17353 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 17353 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,268, 100% | 4,957,736 | 116,211,092 |
Utility Gas | 170, 13.41%, see rank | 51.01% | 48.85% |
Bottled, Tank, or LP Gas | 252, 19.87%, see rank | 3.81% | 4.86% |
Electricity | 255, 20.11%, see rank | 21.18% | 36.68% |
Fuel Oil, Kerosene, etc. | 355, 28.00%, see rank | 18.77% | 5.86% |
Coal or Coke | 30, 2.37%, see rank | 1.37% | 0.12% |
Wood | 190, 14.98%, see rank | 2.87% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 16, 1.26%, see rank | 0.65% | 0.47% |
No Fuel Used | 0, 0.00%, see rank | 0.30% | 1.00% |
ACS 2008-2012 data
| 17353 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,152, 100% | 4,959,633 | 115,226,802 |
Utility Gas | 239, 20.75%, see rank | 51.16% | 49.42% |
Bottled, Tank, or LP Gas | 260, 22.57%, see rank | 3.64% | 5.03% |
Electricity | 159, 13.80%, see rank | 20.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 284, 24.65%, see rank | 20.21% | 6.46% |
Coal or Coke | 45, 3.91%, see rank | 1.35% | 0.12% |
Wood | 143, 12.41%, see rank | 2.71% | 2.08% |
Solar Energy | 6, 0.52%, see rank | 0.02% | 0.04% |
Other Fuel | 16, 1.39%, see rank | 0.56% | 0.43% |
No Fuel Used | 0, 0.00%, see rank | 0.24% | 0.90% |
US Census 2000 data
| 17353 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,167, 100% | 4,777,003 | 105,480,101 |
Utility Gas | 222, 19.02%, see rank | 51.35% | 51.22% |
Bottled, Tank, or LP Gas | 173, 14.82%, see rank | 3.04% | 6.52% |
Electricity | 235, 20.14%, see rank | 16.47% | 30.35% |
Fuel Oil, Kerosene, etc. | 366, 31.36%, see rank | 25.48% | 8.97% |
Coal or Coke | 31, 2.66%, see rank | 1.42% | 0.14% |
Wood | 136, 11.65%, see rank | 1.59% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 4, 0.34%, 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.