The map below shows majority race by area in La Selva Beach, 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 La Selva Beach racial diversity and diversity scores. Click here to scroll to diversity data.
WhiteHispanicBlackAsianMultiple/Other
Majority race by area
The majority race in La Selva Beach overall is white, making up 76.6% of residents. The next most-common racial group is hispanic at 12.0%. There are more white people in the central areas of the city. People who identify as hispanic 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 La Selva Beach
Self-Identified Race |
La Selva Beach, CA Population |
|---|---|
White |
76.6% |
Hispanic |
12.0% |
Black |
0.0% |
Asian |
2.0% |
Native American |
0.0% |
Other |
9.3% |
Diversity and Diversity Scores for La Selva Beach, CA
The map below shows diversity in La Selva Beach. 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.
Less diverse
More diverse
Colorblind friendly
off
La Selva Beach Diversity Score
38.9
More diverse than 72% of US cities
La Selva Beach has a diversity score of 38.9: 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. La Selva Beach is more diverse than other US cities, more diverse than 72% of them.
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.