The map below shows majority race by area in Seven Oaks, 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 Seven Oaks racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Seven Oaks overall is white, making up 81.9% of residents. The next most-common racial group is hispanic at 8.3%. There are more white people in the northwest areas of the city. People who identify as hispanic 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 Seven Oaks
Self-Identified Race |
Seven Oaks, CA Population |
|---|---|
White |
81.9% |
Hispanic |
8.3% |
Black |
3.9% |
Asian |
0.7% |
Native American |
0.0% |
Other |
5.2% |
Diversity and Diversity Scores for Seven Oaks, CA
The map below shows diversity in Seven Oaks. 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.
Seven Oaks Diversity Score
31.9
More diverse than 64% of US cities
Seven Oaks has a diversity score of 31.9: 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. Seven Oaks is more diverse than other US cities, more diverse than 64% of them. Within Seven Oaks's proper boundaries, the most diverse area is east Seven Oaks, and the least diverse areas are in northwest Seven Oaks.
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.