30066 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 30066 Zip Code | Georgia | U.S. |
Occupied Units Paying Rent | 3,799, 100% | 1,190,014 | 39,201,928 |
$199 or Less | 0, 0.00%, see rank | 1.50% | 1.50% |
$200 to $299 | 0, 0.00%, see rank | 2.66% | 3.18% |
$300 to $499 | 13, 0.34%, see rank | 7.45% | 7.37% |
$500 to $699 | 186, 4.90%, see rank | 17.24% | 16.01% |
$700 to $999 | 1,064, 28.01%, see rank | 35.81% | 29.17% |
$1,000 to $1,499 | 1,680, 44.22%, see rank | 27.76% | 26.88% |
$1,500 to $1,999 | 679, 17.87%, see rank | 5.62% | 9.79% |
$2,000 or More | 177, 4.66%, see rank | 1.96% | 6.10% |
Median | $1,197, see rank | $874 | $920 |
ACS 2008-2012 data
Monthly Rental | 30066 Zip Code | Georgia | U.S. |
Occupied Units Paying Rent | 3,857, 100% | 1,116,630 | 37,562,111 |
$199 or Less | 0, 0.00%, see rank | 1.69% | 1.76% |
$200 to $299 | 0, 0.00%, see rank | 2.97% | 3.29% |
$300 to $499 | 73, 1.89%, see rank | 8.41% | 8.20% |
$500 to $699 | 35, 0.91%, see rank | 18.64% | 17.39% |
$700 to $999 | 1,360, 35.26%, see rank | 35.83% | 29.40% |
$1,000 to $1,499 | 1,685, 43.69%, see rank | 25.78% | 25.73% |
$1,500 to $1,999 | 585, 15.17%, see rank | 4.95% | 8.92% |
$2,000 or More | 119, 3.09%, see rank | 1.72% | 5.30% |
Median | $1,133, see rank | $849 | $889 |
US Census 2000 data
Monthly Rental | 30066 Zip Code | Georgia | U.S. |
Occupied Units Paying Rent | 2,450, 100% | 905,913 | 33,386,326 |
$199 or Less | 0, 0.00%, see rank | 6.44% | 5.52% |
$200 to $299 | 0, 0.00%, see rank | 6.18% | 5.45% |
$300 to $499 | 29, 1.18%, see rank | 22.20% | 23.18% |
$500 to $699 | 291, 11.88%, see rank | 26.87% | 29.57% |
$700 to $999 | 1,314, 53.63%, see rank | 28.51% | 24.06% |
$1,000 to $1,499 | 680, 27.76%, see rank | 8.34% | 9.15% |
$1,500 to $1,999 | 125, 5.10%, see rank | 1.07% | 2.05% |
$2,000 or More | 11, 0.45%, see rank | 0.39% | 1.02% |
Median | $882, see rank | $613 | $602 |
* 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.