The map below shows majority race by area in Mountain Pass, 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 Mountain Pass racial diversity and diversity scores. Click here to scroll to diversity data.
WhiteHispanicBlackAsianMultiple/Other
Majority race by area
The majority race in Mountain Pass overall is hispanic, making up 58.8% of residents. The next most-common racial group is white at 39.5%. There are more hispanic people in the central areas of the city. People who identify as white 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 Mountain Pass
Self-Identified Race |
Mountain Pass, CA Population |
|---|---|
White |
39.5% |
Hispanic |
58.8% |
Black |
0.0% |
Asian |
1.6% |
Native American |
0.0% |
Other |
0.0% |
Diversity and Diversity Scores for Mountain Pass, CA
The map below shows diversity in Mountain Pass. 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
Mountain Pass Diversity Score
49.7
More diverse than 83% of US cities
Mountain Pass has a diversity score of 49.7: 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. Mountain Pass is much more diverse than other US cities, more diverse than 83% 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.