When thinking about graphs to display significance of data over time, my first thought would be a bar graph with time on the X axis and the data being measured on the Y axis. However after exploring Flourish a bit, I re-discovered heatmaps and how data can be conveyed through opacity of color.
I think a heatmap is a good choice for this assignment because the opacity and intensity in color can instantly draw attention to a certain spot for each name. Just from a glance, Isabella and Jacob can be seen as the most chosen baby names within the year 2010 due to the darkness of each box labelling their pick rate. Just like a bar graph numbers can be estimated at face value, or be told apart by hovering over data to reveal a more specific number, which is why i think a less plain graph is better.
Process+
Overall the creation process wasn’t too bad, but the initial learning curve of the website was very difficult. After inputting my data the website kept assigning the wrong values to different places and without properly reading through each line of text in the Data tab, it took my a while to fix things around. I personally decided to omit the ranking and gender categories because of the lack of variables to add with this particular graph, and also because I felt it wasn’t as important in conveying the important information as what you see above. As for the changes I made from the default version, I added a tab to switch between boys (M) and girls (F) and added a title for an overall description of the dataset. Additionally, i slightly changed the scale for opacity to better differentiate each names pick density within the boxes.
My main goal was trying to replicate some of the points Lin mentioned in class about keeping the data clean without clutter, while still being able to convey important information relevant to the data set. In this case, without taking up space labeling rank, I feel i was able to accomplish that because we can see change in name pick rate, and pick density over time for boys and girls, while also comparing rows to see those differences. Connecting this and Lin’s lecture to DH, since I feel like this graph is organized well, it makes it easier to follow and understand the information being presented which is an important part of data visualization. Being able to visualize data clearly is what allows information to be passed and shared properly among others, helping to grow creativity and create big projects.