19541 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 19541 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,489, 100% | 4,957,736 | 116,211,092 |
Utility Gas | 126, 8.46%, see rank | 51.01% | 48.85% |
Bottled, Tank, or LP Gas | 168, 11.28%, see rank | 3.81% | 4.86% |
Electricity | 231, 15.51%, see rank | 21.18% | 36.68% |
Fuel Oil, Kerosene, etc. | 684, 45.94%, see rank | 18.77% | 5.86% |
Coal or Coke | 79, 5.31%, see rank | 1.37% | 0.12% |
Wood | 147, 9.87%, see rank | 2.87% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 51, 3.43%, see rank | 0.65% | 0.47% |
No Fuel Used | 3, 0.20%, see rank | 0.30% | 1.00% |
ACS 2008-2012 data
| 19541 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,512, 100% | 4,959,633 | 115,226,802 |
Utility Gas | 186, 12.30%, see rank | 51.16% | 49.42% |
Bottled, Tank, or LP Gas | 200, 13.23%, see rank | 3.64% | 5.03% |
Electricity | 250, 16.53%, see rank | 20.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 574, 37.96%, see rank | 20.21% | 6.46% |
Coal or Coke | 77, 5.09%, see rank | 1.35% | 0.12% |
Wood | 181, 11.97%, see rank | 2.71% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 28, 1.85%, see rank | 0.56% | 0.43% |
No Fuel Used | 16, 1.06%, see rank | 0.24% | 0.90% |
US Census 2000 data
| 19541 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 1,256, 100% | 4,777,003 | 105,480,101 |
Utility Gas | 96, 7.64%, see rank | 51.35% | 51.22% |
Bottled, Tank, or LP Gas | 137, 10.91%, see rank | 3.04% | 6.52% |
Electricity | 216, 17.20%, see rank | 16.47% | 30.35% |
Fuel Oil, Kerosene, etc. | 717, 57.09%, see rank | 25.48% | 8.97% |
Coal or Coke | 65, 5.18%, see rank | 1.42% | 0.14% |
Wood | 25, 1.99%, see rank | 1.59% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 0, 0.00%, 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.