In this lab assignment, I built a line graph on Flourish for popular baby names in New Zealand from 2001 to 2010. The reason I chose a line graph is that it is easier and clearer to show the trend of name counts changing from year to year. I labeled the x-axis as the year, from 2001 to 2010, and the y-axis as the counts of a name in the corresponding year. Then, I divided the data into two parts, male and female, and filtered them by name. As a result, a single line graph represents the trend or change in name counts from 2001 to 2010.
To improve the clarity of the visualization, I first added titles to the axes—”Year” to the x-axis and “Count” to the y-axis—and added a title to the graph. Moreover, I changed the curved line to a straight line because only the count of each year is provided, and we do not know the specific trend during the year. Therefore, I think a straight line is better to describe the change between years.
From my perspective, the way my visualization relates to Digital Humanities (DH) is that turning a dataset into a graph or chart can help reveal specific cultural trends or shifts. In this lab assignment, I created a graph using the data for popular baby names in New Zealand. As a result, we can identify patterns in these trends and changes, which may relate to other events that occurred during the time period, allowing us to better analyze the reasons behind these patterns.
3 thoughts on “Lab 3”
Leave a Reply
This site uses Akismet to reduce spam. Learn how your comment data is processed.
I like the way you chose to present the data, being able to view the trends name by name. I kind of wish the graph were interactive on the blog post, it would be cool to get to mess around with it. I appreciate the work you put into making the chart easy to read and understand what is going on.
Hi Hongmiao! Your data visualization is fascinating! I appreciate the reasoning you provided for changing the curved line to a straight one—since the data only includes the yearly counts and doesn’t reflect the specific trends within each year. That’s a perspective I hadn’t considered initially, and it makes a lot of sense when aiming for the most accurate representation of the data. However, I think it could also be interesting to explore a way to compare multiple names and their trends simultaneously. With just one name and graph, it’s a bit harder to grasp any unique or distinct patterns that might emerge in comparison to others.
Hi, I really like the visualization that you created. I think that the things you did to make it more clear like adding a title and the straight line were very smart decisions on your part. I also like how you can choose one name at a time to see the result instead of having lines for all the names on the same plane which tends to create a more cluttered visual.