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Census Block 200605-1-015 in Montgomery County, Pennsylvania

Population180 (2010), see rank
House Units128, see rank
RaceWhites:93.9%, Hispanics:1.1%, Blacks:2.8%, Asians:1.1%, Others:2.2%
Total Area:0.04 sq mi
Water Area:0.00 sq mi (0.00%)
State:Pennsylvania
Area:Philadelphia-Camden-Wilmington, PA-NJ-DE-MD
County:Montgomery County
City:North Wales
Census Tract:200605
Census Block Group:200605-1

Census Block 200605-1-015 Map, Border, and Nearby Locations

Population by Races

White:169 (93.89%, see rank)
Black:5 (2.78%, see rank)
Hispanic:2 (1.11%, see rank)
Asian:2 (1.11%, see rank)
Native (American Indian, Alaska Native, Hawaiian Native, etc.):0 (0.00%, see rank)
One Race, Other:0 (0.00%, see rank)
Two or More Races:4 (2.22%, see rank)

Population by Gender

Male: 67 (37.22%, see rank)
Females: 113 (62.78%, see rank)

Household and Family

 Census Block 200605-1-015%
Total Households122100%
Average Household Size1.48, see rank-
1 Person Households6654.10%, see rank
2 or More Person Households5645.90%, see rank
Family Households (Families)5242.62%, see rank
Average Family Size2.02, see rank-
Married-Couple Family4234.43%, see rank
Nonfamily Households7057.38%, see rank

Housing Occupancy

 Census Block 200605-1-015%
Total Housing Units128100%
Occupied Housing Units12295.31%, see rank
Owner Occupied11992.97%, see rank
Owner Occupied with Mortgage3023.44%
Owner Occupied without Mortgage8969.53%
Renter Occupied32.34%, see rank
Vacant Housing Units64.69%, see rank
For Rent21.56%, see rank
For Sale Only21.56%, see rank
Rented or Sold, Not Occupied00.00%, see rank
For Seasonal, Recreational, or Occasional Use10.78%, see rank
For Migrant Workers00.00%, see rank
Other Vacant10.78%, 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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