For this week’s lab assignment, I used Rawgraphs.io in order to explore data visualization for the New Zealand data set that describes the most popular baby names from 2001to 2010. In this process, I honestly found it very difficult to find a graph that fits this data correctly. I think because Rawgraphs.io had so many options available, I kept trying and trying to find the perfect graph but it was difficult because it initially seemed like none of the graphs fit the data correctly despite the large quantity available to choose from. Due to this New Zealand baby names data set holding many variables, I was looking to find one graph that could contain all of these variables, which made this process more difficult than I think it should have been.
And in the end, I still do not believe I managed to find that perfect graph that I wanted. However, I feel I did come up with something that is acceptable, and this was by using a line chart. In using this graph, I chose to make my x-axis the year and the y-axis the count of the baby name for that year. This allowed me to see trends in terms of baby names over time. And, in trying to get all the data to fit, I knew I wanted to try to get name ranking for the year somewhere, which I managed to fit with the color of the lines. In order to make the graph more understandable in terms of these colors, I added a legend for each of the rankings that these colors represented. However, when I did that, I was quite disappointed in the website, as I fiddled with the graph for ages and could not figure out how to get all of these color rankings to fit the graph’s legend without it being cut off beyond that blue 8,7,10,1 shade. But nonetheless, afterwards, I also added gender to allow us to distinguish boys and girls names in the graphs.
Moreover, in changing the presentation options for clarity, I increased each of the margins to make the graph look nicer. Like Lin mentioned in her lecture, graphs can be made to look much more appealing just by changing even the smallest of details. To me, changing these margins is something I believe Lin would approve of, allowing me to create an acceptable graph.
Cool graph, Brandon. I had a similar format but I like how you added the key to describe the frequencies of each name over time. I also like your color scheme. Do you think this format of graph would work for other kinds of temporal datasets?
This is great Brandon, I also used a line graph as I felt it was the best option to display data over time. I also separated the names by gender and gave them unique colors to make it easier to read.
Brandon, I love the visualization you ended up choosing. I think the graph is super creative and does a good job showing rank over time, which I haven’t seen yet. And not only that, but the places to which it ranks over time, too! Again, a fantastic job thinking outside the box and displaying work that is fun to engage with and learn from!
Really impressive work on this graph! I used Flourish to create my graph, so it’s incredible to see what Rawgraphs.io can do since it seems Flourish offers fewer options compared to what you were able to create. While the color scheme is a little challenging to read at times, I love the split of the graph between male and female names, as it adds another dimension to the data you are displaying. Perhaps adding more options to the legend and display would help with the issues you had with the ranking display.