The map below shows majority race by area in Red Lake, 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 Red Lake racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Red Lake overall is native american, making up 91.3% of residents. The next most-common racial group is white at 5.3%. There are more native american people in the northeast areas of the city. People who identify as white are most likely to be living in the northwest 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 Red Lake
Self-Identified Race |
Red Lake, MN Population |
|---|---|
White |
5.3% |
Hispanic |
0.2% |
Black |
0.7% |
Asian |
0.0% |
Native American |
91.3% |
Other |
2.5% |
Diversity and Diversity Scores for Red Lake, MN
The map below shows diversity in Red Lake. 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.
Red Lake Diversity Score
16.2
More diverse than 37% of US cities
Red Lake has a diversity score of 16.2: 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. Red Lake is less diverse than other US cities, more diverse than 37% of them. Within Red Lake's proper boundaries, the most diverse area is northwest Red Lake, and the least diverse areas are in northeast Red Lake.
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.