When I first clicked into the folder for the project dataset options, within seconds the first things that piqued my interest were “spotify” and “aggregated genre by year total streams”. I knew from that point I wanted to explore this dataset. Diving into this dataset, I already knew I wanted to do something closely related to the genre of Hip-hop, so the question I decided to ask was who led in overall streams for the years 2010-2023. I wanted to use this data to not only understand who is dominating the streams between the two but the gaps in streams as well. However, I did consider questions such as how the data is represented, whether any group is unrepresented, and my own personal question:s can a song belong to more than one genre. This is because there have been multiple instances where rap artists and rock artists collab to make a song.

When working to visually represent my dataset, I used Flourish to visualize the data. The first thing I did was take the information from the Excel sheet and put that directly into Flourish. Initially, I wanted to use a pie chart to represent my data, but then I found it was not visually comprehensible. Furthermore, I remember when looking at the types if graph before class that, when doing comparison it is better to use a line graph. Furthermore, I had to adjust the Excel sheet information to only have the year and streams for the genres rap and rock music. Then, resubmitted the data back to Flourish to get a better line graph. The obstacle I ran into was the coloring of the graph because I wanted the background to be black for my graph, but it was just not visually appealing. From here on, after multiple tries, I pivoted, and I attached my Claude to my Flourish to clear up the formatting. What surprised me during this process was how easy it was for the AI to take what I initially created and clean it up so fast to make it visually appealing.