The map below shows majority race by area in Cactus Flat, 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 Cactus Flat racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Cactus Flat overall is white, making up 81.3% of residents. The next most-common racial group is other at 7.4%. There are more white people in the east areas of the city. People who identify as other are most likely to be living in the central 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 Cactus Flat
Self-Identified Race |
Cactus Flat, SD Population |
|---|---|
White |
81.3% |
Hispanic |
6.7% |
Black |
0.8% |
Asian |
0.7% |
Native American |
3.1% |
Other |
7.4% |
Diversity and Diversity Scores for Cactus Flat, SD
The map below shows diversity in Cactus Flat. 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.
Cactus Flat Diversity Score
32.8
More diverse than 65% of US cities
Cactus Flat has a diversity score of 32.8: 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. Cactus Flat is more diverse than other US cities, more diverse than 65% of them. Within Cactus Flat's proper boundaries, the most diverse area is central Cactus Flat, and the least diverse areas are in east Cactus Flat.
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.