The map below shows majority race by area in Garden City, 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 Garden City racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Garden City overall is hispanic, making up 56.2% of residents. The next most-common racial group is white at 32.1%. There are more hispanic people in the west areas of the city. People who identify as white 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 Garden City
Self-Identified Race |
Garden City, KS Population |
|---|---|
White |
32.1% |
Hispanic |
56.2% |
Black |
5.6% |
Asian |
4.5% |
Native American |
0.1% |
Other |
1.4% |
Diversity and Diversity Scores for Garden City, KS
The map below shows diversity in Garden City. 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.
Garden City Diversity Score
57.5
More diverse than 92% of US cities
Garden City has a diversity score of 57.5: 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. Garden City is much more diverse than other US cities, more diverse than 92% of them. Within Garden City's proper boundaries, the most diverse area is northeast Garden City, and the least diverse areas are in west Garden City.
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.