The map below shows majority race by area in Williamston, 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 Williamston racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Williamston overall is white, making up 77.1% of residents. The next most-common racial group is hispanic at 8.2%. There are more white people in the northwest areas of the city. People who identify as hispanic are most likely to be living in the west 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 Williamston
Self-Identified Race |
Williamston, SC Population |
|---|---|
White |
77.1% |
Hispanic |
8.2% |
Black |
8.0% |
Asian |
0.2% |
Native American |
0.0% |
Other |
6.4% |
Diversity and Diversity Scores for Williamston, SC
The map below shows diversity in Williamston. 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.
Williamston Diversity Score
38.9
More diverse than 71% of US cities
Williamston has a diversity score of 38.9: 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. Williamston is more diverse than other US cities, more diverse than 71% of them. Within Williamston's proper boundaries, the most diverse area is south Williamston, and the least diverse areas are in northwest Williamston.
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.