29576 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 29576 Zip Code | South Carolina | U.S. |
Occupied Units Paying Rent | 1,910, 100% | 508,636 | 39,201,928 |
$199 or Less | 0, 0.00%, see rank | 1.64% | 1.50% |
$200 to $299 | 0, 0.00%, see rank | 3.64% | 3.18% |
$300 to $499 | 70, 3.66%, see rank | 9.95% | 7.37% |
$500 to $699 | 241, 12.62%, see rank | 23.11% | 16.01% |
$700 to $999 | 717, 37.54%, see rank | 35.98% | 29.17% |
$1,000 to $1,499 | 673, 35.24%, see rank | 19.71% | 26.88% |
$1,500 to $1,999 | 146, 7.64%, see rank | 4.01% | 9.79% |
$2,000 or More | 63, 3.30%, see rank | 1.97% | 6.10% |
Median | $975, see rank | $784 | $920 |
ACS 2008-2012 data
Monthly Rental | 29576 Zip Code | South Carolina | U.S. |
Occupied Units Paying Rent | 1,789, 100% | 484,550 | 37,562,111 |
$199 or Less | 0, 0.00%, see rank | 1.94% | 1.76% |
$200 to $299 | 0, 0.00%, see rank | 3.69% | 3.29% |
$300 to $499 | 63, 3.52%, see rank | 11.43% | 8.20% |
$500 to $699 | 284, 15.87%, see rank | 25.61% | 17.39% |
$700 to $999 | 710, 39.69%, see rank | 35.11% | 29.40% |
$1,000 to $1,499 | 640, 35.77%, see rank | 17.39% | 25.73% |
$1,500 to $1,999 | 67, 3.75%, see rank | 3.32% | 8.92% |
$2,000 or More | 25, 1.40%, see rank | 1.51% | 5.30% |
Median | $953, see rank | $749 | $889 |
US Census 2000 data
Monthly Rental | 29576 Zip Code | South Carolina | U.S. |
Occupied Units Paying Rent | 980, 100% | 379,262 | 33,386,326 |
$199 or Less | 10, 1.02%, see rank | 7.25% | 5.52% |
$200 to $299 | 13, 1.33%, see rank | 8.43% | 5.45% |
$300 to $499 | 140, 14.29%, see rank | 32.35% | 23.18% |
$500 to $699 | 371, 37.86%, see rank | 31.98% | 29.57% |
$700 to $999 | 336, 34.29%, see rank | 15.40% | 24.06% |
$1,000 to $1,499 | 99, 10.10%, see rank | 3.46% | 9.15% |
$1,500 to $1,999 | 5, 0.51%, see rank | 0.77% | 2.05% |
$2,000 or More | 6, 0.61%, see rank | 0.36% | 1.02% |
Median | $680, see rank | $510 | $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.