The map below shows majority race by area in Lost City, 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 Lost City racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Lost City overall is white, making up 42.5% of residents. The next most-common racial group is native american at 27.0%. There are more white people in the northwest areas of the city. People who identify as native american 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 Lost City
Self-Identified Race |
Lost City, OK Population |
|---|---|
White |
42.5% |
Hispanic |
9.7% |
Black |
0.6% |
Asian |
1.1% |
Native American |
27.0% |
Other |
19.1% |
Diversity and Diversity Scores for Lost City, OK
The map below shows diversity in Lost City. 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.
Lost City Diversity Score
70.0
More diverse than 99% of US cities
Lost City has a diversity score of 70.0: 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. Lost City is much more diverse than other US cities, more diverse than 99% of them. Within Lost City's proper boundaries, the most diverse area is central Lost City, and the least diverse areas are in northwest Lost City.
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.