The map below shows majority race by area in Los Molinos, 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 Los Molinos racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Los Molinos overall is white, making up 59.3% of residents. The next most-common racial group is hispanic at 36.2%. There are more white people in the north 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 Los Molinos
Self-Identified Race |
Los Molinos, CA Population |
|---|---|
White |
59.3% |
Hispanic |
36.2% |
Black |
0.0% |
Asian |
1.4% |
Native American |
0.0% |
Other |
3.1% |
Diversity and Diversity Scores for Los Molinos, CA
The map below shows diversity in Los Molinos. 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.
Los Molinos Diversity Score
51.6
More diverse than 86% of US cities
Los Molinos has a diversity score of 51.6: 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. Los Molinos is much more diverse than other US cities, more diverse than 86% of them. Within Los Molinos's proper boundaries, the most diverse area is west Los Molinos, and the least diverse areas are in southeast Los Molinos.
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.