Race, Diversity, and Ethnicity in Van Order, SD

The map below shows majority race by area in Van Order, 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 Van Order racial diversity and diversity scores. Click here to scroll to diversity data.

Van Order, SD map of race and ethnicity
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White
Hispanic
Black
Asian
Multiple/Other
WhiteHispanicBlackAsianMultiple/Other
Majority race by area

The majority race in Van Order overall is white, making up 81.2% of residents. The next most-common racial group is hispanic at 7.6%. There are more white people in the northeast areas of the city. People who identify as hispanic are most likely to be living in the north 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 Van Order
Race
Van Order, SD Population
White
81.2%
Hispanic
7.6%
Black
4.1%
Asian
0.0%
Native American
2.9%
Other
4.3%
 

Racial Distribution Key

White
Hispanic
Black
Asian
Native American
Other
 
Self-Identified Race
Van Order, SD Population
White
81.2%
Hispanic
7.6%
Black
4.1%
Asian
0.0%
Native American
2.9%
Other
4.3%
   

Diversity and Diversity Scores for Van Order, SD

The map below shows diversity in Van Order. 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.

Van Order, SD map of race and ethnicity
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Diversity Score

Diverse
Moderately diverse
No diversity
 

Van Order Diversity Score

88

With a diversity score of 88 out of 100, Van Order is much more diverse than other US cities. The most diverse area within Van Order's proper boundaries is to the north of the city. The least diverse areas are located in the northeast parts of Van Order.

Data Sources: U.S. Census, proprietary data mapping and analysis. Special thanks to the University of Virginia.

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