I used a bar chart to display the popularity of girls’ and boys’ names from 2001-2010 in New Zealand. I thought this was the best way to present the given data, in a concise and easy way to interpret. While mapping the data, I was having difficulty properly displaying the names on the x-axis in a way that was easy to read. This was because the names were overlapping and this made it difficult to interpret. To offset the overlapping of names, I increased the width on the x-axis, this change made it so the names did not overlap, making it much easier to interpret the graph. Proper visualization of data is a very important aspect of the digital humanities because when displayed properly, data is able to tell a story to the observer of a graph.
2 thoughts on “Blog 3 – Data Visualization (Marcus Merkelbach)”
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I also struggled with fitting the names, which is what drove me away from the bar and line graphs. I didn’t initially consider changing the graph from the default settings, so you were definitely a step ahead of me there. I am slightly confused about the y-axis on your graph; is the graph displaying how many babies with that name were born in total over those ten years?
Good job getting all the names to fit! I got them to on Rawgraphs but then the photo I saved was so low resolution I had to switch graph types but this photo looks great. Good idea to color the graphs differently for male and female names. I think a bar graph is definitely a great strategy for graphing the different names I wonder though if having so many bars makes the bar graph too hard to read in comparison to if you made two bar graphs, one female names on male? All in all great visualization!