The map below shows majority race by area in March ARB, 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 March ARB racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in March ARB overall is white, making up 41.3% of residents. The next most-common racial group is hispanic at 17.2%. There are more white people in the southwest 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 March ARB
Self-Identified Race |
March ARB, CA Population |
|---|---|
White |
41.3% |
Hispanic |
17.2% |
Black |
10.1% |
Asian |
16.3% |
Native American |
0.0% |
Other |
15.0% |
Diversity and Diversity Scores for March ARB, CA
The map below shows diversity in March ARB. 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.
March ARB Diversity Score
74.0
More diverse than 100% of US cities
March ARB has a diversity score of 74.0: 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. March ARB is much more diverse than other US cities, more diverse than 100% of them. Within March ARB's proper boundaries, the most diverse area is north March ARB, and the least diverse areas are in southwest March ARB.
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.