The map below shows majority race by area in Little Rock, 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 Little Rock racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Little Rock overall is white, making up 41.2% of residents. The next most-common racial group is black at 32.1%. There are more white people in the south areas of the city. People who identify as black 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 Little Rock
Self-Identified Race |
Little Rock, SC Population |
|---|---|
White |
41.2% |
Hispanic |
3.2% |
Black |
32.1% |
Asian |
0.0% |
Native American |
18.4% |
Other |
5.2% |
Diversity and Diversity Scores for Little Rock, SC
The map below shows diversity in Little Rock. 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.
Little Rock Diversity Score
69.0
More diverse than 99% of US cities
Little Rock has a diversity score of 69.0: 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. Little Rock is much more diverse than other US cities, more diverse than 99% of them. Within Little Rock's proper boundaries, the most diverse area is central Little Rock, and the least diverse areas are in south Little Rock.
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.