The map below shows majority race by area in Pine Level, 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 Pine Level racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Pine Level overall is white, making up 84.8% of residents. The next most-common racial group is black at 8.6%. There are more white people in the northwest 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 Pine Level
Self-Identified Race |
Pine Level, AL Population |
|---|---|
White |
84.8% |
Hispanic |
3.0% |
Black |
8.6% |
Asian |
0.0% |
Native American |
0.0% |
Other |
3.7% |
Diversity and Diversity Scores for Pine Level, AL
The map below shows diversity in Pine Level. 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.
Pine Level Diversity Score
27.1
More diverse than 58% of US cities
Pine Level has a diversity score of 27.1: 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. Pine Level is about average for diversity versus other US cities, more diverse than 58% of them. Within Pine Level's proper boundaries, the most diverse area is central Pine Level, and the least diverse areas are in northwest Pine Level.
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.