Race, Diversity, and Ethnicity in Enfield Estates, Edinburg, TX

The map below shows majority race by area in Enfield Estates, 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 Enfield Estates racial diversity and diversity scores. Click here to scroll to diversity data.

Enfield Estates, Edinburg, TX map of race and ethnicity
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White
Hispanic
Black
Asian
Multiple/Other
WhiteHispanicBlackAsianMultiple/Other
Majority race by area

The majority race in Enfield Estates overall is hispanic, making up 79.3% of residents. The next most-common racial group is white at 14.7%. There are more hispanic people in the east areas of the neighborhood. People who identify as white are most likely to be living in the southeast 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 Enfield Estates

 
Self-Identified Race
Enfield Estates, Edinburg, TX Population
White
14.7%
Hispanic
79.3%
Black
4.7%
Asian
0.1%
Native American
0.5%
Other
0.7%
   

Diversity and Diversity Scores for Enfield Estates, Edinburg, TX

The map below shows diversity in Enfield Estates. 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 neighborhood would both be considered lacking diversity.

Enfield Estates, Edinburg, TX map of race and ethnicity
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More diverse Less diverse
Colorblind friendly off

Enfield Estates Diversity Score

13

With a diversity score of 13 out of 100, Enfield Estates is much less diverse than other US neighborhoods. The most diverse area within Enfield Estates's proper boundaries is to the southwest of the neighborhood. The least diverse areas are located in the east parts of Enfield Estates.

Data Sources: U.S. Census, proprietary data mapping and analysis. Special thanks to the University of Virginia.

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