17502 Zip Code Historical Amount of Rooms in a House Data
ACS 2010-2014 data
| 17502 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,058, 100% | 5,578,393 | 132,741,033 |
1 Room | 0, 0.00%, see rank | 1.73% | 1.95% |
2 Rooms | 0, 0.00%, see rank | 1.73% | 2.48% |
3 Rooms | 9, 0.85%, see rank | 7.21% | 9.13% |
4 Rooms | 73, 6.90%, see rank | 12.40% | 16.60% |
5 Rooms | 241, 22.78%, see rank | 16.40% | 20.41% |
6 Rooms | 244, 23.06%, see rank | 21.82% | 18.06% |
7 Rooms | 212, 20.04%, see rank | 14.82% | 12.27% |
8 Rooms | 155, 14.65%, see rank | 10.70% | 8.48% |
9 Rooms or More | 124, 11.72%, see rank | 13.18% | 10.60% |
Median Rooms | 6.30, see rank | 6.00 | 5.50 |
ACS 2008-2012 data
| 17502 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,113, 100% | 5,563,832 | 131,642,457 |
1 Room | 0, 0.00%, see rank | 1.68% | 1.95% |
2 Rooms | 0, 0.00%, see rank | 1.69% | 2.36% |
3 Rooms | 29, 2.61%, see rank | 7.15% | 8.97% |
4 Rooms | 80, 7.19%, see rank | 12.46% | 16.57% |
5 Rooms | 288, 25.88%, see rank | 16.43% | 20.41% |
6 Rooms | 259, 23.27%, see rank | 21.86% | 18.25% |
7 Rooms | 152, 13.66%, see rank | 14.93% | 12.38% |
8 Rooms | 149, 13.39%, see rank | 10.77% | 8.59% |
9 Rooms or More | 156, 14.02%, see rank | 13.03% | 10.52% |
Median Rooms | 6.10, see rank | 6.00 | 5.50 |
US Census 2000 data
| 17502 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 901, 100% | 5,249,750 | 115,904,641 |
1 Room | 4, 0.44%, see rank | 1.19% | 2.20% |
2 Rooms | 4, 0.44%, see rank | 2.73% | 4.81% |
3 Rooms | 16, 1.78%, see rank | 7.69% | 9.84% |
4 Rooms | 110, 12.21%, see rank | 12.73% | 15.97% |
5 Rooms | 178, 19.76%, see rank | 17.61% | 20.89% |
6 Rooms | 266, 29.52%, see rank | 23.25% | 18.45% |
7 Rooms | 142, 15.76%, see rank | 14.62% | 12.06% |
8 Rooms | 90, 9.99%, see rank | 10.69% | 8.06% |
9 Rooms or More | 91, 10.10%, see rank | 9.49% | 7.70% |
Median Rooms | 6.00, 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.