Robert Dees LIS4273

  I used a dataset of Florida gym locations downloaded from GymsListHQ: https://gymslistshq.com/b2b-database/country/united-states/list-of-gyms-in-florida  I created a geographic map of fitness centers in Florida using Tableau. Each point on the map represents a gym location, and the color of each point reflects the rating of the gym. This map allows viewers to see both where gyms are located and how they are rated. I noticed that many gyms are clustered in more populated areas such as Central and South Florida. Cities like Orlando, Tampa, and areas near Miami show a higher concentration of fitness centers, while fewer locations appear in the Panhandle and more rural parts of the state. This shows how gym locations are often connected to population density and demand. One challenge I faced was making sure Tableau correctly recognized the geographic data. I also had to make sure the dataset I downloaded worked properly in Tableau. Another challenge was adjusting the map, so the...

  https://datawrapper.dwcdn.net/DNyRO/full.png I chose this visualization because I came across it online a couple of weeks ago and found it genuinely interesting, especially in how it measures and compares what makes a state “good” for raising a family. One detail that stood out to me was that Florida was ranked somewhat higher than I expected. This caught my attention because I grew up in California and later moved to Florida, so seeing the comparison between states felt personally relevant. I think this visualization was made by a human designer using a tool called Data wrapper, rather than being fully generated by AI. Data wrapper is a known tool that lets people create maps and charts from data by choosing things like colors, legends, and titles, kind of like Tableau. Because someone has to actually decide how the data is laid out and how it’s presented, it feels much more like a human-designed visualization than something automatically generated by AI.  I have read and u...