The map below shows majority race by area in San Martin, 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 San Martin racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in San Martin overall is hispanic, making up 44.5% of residents. The next most-common racial group is white at 42.0%. There are more hispanic people in the northwest areas of the city. People who identify as white are most likely to be living in the east 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 San Martin
Self-Identified Race |
San Martin, CA Population |
|---|---|
White |
42.0% |
Hispanic |
44.5% |
Black |
3.3% |
Asian |
6.7% |
Native American |
0.2% |
Other |
3.3% |
Diversity and Diversity Scores for San Martin, CA
The map below shows diversity in San Martin. 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.
San Martin Diversity Score
61.9
More diverse than 95% of US cities
San Martin has a diversity score of 61.9: 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. San Martin is much more diverse than other US cities, more diverse than 95% of them. Within San Martin's proper boundaries, the most diverse area is west San Martin, and the least diverse areas are in northwest San Martin.
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.