Module # 2 Google Table, Tableau and Geographic map

 

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 points were visible without overcrowding the display.

I used color to represent average gym ratings, which helps viewers quickly identify higher and lower rated locations. Proximity also plays an important role, as gyms that appear close together on the map are visually grouped, showing clusters in urban areas. Adding labels and tooltips improves clarity by giving viewers more detailed information when they interact with the map. To further improve the visualization, I could adjust the color scale to create clearer contrasts or add filters so users could explore gyms by city or rating range. I also think this map could be improved with a larger dataset, since I was limited to about 20 gyms from the data I found.


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