The map below shows majority race by area in Grand View-on-Hudson, 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 Grand View-on-Hudson racial diversity and diversity scores. Click here to scroll to diversity data.
WhiteHispanicBlackAsianMultiple/Other
Majority race by area
The majority race in Grand View-on-Hudson overall is white, making up 81.2% of residents. The next most-common racial group is asian at 12.8%. There are more white people in the central areas of the city. People who identify as asian 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 |
Grand View-on-Hudson, NY Population |
|---|---|
White |
81.2% |
Hispanic |
3.0% |
Black |
2.9% |
Asian |
12.8% |
Native American |
0.0% |
Other |
0.1% |
Racial Distribution Key
White
Hispanic
Black
Asian
Native American
Other
Self-Identified Race |
Grand View-on-Hudson, NY Population |
|---|---|
White |
81.2% |
Hispanic |
3.0% |
Black |
2.9% |
Asian |
12.8% |
Native American |
0.0% |
Other |
0.1% |
Diversity and Diversity Scores for Grand View-on-Hudson, NY
The map below shows diversity in Grand View-on-Hudson. 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
Grand View-on-Hudson Diversity Score
72
With a diversity score of 72 out of 100, Grand View-on-Hudson is more diverse than other US cities. The most diverse area within Grand View-on-Hudson's proper boundaries is to the central of the city. The least diverse areas are located in the central parts of Grand View-on-Hudson.
Data Sources: U.S. Census, proprietary data mapping and analysis. Special thanks to the University of Virginia.
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