17857 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 17857 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 3,354, 100% | 4,957,736 | 116,211,092 |
Utility Gas | 1,413, 42.13%, see rank | 51.01% | 48.85% |
Bottled, Tank, or LP Gas | 123, 3.67%, see rank | 3.81% | 4.86% |
Electricity | 876, 26.12%, see rank | 21.18% | 36.68% |
Fuel Oil, Kerosene, etc. | 737, 21.97%, see rank | 18.77% | 5.86% |
Coal or Coke | 108, 3.22%, see rank | 1.37% | 0.12% |
Wood | 70, 2.09%, see rank | 2.87% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 17, 0.51%, see rank | 0.65% | 0.47% |
No Fuel Used | 10, 0.30%, see rank | 0.30% | 1.00% |
ACS 2008-2012 data
| 17857 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 3,363, 100% | 4,959,633 | 115,226,802 |
Utility Gas | 1,277, 37.97%, see rank | 51.16% | 49.42% |
Bottled, Tank, or LP Gas | 86, 2.56%, see rank | 3.64% | 5.03% |
Electricity | 957, 28.46%, see rank | 20.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 818, 24.32%, see rank | 20.21% | 6.46% |
Coal or Coke | 136, 4.04%, see rank | 1.35% | 0.12% |
Wood | 59, 1.75%, see rank | 2.71% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 17, 0.51%, see rank | 0.56% | 0.43% |
No Fuel Used | 13, 0.39%, see rank | 0.24% | 0.90% |
US Census 2000 data
| 17857 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 3,100, 100% | 4,777,003 | 105,480,101 |
Utility Gas | 1,164, 37.55%, see rank | 51.35% | 51.22% |
Bottled, Tank, or LP Gas | 138, 4.45%, see rank | 3.04% | 6.52% |
Electricity | 702, 22.65%, see rank | 16.47% | 30.35% |
Fuel Oil, Kerosene, etc. | 947, 30.55%, see rank | 25.48% | 8.97% |
Coal or Coke | 107, 3.45%, see rank | 1.42% | 0.14% |
Wood | 34, 1.10%, see rank | 1.59% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 8, 0.26%, see rank | 0.43% | 0.39% |
No Fuel Used | 0, 0.00%, 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.