Lab 3

After breifly looking at the dataset, I decided I wanted to create barcharts to be able to quickly adn easily identify the changes in amount of people with each name over the years. I created the barcharts so that the x axis was the year, the y-axis was the count, and each chart was for a different name. The main things I changed from the default settings was the width of each bar so that they were more visible. I also changed the width and height of each graph so that the numbers on each axis were readable because initially they were all overlapping and it looked awful. The downside to this change was that I had to zoom out to be able to capture all the graphs in one screenshot, which could make it harder to read in the image above. I was initially hoping to rotate the text so that each year on the x-axis would be diagonal so that I wouldn’t need to stretch them out as much, but I could not figure out how to do so on this platform.

Following the lecture and readings, along with my previous stats background, I know there are so many possibilities when it comes to choices of viewing and presenting data depending on the goal of the project, which can be good because it allows for adaptability for different data and there is always a good choice, but it can also be hard to figure out which design choices are the most effective for a given dataset without “hiding” crucial information. In my experience it has always been the best to keep displays as straightforward and simple as possible to allow the given audience to be able to interpret what is being displayed with ease.

I think my choice of display relates to DH because it portrays the changes in name usage over time, and change over time is a crucial part of DH. I feel like my display is a good start to exploring the changes in name usage in New Zealand over time, but in order to do so fully, I would ned more information besides just count of names for each year.