Concept:
Since January 2024, there has been over 50 school shootings in the US, with the four most recent ones being just two days before this post was made, all on September 21, 2024. The frequency of school shootings in the US is devastatingly overlooked, and I wanted to make a piece that could raise awareness on how insanely young a lot of these shooters are. “Know the Numbers” is a generative text output that randomizes statistics from a CSV file that consists of all school shootings in the US from 1990 until September 4, 2024. The link to the Washington Post’s CSV file can be found here. To view these shocking statistics, simply click anywhere on the canvas with your mouse.
Originally, I wanted to do a data visualization to emphasize the regions with the most shootings, but I realized that could easily be found with a quick Google search. Something that wasn’t as common was close up statistics of these shootings, which is what I wanted to do, but I didn’t know how to display it. I scrolled through other students’ works to get a feel of how they did this assignment, and Ahmad’s project looked like a good foundation for my idea, so I took inspiration from his work. I ended up creating this piece that emphasizes the age of these shooters. Some say unknown to keep up with the real statistics. There will also be some where the kills, injuries, and casualties are zero and the age of the shooter might even be unknown. These represent gunshots that went off in a school setting that fortunately didn’t harm anyone.
I wanted to add a dripping blood border to the top edge of the canvas to emphasize the gun violence. I tried to code some blood drips from this YouTube tutorial by Barney Codes, but it ended up being too difficult and it wasn’t static nor was it grouped together, so I decided to keep the poster simple.
The Piece:
Highlight:
The piece of code I’m proud of is ironically one that wasn’t much use to my piece. For the other sections (number of kills, number of casualties, etc) I managed to combine the CSV data with a message, for example, the CSV data on casualties is “16,” but I was able to add “there were” and “casualties” before and after the data was displayed. However, the age was the only one that didn’t work, and I couldn’t figure out the reason why, so on Google Sheets, I manually added “the shooter was #-years-old” in place of just the age, for over 400 rows of data. This way, I would’ve still been able to include context text with the statistic even though the code doesn’t work. I kept looking, and I eventually found out what I did wrong, which was a silly spelling mistake. So I’m proud of my patience and determination in showing these age numbers, otherwise, I would’ve just scrapped the ages. I’m also proud of myself for still trying to find out what was wrong so that I could learn from my mistake.
let numRows = shooting.getRowCount();
let age = shooting.getColumn('shooter_age');
let state = shooting.getColumn('state');
let year = shooting.getColumn('year')
let kills = shooting.getColumn('killed')
let injuries = shooting.getColumn('injured')
let casualties = shooting.getColumn('casualties')
print(age[statistic - 1]);
push();
textSize(53);
fill(233, 210, 18);
text(str(age[statistic - 1]), width/2, height/2 + 210);
pop();
Reflection/Future Improvements:
This project was eye-opening even for me. I already knew how terrible these statistics were, but as I was manually adding text to the ages, I saw the age of every shooter on that list. It was already devastating that the vast majority of shooters were young teens, but the most jaw-dropping were the single digit numbers. The youngest school shooter was just 6-years-old, which is absolutely insane to me. Not to mention, there were three 6-year-old shooters, not just one. I hope others will find this project as informative as I did, because I definitely learned a lot more from it. The project itself was relatively easy because it was text. I know that if I stuck with data visualization, it would’ve been a lot harder for me to complete.
For future improvements, I would like to somehow adjust the grammar to match the statistic. For example, if there’s one causality, it would say “there were one causalities” because it is a fixed text. I would also like to add the blood drip edge that I originally wanted. In general, I’d want to make it pop more so that people would know exactly what it’s about once they see it, without reading anything yet.