The map below shows majority race by area in Milnesville, 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 Milnesville racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Milnesville overall is white, making up 91.8% of residents. The next most-common racial group is hispanic at 8.1%. There are more white people in the central areas of the city. People who identify as hispanic are most likely to be living in the southwest 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 Milnesville
Self-Identified Race |
Milnesville, PA Population |
|---|---|
White |
91.8% |
Hispanic |
8.1% |
Black |
0.1% |
Asian |
0.0% |
Native American |
0.0% |
Other |
0.0% |
Diversity and Diversity Scores for Milnesville, PA
The map below shows diversity in Milnesville. 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.
Milnesville Diversity Score
15.1
More diverse than 34% of US cities
Milnesville has a diversity score of 15.1: 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. Milnesville is less diverse than other US cities, more diverse than 34% of them. Within Milnesville's proper boundaries, the most diverse area is southwest Milnesville, and the least diverse areas are in central Milnesville.
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.