Lab Assignment #3

Instead of visualizing the top ten most popular names in order, I just decided to visualize all of the names along with their frequency using a beeswarm plot and split them by gender with girls at the top and boys at the bottom. Each point is the number of children named a specific name for a certain year. I had some trouble adjusting the points in the 2001 column such that they didn’t cover up part of the name on the y-axis, but they had to be really small to the point where there was no color, so I ultimately had to compromise and make them large enough to see the color but not cover up the entire name. To me, this seems like an interesting way to show when names started to get popular as well as showing how popular they were in a given year. For example, in this graph you can see that the name Oliver didn’t start to become popular until 2007, and the name Grace stopped being popular after 2008. The default graph made the color for girls blue and the color for boys orange, so I changed the colors to make it clear which side was male and which side was female.

What stood out to me the most about Lin’s lecture was the idea of making the visualizations of data clean and simple to look at for the users (the CAPS process). By looking at the raw data as it was, it would be nearly impossible to find any trends across the years. Although I struggled with the furthest points not covering the names, I still feel the plot does a solid job in visualizing every name and their respective counts in a way that allows for viewers to see trends in name popularity from 2001 to 2010. By following the CAPS process, it also aligns with Digital Humanitie’s emphasis on accessbility of information. Visuals of data will always be more accessible to more people than raw data will be.