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Census Block 009707-1-009 in San Bernardino County, California

Population127 (2010), see rank
House Units109, see rank
RaceWhites:87.4%, Hispanics:16.5%, Blacks:1.6%, Asians:1.6%, Others:9.4%
Total Area:0.04 sq mi
Water Area:0.00 sq mi (0.00%)
State:California
Area:Riverside-San Bernardino-Ontario, CA
County:San Bernardino County
City:Apple Valley
Census Tract:009707
Census Block Group:009707-1

Census Block 009707-1-009 Map, Border, and Nearby Locations

Population by Races

White:111 (87.40%, see rank)
Black:2 (1.57%, see rank)
Hispanic:21 (16.54%, see rank)
Asian:2 (1.57%, see rank)
Native (American Indian, Alaska Native, Hawaiian Native, etc.):1 (0.79%, see rank)
One Race, Other:6 (4.72%, see rank)
Two or More Races:5 (3.94%, see rank)

Population by Gender

Male: 48 (37.80%, see rank)
Females: 79 (62.20%, see rank)

Household and Family

 Census Block 009707-1-009%
Total Households89100%
Average Household Size1.43, see rank-
1 Person Households5561.80%, see rank
2 or More Person Households3438.20%, see rank
Family Households (Families)3134.83%, see rank
Average Family Size2.10, see rank-
Married-Couple Family2528.09%, see rank
Nonfamily Households5865.17%, see rank

Housing Occupancy

 Census Block 009707-1-009%
Total Housing Units109100%
Occupied Housing Units8981.65%, see rank
Owner Occupied5651.38%, see rank
Owner Occupied with Mortgage2321.10%
Owner Occupied without Mortgage3330.28%
Renter Occupied3330.28%, see rank
Vacant Housing Units2018.35%, see rank
For Rent21.83%, see rank
For Sale Only43.67%, see rank
Rented or Sold, Not Occupied32.75%, see rank
For Seasonal, Recreational, or Occasional Use21.83%, see rank
For Migrant Workers00.00%, see rank
Other Vacant98.26%, see rank

*Based on 2010 data.


*A census block is the smallest geographic area defined by the United States Census Bureau to take census. In total, there are more than 10 million census blocks in the United Status with an average of around 30 residents in each. A census block normally only covers a street block or a small community. It is ideal for studying data relating to the smallest geographic area.


 
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