17320 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 17320 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 2,929, 100% | 4,957,736 | 116,211,092 |
Utility Gas | 351, 11.98%, see rank | 51.01% | 48.85% |
Bottled, Tank, or LP Gas | 580, 19.80%, see rank | 3.81% | 4.86% |
Electricity | 1,123, 38.34%, see rank | 21.18% | 36.68% |
Fuel Oil, Kerosene, etc. | 451, 15.40%, see rank | 18.77% | 5.86% |
Coal or Coke | 11, 0.38%, see rank | 1.37% | 0.12% |
Wood | 344, 11.74%, see rank | 2.87% | 2.12% |
Solar Energy | 3, 0.10%, see rank | 0.03% | 0.05% |
Other Fuel | 37, 1.26%, see rank | 0.65% | 0.47% |
No Fuel Used | 29, 0.99%, see rank | 0.30% | 1.00% |
ACS 2008-2012 data
| 17320 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 2,914, 100% | 4,959,633 | 115,226,802 |
Utility Gas | 407, 13.97%, see rank | 51.16% | 49.42% |
Bottled, Tank, or LP Gas | 557, 19.11%, see rank | 3.64% | 5.03% |
Electricity | 1,113, 38.19%, see rank | 20.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 464, 15.92%, see rank | 20.21% | 6.46% |
Coal or Coke | 7, 0.24%, see rank | 1.35% | 0.12% |
Wood | 343, 11.77%, see rank | 2.71% | 2.08% |
Solar Energy | 2, 0.07%, see rank | 0.02% | 0.04% |
Other Fuel | 14, 0.48%, see rank | 0.56% | 0.43% |
No Fuel Used | 7, 0.24%, see rank | 0.24% | 0.90% |
US Census 2000 data
| 17320 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 2,562, 100% | 4,777,003 | 105,480,101 |
Utility Gas | 347, 13.54%, see rank | 51.35% | 51.22% |
Bottled, Tank, or LP Gas | 376, 14.68%, see rank | 3.04% | 6.52% |
Electricity | 969, 37.82%, see rank | 16.47% | 30.35% |
Fuel Oil, Kerosene, etc. | 592, 23.11%, see rank | 25.48% | 8.97% |
Coal or Coke | 37, 1.44%, see rank | 1.42% | 0.14% |
Wood | 220, 8.59%, see rank | 1.59% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 16, 0.62%, see rank | 0.43% | 0.39% |
No Fuel Used | 5, 0.20%, see rank | 0.21% | 0.69% |
* 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.