Race, Diversity, and Ethnicity in Hardwood, LA

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

Hardwood, LA 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 Hardwood overall is white, making up 81.6% of residents. The next most-common racial group is black at 16.6%. There are more white people in the east areas of the city. People who identify as black are most likely to be living in the northeast 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 Hardwood
Race
Hardwood, LA Population
White
81.6%
Hispanic
0.7%
Black
16.6%
Asian
0.0%
Native American
0.0%
Other
1.1%
 

Racial Distribution Key

White
Hispanic
Black
Asian
Native American
Other
 
Self-Identified Race
Hardwood, LA Population
White
81.6%
Hispanic
0.7%
Black
16.6%
Asian
0.0%
Native American
0.0%
Other
1.1%
   

Diversity and Diversity Scores for Hardwood, LA

The map below shows diversity in Hardwood. 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.

Hardwood, LA map of race and ethnicity
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Diversity Score

Diverse
Moderately diverse
No diversity
 

Hardwood Diversity Score

57

With a diversity score of 57 out of 100, Hardwood is about average for diversity versus other US cities. The most diverse area within Hardwood's proper boundaries is to the northeast of the city. The least diverse areas are located in the east parts of Hardwood.

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

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