The map below shows majority race by area in San Francisco Plaza, 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 San Francisco Plaza racial diversity and diversity scores. Click here to scroll to diversity data.
WhiteHispanicBlackAsianMultiple/Other
Majority race by area
The majority race in San Francisco Plaza overall is white, making up 83.0% of residents. The next most-common racial group is hispanic at 16.1%. 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 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 |
San Francisco Plaza, NM Population |
|---|---|
White |
83.0% |
Hispanic |
16.1% |
Black |
0.2% |
Asian |
0.0% |
Native American |
0.7% |
Other |
0.0% |
Racial Distribution Key
White
Hispanic
Black
Asian
Native American
Other
Self-Identified Race |
San Francisco Plaza, NM Population |
|---|---|
White |
83.0% |
Hispanic |
16.1% |
Black |
0.2% |
Asian |
0.0% |
Native American |
0.7% |
Other |
0.0% |
Diversity and Diversity Scores for San Francisco Plaza, NM
The map below shows diversity in San Francisco Plaza. 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.
Diversity Score
Diverse
Moderately diverse
No diversity
San Francisco Plaza Diversity Score
49
With a diversity score of 49 out of 100, San Francisco Plaza is about average for diversity versus other US cities. The most diverse area within San Francisco Plaza's proper boundaries is to the central of the city. The least diverse areas are located in the northwest parts of San Francisco Plaza.
Data Sources: U.S. Census, proprietary data mapping and analysis. Special thanks to the University of Virginia.
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