The map below shows majority race by area in Mount Dora, as self-identified on the US census. Darker shades indicate a larger racial majority in that neighborhood. This page also contains data and maps on Mount Dora racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Mount Dora overall is white, making up 60.6% of residents. The next most-common racial group is hispanic at 21.9%. There are more white people in the southwest areas of the city. People who identify as hispanic are most likely to be living in the southeast places. The data below shows how many people identify themselves as each of the following races, which most Americans base on their family's national origin:
Race in Mount Dora
Self-Identified Race |
Mount Dora, FL Population |
|---|---|
White |
60.6% |
Hispanic |
21.9% |
Black |
12.6% |
Asian |
0.9% |
Native American |
0.0% |
Other |
3.9% |
Diversity and Diversity Scores for Mount Dora, FL
The map below shows diversity in Mount Dora. Areas in green are more diverse, while areas in red are much less diverse. Diversity, in this case, means a mixture of people with different race and ethnicity living close to one another. For example, all-black and all-white areas in the city would both be considered lacking diversity.
Mount Dora Diversity Score
56.7
More diverse than 91% of US cities
Mount Dora has a diversity score of 56.7: the chance, in percent, that two residents picked at random belong to different racial or ethnic groups, from ACS race counts. A place where everyone shares one group scores 0, and an even mix of the six groups in the chart above scores the maximum, 83.3. Mount Dora is much more diverse than other US cities, more diverse than 91% of them. Within Mount Dora's proper boundaries, the most diverse area is southeast Mount Dora, and the least diverse areas are in southwest Mount Dora.
Source: BestNeighborhood calculations from the U.S. Census Bureau, American Community Survey (ACS) 2020-2024 5-year estimates (race and Hispanic origin); proprietary data mapping and analysis. Special thanks to the University of Virginia.