17264 Zip Code Historical Amount of Rooms in a House Data
ACS 2010-2014 data
| 17264 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,282, 100% | 5,578,393 | 132,741,033 |
1 Room | 24, 1.87%, see rank | 1.73% | 1.95% |
2 Rooms | 22, 1.72%, see rank | 1.73% | 2.48% |
3 Rooms | 73, 5.69%, see rank | 7.21% | 9.13% |
4 Rooms | 204, 15.91%, see rank | 12.40% | 16.60% |
5 Rooms | 333, 25.98%, see rank | 16.40% | 20.41% |
6 Rooms | 220, 17.16%, see rank | 21.82% | 18.06% |
7 Rooms | 189, 14.74%, see rank | 14.82% | 12.27% |
8 Rooms | 109, 8.50%, see rank | 10.70% | 8.48% |
9 Rooms or More | 108, 8.42%, see rank | 13.18% | 10.60% |
Median Rooms | 5.50, see rank | 6.00 | 5.50 |
ACS 2008-2012 data
| 17264 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,350, 100% | 5,563,832 | 131,642,457 |
1 Room | 29, 2.15%, see rank | 1.68% | 1.95% |
2 Rooms | 19, 1.41%, see rank | 1.69% | 2.36% |
3 Rooms | 89, 6.59%, see rank | 7.15% | 8.97% |
4 Rooms | 209, 15.48%, see rank | 12.46% | 16.57% |
5 Rooms | 292, 21.63%, see rank | 16.43% | 20.41% |
6 Rooms | 297, 22.00%, see rank | 21.86% | 18.25% |
7 Rooms | 170, 12.59%, see rank | 14.93% | 12.38% |
8 Rooms | 120, 8.89%, see rank | 10.77% | 8.59% |
9 Rooms or More | 125, 9.26%, see rank | 13.03% | 10.52% |
Median Rooms | 5.60, see rank | 6.00 | 5.50 |
US Census 2000 data
| 17264 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,299, 100% | 5,249,750 | 115,904,641 |
1 Room | 17, 1.31%, see rank | 1.19% | 2.20% |
2 Rooms | 29, 2.23%, see rank | 2.73% | 4.81% |
3 Rooms | 77, 5.93%, see rank | 7.69% | 9.84% |
4 Rooms | 200, 15.40%, see rank | 12.73% | 15.97% |
5 Rooms | 367, 28.25%, see rank | 17.61% | 20.89% |
6 Rooms | 275, 21.17%, see rank | 23.25% | 18.45% |
7 Rooms | 149, 11.47%, see rank | 14.62% | 12.06% |
8 Rooms | 108, 8.31%, see rank | 10.69% | 8.06% |
9 Rooms or More | 77, 5.93%, 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.