The map below shows majority race by area in Nances Creek, 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 Nances Creek racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Nances Creek overall is white, making up 96.8% of residents. The next most-common racial group is black at 1.3%. There are more white people in the north areas of the city. People who identify as black 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 Nances Creek
Self-Identified Race |
Nances Creek, AL Population |
|---|---|
White |
96.8% |
Hispanic |
0.5% |
Black |
1.3% |
Asian |
0.0% |
Native American |
0.3% |
Other |
1.1% |
Diversity and Diversity Scores for Nances Creek, AL
The map below shows diversity in Nances Creek. 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.
Nances Creek Diversity Score
6.3
More diverse than 9% of US cities
Nances Creek has a diversity score of 6.3: 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. Nances Creek is much less diverse than other US cities, more diverse than 9% of them. Within Nances Creek's proper boundaries, the most diverse area is central Nances Creek, and the least diverse areas are in north Nances Creek.
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.