57366 Zip Code Historical Amount of Rooms in a House Data
ACS 2010-2014 data
| 57366 Zip Code | South Dakota | U.S. |
Total Housing Units | 1,027, 100% | 369,186 | 132,741,033 |
1 Room | 13, 1.27%, see rank | 1.34% | 1.95% |
2 Rooms | 0, 0.00%, see rank | 2.62% | 2.48% |
3 Rooms | 79, 7.69%, see rank | 8.18% | 9.13% |
4 Rooms | 72, 7.01%, see rank | 16.39% | 16.60% |
5 Rooms | 187, 18.21%, see rank | 17.57% | 20.41% |
6 Rooms | 207, 20.16%, see rank | 14.84% | 18.06% |
7 Rooms | 105, 10.22%, see rank | 12.44% | 12.27% |
8 Rooms | 166, 16.16%, see rank | 10.74% | 8.48% |
9 Rooms or More | 198, 19.28%, see rank | 15.89% | 10.60% |
Median Rooms | 6.30, see rank | 5.80 | 5.50 |
ACS 2008-2012 data
| 57366 Zip Code | South Dakota | U.S. |
Total Housing Units | 1,000, 100% | 363,793 | 131,642,457 |
1 Room | 11, 1.10%, see rank | 1.36% | 1.95% |
2 Rooms | 20, 2.00%, see rank | 2.55% | 2.36% |
3 Rooms | 53, 5.30%, see rank | 7.91% | 8.97% |
4 Rooms | 104, 10.40%, see rank | 16.44% | 16.57% |
5 Rooms | 198, 19.80%, see rank | 17.97% | 20.41% |
6 Rooms | 155, 15.50%, see rank | 15.05% | 18.25% |
7 Rooms | 121, 12.10%, see rank | 12.84% | 12.38% |
8 Rooms | 151, 15.10%, see rank | 10.43% | 8.59% |
9 Rooms or More | 187, 18.70%, see rank | 15.45% | 10.52% |
Median Rooms | 6.20, see rank | 5.80 | 5.50 |
US Census 2000 data
| 57366 Zip Code | South Dakota | U.S. |
Total Housing Units | 1,065, 100% | 323,208 | 115,904,641 |
1 Room | 0, 0.00%, see rank | 1.23% | 2.20% |
2 Rooms | 25, 2.35%, see rank | 4.06% | 4.81% |
3 Rooms | 74, 6.95%, see rank | 8.62% | 9.84% |
4 Rooms | 130, 12.21%, see rank | 16.53% | 15.97% |
5 Rooms | 259, 24.32%, see rank | 20.54% | 20.89% |
6 Rooms | 201, 18.87%, see rank | 15.72% | 18.45% |
7 Rooms | 163, 15.31%, see rank | 12.46% | 12.06% |
8 Rooms | 120, 11.27%, see rank | 9.99% | 8.06% |
9 Rooms or More | 93, 8.73%, see rank | 10.85% | 7.70% |
Median Rooms | 5.70, see rank | 5.50 | 5.30 |
* 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.