The map below shows majority race by area in Sweet Lake, 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 Sweet Lake racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Sweet Lake overall is white, making up 83.3% of residents. The next most-common racial group is other at 10.4%. There are more white people in the north areas of the city. People who identify as other 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 Sweet Lake
Self-Identified Race |
Sweet Lake, LA Population |
|---|---|
White |
83.3% |
Hispanic |
0.4% |
Black |
4.7% |
Asian |
0.0% |
Native American |
1.2% |
Other |
10.4% |
Diversity and Diversity Scores for Sweet Lake, LA
The map below shows diversity in Sweet Lake. 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.
Sweet Lake Diversity Score
29.3
More diverse than 60% of US cities
Sweet Lake has a diversity score of 29.3: 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. Sweet Lake is more diverse than other US cities, more diverse than 60% of them. Within Sweet Lake's proper boundaries, the most diverse area is northwest Sweet Lake, and the least diverse areas are in central Sweet Lake.
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.