57350 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 57350 Zip Code | South Dakota | U.S. |
Occupied Units Paying Rent | 2,156, 100% | 95,597 | 39,201,928 |
$199 or Less | 138, 6.40%, see rank | 3.76% | 1.50% |
$200 to $299 | 155, 7.19%, see rank | 5.89% | 3.18% |
$300 to $499 | 521, 24.17%, see rank | 19.38% | 7.37% |
$500 to $699 | 634, 29.41%, see rank | 28.86% | 16.01% |
$700 to $999 | 514, 23.84%, see rank | 27.81% | 29.17% |
$1,000 to $1,499 | 138, 6.40%, see rank | 11.89% | 26.88% |
$1,500 to $1,999 | 36, 1.67%, see rank | 1.55% | 9.79% |
$2,000 or More | 20, 0.93%, see rank | 0.86% | 6.10% |
Median | $546, see rank | $648 | $920 |
ACS 2008-2012 data
Monthly Rental | 57350 Zip Code | South Dakota | U.S. |
Occupied Units Paying Rent | 2,032, 100% | 91,039 | 37,562,111 |
$199 or Less | 144, 7.09%, see rank | 4.41% | 1.76% |
$200 to $299 | 166, 8.17%, see rank | 6.20% | 3.29% |
$300 to $499 | 781, 38.44%, see rank | 23.10% | 8.20% |
$500 to $699 | 455, 22.39%, see rank | 28.50% | 17.39% |
$700 to $999 | 284, 13.98%, see rank | 25.87% | 29.40% |
$1,000 to $1,499 | 146, 7.19%, see rank | 9.75% | 25.73% |
$1,500 to $1,999 | 38, 1.87%, see rank | 1.36% | 8.92% |
$2,000 or More | 18, 0.89%, see rank | 0.81% | 5.30% |
Median | $488, see rank | $617 | $889 |
US Census 2000 data
Monthly Rental | 57350 Zip Code | South Dakota | U.S. |
Occupied Units Paying Rent | 1,881, 100% | 79,603 | 33,386,326 |
$199 or Less | 367, 19.51%, see rank | 11.80% | 5.52% |
$200 to $299 | 302, 16.06%, see rank | 13.50% | 5.45% |
$300 to $499 | 730, 38.81%, see rank | 39.43% | 23.18% |
$500 to $699 | 283, 15.05%, see rank | 25.02% | 29.57% |
$700 to $999 | 169, 8.98%, see rank | 8.08% | 24.06% |
$1,000 to $1,499 | 24, 1.28%, see rank | 1.69% | 9.15% |
$1,500 to $1,999 | 6, 0.32%, see rank | 0.30% | 2.05% |
$2,000 or More | 0, 0.00%, see rank | 0.19% | 1.02% |
Median | $366, 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.