57069 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 57069 Zip Code | South Dakota | U.S. |
Occupied Units Paying Rent | 2,330, 100% | 95,597 | 39,201,928 |
$199 or Less | 57, 2.45%, see rank | 3.76% | 1.50% |
$200 to $299 | 169, 7.25%, see rank | 5.89% | 3.18% |
$300 to $499 | 317, 13.61%, see rank | 19.38% | 7.37% |
$500 to $699 | 736, 31.59%, see rank | 28.86% | 16.01% |
$700 to $999 | 719, 30.86%, see rank | 27.81% | 29.17% |
$1,000 to $1,499 | 250, 10.73%, see rank | 11.89% | 26.88% |
$1,500 to $1,999 | 46, 1.97%, see rank | 1.55% | 9.79% |
$2,000 or More | 36, 1.55%, see rank | 0.86% | 6.10% |
Median | $678, see rank | $648 | $920 |
ACS 2008-2012 data
Monthly Rental | 57069 Zip Code | South Dakota | U.S. |
Occupied Units Paying Rent | 2,036, 100% | 91,039 | 37,562,111 |
$199 or Less | 63, 3.09%, see rank | 4.41% | 1.76% |
$200 to $299 | 104, 5.11%, see rank | 6.20% | 3.29% |
$300 to $499 | 322, 15.82%, see rank | 23.10% | 8.20% |
$500 to $699 | 765, 37.57%, see rank | 28.50% | 17.39% |
$700 to $999 | 567, 27.85%, see rank | 25.87% | 29.40% |
$1,000 to $1,499 | 215, 10.56%, see rank | 9.75% | 25.73% |
$1,500 to $1,999 | 0, 0.00%, see rank | 1.36% | 8.92% |
$2,000 or More | 0, 0.00%, see rank | 0.81% | 5.30% |
Median | $637, see rank | $617 | $889 |
US Census 2000 data
Monthly Rental | 57069 Zip Code | South Dakota | U.S. |
Occupied Units Paying Rent | 1,914, 100% | 79,603 | 33,386,326 |
$199 or Less | 132, 6.90%, see rank | 11.80% | 5.52% |
$200 to $299 | 322, 16.82%, see rank | 13.50% | 5.45% |
$300 to $499 | 779, 40.70%, see rank | 39.43% | 23.18% |
$500 to $699 | 462, 24.14%, see rank | 25.02% | 29.57% |
$700 to $999 | 127, 6.64%, see rank | 8.08% | 24.06% |
$1,000 to $1,499 | 92, 4.81%, see rank | 1.69% | 9.15% |
$1,500 to $1,999 | 0, 0.00%, see rank | 0.30% | 2.05% |
$2,000 or More | 0, 0.00%, see rank | 0.19% | 1.02% |
Median | $437, see rank | $426 | $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.