introduction:
For my project, I decided to create a data visualization that represents the number of appearances the various X-Men characters made on comic book covers over various editions. This visualization aims to give an interactive experience of the data collected on this subject.
Sources:
I used a dataset from the Claremont Run Project as the basis of this project. The original data I downloaded had information on comic book issues 200-249. It also included the cover artists, narrative captions, characters visualized, and aspects of dialogue.
Processes:
I decided that I wanted to focus on just the characters visualized column and the issues they were featured in. To make these changes, I exported the dataset to Google Sheets and organized it with the issue on the left column and the top 10 most featured characters across the top. I decided to limit the characters I looked at to just these 10 because there were a lot of characters featured a single time and I felt that would clutter my visualization. Within these columns, I then organized the data by finding the editions they were featured in and creating a summative organization system. I noted the number of times they had been featured for each issue. For example, if Colossus was featured in the 200 and 202 issue, the row of the 200 and 201 issue would show that he had 1 feature, and the 202 row would show that he had 2 features.
Presentation:
After organizing my data, I decided to use Flourish to represent the numbers in a visual way. I chose to use a line graph because I wanted to represent the characters individually and over time (issues). I chose different colors for each character to set them apart and then had the name labels on the side to make it clear which line was which character. I also made it interactive by choosing an option in Flourish that allows the viewer to search for a character and zoom in on their line specifically. Similarly, the viewer can put their mouse over a particular area of the graph and it will show how many cover features they had at the release of that issue.
Significance:
I thought the data visualization I did here created a great product. This was my first time being able to create an interactive graph, and I am very proud of how it turned out. Not only this, but I thought that the way I organized the data before inputting it to Flourish was a key aspect of this process. By narrowing down the data to just the top 10, it allowed me to create a clear and understandable visualization. I think the choices I made can give some new insights to the data. The use of the interactive line graph allows the viewer to see the data in a comparative way as well as over time. The flexibility of the data using these visualization tools is a definite plus. I also think that it was an output unique to Digital Arts and Humanities as opposed to just data science because of the purpose and some choices I made. The purpose of this project was to take a humanities work (comics) and derive data from it (# of appearances), which was then used to create a digitalized visualization (graph). I think the sources and processes are different from how I see regular data sciences.
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