm\/","title":{"rendered":"Hacking the Humanities Midterm"},"content":{"rendered":"\n

Introduction:<\/strong><\/p>\n\n\n\n

For my Hacking the Humanities midterm project, I opted to do an analysis of the locations in Chris Claremont’s Uncanny X-Men run. I wanted to determine which locations were used the most during Claremont’s run in order to perhaps understand which locations had the most importance. In order to do this, I used R, which is a coding program designed for statistical analysis, to make a graphic from a data set that contained a list of locations used in each issue of Claremont’s run.<\/p>\n\n\n\n

Processes:<\/strong><\/p>\n\n\n\n

The first step in making this graphic was to manipulate my data set in order to have it fit my need. In R, there are a couple ways to do this and I opted for a pretty easy option. My first step was to load the csv data set into R and then, for ease of future commands, rename the variable I’m interested in (Location).<\/p>\n\n\n\n

\"Commands
The first steps in creating my graphic are editing it to my liking.<\/figcaption><\/figure>\n\n\n\n

I still need to edit my data set as it’s not exactly what I want yet. I needed to obtain a count of each location’s appearances in Claremont’s run. There are two ways to do this in R. One way we can do this is by piping together the group_by and summarize commands to obtain a count. Another way we could do this is by simply piping the data set into the count command which will allow us to get a count of each location. This is a significantly easier route as while summarize is great for all manner of numerical summaries, the count command is the simplest and best command for strictly obtaining counts of a certain variable. The pipe (%>%) is extremely useful when you don’t want to retype many lines of code and are using the same data set.<\/p>\n\n\n\n

\"Count
The count command helped me get a numerical count of each location’s appearances.<\/figcaption><\/figure>\n\n\n\n

The last thing I opted to do was simplify my data set by slicing the 10 locations with the highest number of appearances. There were over 200 locations used in Claremont’s run and creating a graphic using all 200 would’ve been a bit messy and difficult to accomplish. I used the slice_max command to finish my alterations to the data set and now I was ready to create my figure.<\/p>\n\n\n\n

\"Slice_max
The slice command is very important for finding the highest and lowest numbers in a data set.<\/figcaption><\/figure>\n\n\n\n

Creating the graphic after was pretty simple. I created a bar chart using the ggplot package and the geom_col command, which will allow me to show the top 10 highest number of location appearances in Claremont’s X-Men run.<\/p>\n\n\n\n

\"Final
A bar chart was the best way to visualize my data.<\/figcaption><\/figure>\n\n\n\n

Presentation<\/strong>:<\/p>\n\n\n\n

I wanted to make my graphic look as nice as possible and luckily R offers a large number of options for graphic design. First, I reordered the factors so that the columns were in order from largest to smallest. Then, I edited the theme and the grid in order to make the graph look a bit cleaner. I also removed the legend and added some color to my graphic to make it cleaner as well. This should make my graphic easy to understand and interpret regardless of whether you have looked at the data set or not. <\/p>\n\n\n\n

\"My
My Final Graphic<\/figcaption><\/figure>\n\n\n\n

Significance:<\/strong><\/p>\n\n\n\n

Using this digital method of analysis could be very useful for the humanities. R is designed for statistical analysis, which would be great for any sort of analysis you would want to do involving finding and comparing some sort of statistic in the humanities. The amount of words a character says across multiple stories, how many times a location appears, and more can be easily analyzed using R. This shows that both data science and the digital humanities can be intertwined and used to expand our understanding of both fields.<\/p>\n","protected":false},"excerpt":{"rendered":"

Introduction: For my Hacking the Humanities midterm project, I opted to do an analysis of the locations in Chris Claremont’s Uncanny X-Men run. I wanted to determine which locations were used the most during Claremont’s run in order to perhaps understand which locations had the most importance. In order to do this, I used R, […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[4,5,6],"class_list":["post-7","post","type-post","status-publish","format-standard","hentry","category-midterm","tag-digital-humanities","tag-r","tag-x-men"],"_links":{"self":[{"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/posts\/7","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/comments?post=7"}],"version-history":[{"count":2,"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/posts\/7\/revisions"}],"predecessor-version":[{"id":15,"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/posts\/7\/revisions\/15"}],"wp:attachment":[{"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/media?parent=7"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/categories?post=7"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/midtermtyfolks.folkst.sites.carleton.edu\/blog\/wp-json\/wp\/v2\/tags?post=7"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}