The map below shows majority race by area in Santa Rosa, 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 Santa Rosa racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Santa Rosa overall is hispanic, making up 78.6% of residents. The next most-common racial group is white at 14.2%. There are more hispanic people in the southwest areas of the city. People who identify as white are most likely to be living in the northwest 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 Santa Rosa
Self-Identified Race |
Santa Rosa, NM Population |
|---|---|
White |
14.2% |
Hispanic |
78.6% |
Black |
1.2% |
Asian |
3.4% |
Native American |
0.4% |
Other |
2.3% |
Diversity and Diversity Scores for Santa Rosa, NM
The map below shows diversity in Santa Rosa. 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.
Santa Rosa Diversity Score
36.1
More diverse than 68% of US cities
Santa Rosa has a diversity score of 36.1: 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. Santa Rosa is more diverse than other US cities, more diverse than 68% of them. Within Santa Rosa's proper boundaries, the most diverse area is south Santa Rosa, and the least diverse areas are in southwest Santa Rosa.
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.