Deciding how to visualize the data took me a lot of time and testing. I plugged the data into various charts until I found one that made the most sense. The beeswarm plot that I picked shows the overall distribution of the data and the individual data points. This graph in particular emphasizes the rank of each of the most popular baby names in New Zealand from 2001 to 2010. For example, in 2002 Thomas was the 1st ranked male name since it contains the largest sized circle in the blue column. The number in each bubble represents the number of babies with the corresponding name.
I added a legend to clarify the ranking and the gender. I enlarged the size of the dots overall so that they are easier to identify, especially with the numbers on top of them. The size of the dots correlates to the ranking of the names from 1 to 10. The bigger the dot, the higher the ranking. I also added the colors to represent the gender; red for female and blue for male.
This data visualization takes a large dataset that by itself is confusing because of the sheer amount of statistics and presents it in a way that is more digestible, which is a key component in digital humanities.
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Great post, Sunniva! I also had to use trial and error with a bunch of the different types of graphs available on the website because it was difficult to find ones that actually made the data visualization easy to understand. I really like the type of graph you picked because it not only shows each individual data point for the names, but also makes it easy to compare the name rankings. Good job!