29334 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 29334 Zip Code | South Carolina | U.S. |
Occupied Units Paying Rent | 1,649, 100% | 508,636 | 39,201,928 |
$199 or Less | 21, 1.27%, see rank | 1.64% | 1.50% |
$200 to $299 | 98, 5.94%, see rank | 3.64% | 3.18% |
$300 to $499 | 70, 4.24%, see rank | 9.95% | 7.37% |
$500 to $699 | 479, 29.05%, see rank | 23.11% | 16.01% |
$700 to $999 | 747, 45.30%, see rank | 35.98% | 29.17% |
$1,000 to $1,499 | 176, 10.67%, see rank | 19.71% | 26.88% |
$1,500 to $1,999 | 44, 2.67%, see rank | 4.01% | 9.79% |
$2,000 or More | 14, 0.85%, see rank | 1.97% | 6.10% |
Median | $765, see rank | $784 | $920 |
ACS 2008-2012 data
Monthly Rental | 29334 Zip Code | South Carolina | U.S. |
Occupied Units Paying Rent | 1,690, 100% | 484,550 | 37,562,111 |
$199 or Less | 18, 1.07%, see rank | 1.94% | 1.76% |
$200 to $299 | 125, 7.40%, see rank | 3.69% | 3.29% |
$300 to $499 | 90, 5.33%, see rank | 11.43% | 8.20% |
$500 to $699 | 599, 35.44%, see rank | 25.61% | 17.39% |
$700 to $999 | 657, 38.88%, see rank | 35.11% | 29.40% |
$1,000 to $1,499 | 164, 9.70%, see rank | 17.39% | 25.73% |
$1,500 to $1,999 | 22, 1.30%, see rank | 3.32% | 8.92% |
$2,000 or More | 15, 0.89%, see rank | 1.51% | 5.30% |
Median | $706, see rank | $749 | $889 |
US Census 2000 data
Monthly Rental | 29334 Zip Code | South Carolina | U.S. |
Occupied Units Paying Rent | 852, 100% | 379,262 | 33,386,326 |
$199 or Less | 82, 9.62%, see rank | 7.25% | 5.52% |
$200 to $299 | 19, 2.23%, see rank | 8.43% | 5.45% |
$300 to $499 | 311, 36.50%, see rank | 32.35% | 23.18% |
$500 to $699 | 300, 35.21%, see rank | 31.98% | 29.57% |
$700 to $999 | 73, 8.57%, see rank | 15.40% | 24.06% |
$1,000 to $1,499 | 67, 7.86%, see rank | 3.46% | 9.15% |
$1,500 to $1,999 | 0, 0.00%, see rank | 0.77% | 2.05% |
$2,000 or More | 0, 0.00%, see rank | 0.36% | 1.02% |
Median | $514, 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.