16346 Zip Code Historical Amount of Rooms in a House Data
ACS 2010-2014 data
| 16346 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,662, 100% | 5,578,393 | 132,741,033 |
1 Room | 0, 0.00%, see rank | 1.73% | 1.95% |
2 Rooms | 11, 0.66%, see rank | 1.73% | 2.48% |
3 Rooms | 51, 3.07%, see rank | 7.21% | 9.13% |
4 Rooms | 207, 12.45%, see rank | 12.40% | 16.60% |
5 Rooms | 302, 18.17%, see rank | 16.40% | 20.41% |
6 Rooms | 464, 27.92%, see rank | 21.82% | 18.06% |
7 Rooms | 239, 14.38%, see rank | 14.82% | 12.27% |
8 Rooms | 185, 11.13%, see rank | 10.70% | 8.48% |
9 Rooms or More | 203, 12.21%, see rank | 13.18% | 10.60% |
Median Rooms | 6.10, see rank | 6.00 | 5.50 |
ACS 2008-2012 data
| 16346 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,606, 100% | 5,563,832 | 131,642,457 |
1 Room | 23, 1.43%, see rank | 1.68% | 1.95% |
2 Rooms | 13, 0.81%, see rank | 1.69% | 2.36% |
3 Rooms | 86, 5.35%, see rank | 7.15% | 8.97% |
4 Rooms | 213, 13.26%, see rank | 12.46% | 16.57% |
5 Rooms | 274, 17.06%, see rank | 16.43% | 20.41% |
6 Rooms | 562, 34.99%, see rank | 21.86% | 18.25% |
7 Rooms | 195, 12.14%, see rank | 14.93% | 12.38% |
8 Rooms | 108, 6.72%, see rank | 10.77% | 8.59% |
9 Rooms or More | 132, 8.22%, see rank | 13.03% | 10.52% |
Median Rooms | 5.80, see rank | 6.00 | 5.50 |
US Census 2000 data
| 16346 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,464, 100% | 5,249,750 | 115,904,641 |
1 Room | 0, 0.00%, see rank | 1.19% | 2.20% |
2 Rooms | 8, 0.55%, see rank | 2.73% | 4.81% |
3 Rooms | 111, 7.58%, see rank | 7.69% | 9.84% |
4 Rooms | 291, 19.88%, see rank | 12.73% | 15.97% |
5 Rooms | 340, 23.22%, see rank | 17.61% | 20.89% |
6 Rooms | 349, 23.84%, see rank | 23.25% | 18.45% |
7 Rooms | 196, 13.39%, see rank | 14.62% | 12.06% |
8 Rooms | 128, 8.74%, see rank | 10.69% | 8.06% |
9 Rooms or More | 41, 2.80%, see rank | 9.49% | 7.70% |
Median Rooms | 5.40, see rank | 5.80 | 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.