The map below shows majority race by area in Patricia, 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 Patricia racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Patricia overall is native american, making up 55.1% of residents. The next most-common racial group is white at 32.5%. There are more native american people in the central areas of the city. People who identify as white 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 Patricia
Self-Identified Race |
Patricia, SD Population |
|---|---|
White |
32.5% |
Hispanic |
5.3% |
Black |
0.0% |
Asian |
0.0% |
Native American |
55.1% |
Other |
7.1% |
Diversity and Diversity Scores for Patricia, SD
The map below shows diversity in Patricia. 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.
Patricia Diversity Score
58.3
More diverse than 93% of US cities
Patricia has a diversity score of 58.3: 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. Patricia is much more diverse than other US cities, more diverse than 93% of them. Within Patricia's proper boundaries, the most diverse area is east Patricia, and the least diverse areas are in central Patricia.
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.