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30009 Zip Code Historical House Occupancy Status Data

 

ACS 2010-2014 data

 30009 Zip CodeGeorgiaU.S.
Total Housing Units6,052, see rank, 100%4,114,496132,741,033
Occupied Housing Units5,830, 96.33%, see rank86.05%87.55%
Owner Occupied3,274, 54.10%, see rank55.22%56.34%
Renter Occupied2,556, 42.23%, see rank30.83%31.21%
Vacant Housing Units222, 3.67%, see rank13.95%12.45%
For Rent132, 2.18%, see rank3.35%2.34%
For Sale Only90, 1.49%, see rank1.73%1.20%
Rented or Sold, Not Occupied0, 0.00%, see rank0.98%0.92%
For Seasonal, Recreational, or Occasional Use0, 0.00%, see rank2.49%3.97%
For Migrant Workers0, 0.00%, see rank0.02%0.03%
Other Vacant0, 0.00%, see rank5.37%4.00%

US Census 2010 data

 30009 Zip CodeGeorgiaU.S.
Total Housing Units6,408, see rank, 100%4,088,801131,704,730
Occupied Housing Units5,859, 91.43%, see rank87.69%88.62%
Owner Occupied3,611, 56.35%, see rank57.58%57.69%
Renter Occupied2,248, 35.08%, see rank30.11%30.93%
Vacant Housing Units549, 8.57%, see rank12.31%11.38%
For Rent309, 4.82%, see rank4.27%3.14%
For Sale Only102, 1.59%, see rank2.05%1.44%
Rented or Sold, Not Occupied30, 0.47%, see rank0.49%0.48%
For Seasonal, Recreational, or Occasional Use38, 0.59%, see rank1.99%3.53%
For Migrant Workers0, 0.00%, see rank0.02%0.02%
Other Vacant70, 1.09%, see rank3.49%2.77%

ACS 2008-2012 data

 30009 Zip CodeGeorgiaU.S.
Total Housing Units5,791, see rank, 100%4,086,231131,642,457
Occupied Housing Units5,416, 93.52%, see rank85.86%87.53%
Owner Occupied3,274, 56.54%, see rank56.66%57.34%
Renter Occupied2,142, 36.99%, see rank29.20%30.19%
Vacant Housing Units375, 6.48%, see rank14.14%12.47%
For Rent202, 3.49%, see rank3.59%2.50%
For Sale Only96, 1.66%, see rank2.05%1.38%
Rented or Sold, Not Occupied0, 0.00%, see rank1.02%0.91%
For Seasonal, Recreational, or Occasional Use68, 1.17%, see rank2.36%3.81%
For Migrant Workers0, 0.00%, see rank0.02%0.03%
Other Vacant9, 0.16%, see rank5.09%3.84%

* ACS stands for U.S. Census American Community Survey. According to the U.S. Census, if the date is a range, you can interpret the data as an average of the period of time.


 
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