Lab 2

As someone who has explored coding across multiple languages and contexts, I’ve experienced firsthand the challenges and rewards of learning programming. Throughout my college experience, I’ve actively pushed myself to explore fields in which I had little prior knowledge. My journey into coding began with courses like Introduction to Computer Science, Data Structures, and Data Science. I also took classes such as Applied Linear Regression, and am currently taking Statistical Inference which involve using R to analyze data in the context of both science and the humanities. Despite having enrolled in many technical courses and learning a variety of programming languages, I’ve always found coding to be a difficult and somewhat intimidating task. It never came naturally to me. However, despite the challenges, I strongly believe that humanities students should learn to code.

Learning to code enables us to develop valuable skills such as critical thinking and problem-solving. I agree with Kirschenbaum’s claim that,

“an appreciation of how complex ideas can be imagined and expressed as a set of formal procedures—rules, models, algorithms—in the virtual space of a computer will be an essential element of a humanities education.”

Matt Kirschenbaum, Hello Worlds: Why Humanities Students Should Learn to Program

For humanities students, this is crucial because it opens up new ways of interpreting and interacting with the world. Coding not only enhances analytical abilities but also provides practical tools for humanities research. It enables us to work more efficiently with large datasets and repetitive tasks. It also opens the possibility of creating visualizations, such as 3D models of historical artifacts, architectural sites, or literary landscapes. By incorporating coding into research, humanities scholars can uncover more insights that might otherwise be difficult or time consuming.

Below is an example of some code in R. I created a contingency table where the tabyl() function from the {janitor} R package is utilized. If I were to do these calculations by hand, it would be much more time consuming. 

library(janitor)
ames <- read.csv("https://aloy.rbind.io/data/ames.csv")
​​tabyl(ames, Kitchen.Qual, Bsmt.Qual) |> adorn_percentages()