Explanation:
For this project, I chose to visualize the popularity of baby names over time using a heatmap. The dataset contains ranked names from 2001 to 2010, along with the number of babies given each name per year. A heatmap is an appropriate choice because it allows for an easy comparison of trends across multiple names and years. The color intensity represents the frequency of a given name in a specific year, making it visually clear which names were more popular at different times.
What did I improve?
To improve the clarity of my visualization, I made one key adjustment: I separated all gender data into distinct groups (female/male). This ensures that we can analyze female name trends without interference from male name data. Additionally, I adjusted the colors from linear to binned to create a stronger contrast between highly popular and less common names, making the heatmap more readable.
Reflection:
This project relates to Digital Humanities in several ways. DH emphasizes using computational methods to analyze cultural and historical trends. This visualization demonstrates how digital tools can help us study naming patterns over time. Names are deeply tied to cultural identity, and by examining their popularity, we gain insights into societal shifts, media influences, and generational trends. The heatmap, as a form of data-driven storytelling, transforms raw numbers into an accessible visual narrative. Such visualization allows us to engage with historical naming trends in a more intuitive way.
