19350 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 19350 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 3,800, 100% | 4,957,736 | 116,211,092 |
Utility Gas | 918, 24.16%, see rank | 51.01% | 48.85% |
Bottled, Tank, or LP Gas | 1,043, 27.45%, see rank | 3.81% | 4.86% |
Electricity | 646, 17.00%, see rank | 21.18% | 36.68% |
Fuel Oil, Kerosene, etc. | 1,047, 27.55%, see rank | 18.77% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 1.37% | 0.12% |
Wood | 72, 1.89%, see rank | 2.87% | 2.12% |
Solar Energy | 6, 0.16%, see rank | 0.03% | 0.05% |
Other Fuel | 45, 1.18%, see rank | 0.65% | 0.47% |
No Fuel Used | 23, 0.61%, see rank | 0.30% | 1.00% |
ACS 2008-2012 data
| 19350 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 3,724, 100% | 4,959,633 | 115,226,802 |
Utility Gas | 800, 21.48%, see rank | 51.16% | 49.42% |
Bottled, Tank, or LP Gas | 1,011, 27.15%, see rank | 3.64% | 5.03% |
Electricity | 772, 20.73%, see rank | 20.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,038, 27.87%, see rank | 20.21% | 6.46% |
Coal or Coke | 5, 0.13%, see rank | 1.35% | 0.12% |
Wood | 47, 1.26%, see rank | 2.71% | 2.08% |
Solar Energy | 11, 0.30%, see rank | 0.02% | 0.04% |
Other Fuel | 33, 0.89%, see rank | 0.56% | 0.43% |
No Fuel Used | 7, 0.19%, see rank | 0.24% | 0.90% |
US Census 2000 data
| 19350 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 3,084, 100% | 4,777,003 | 105,480,101 |
Utility Gas | 643, 20.85%, see rank | 51.35% | 51.22% |
Bottled, Tank, or LP Gas | 770, 24.97%, see rank | 3.04% | 6.52% |
Electricity | 537, 17.41%, see rank | 16.47% | 30.35% |
Fuel Oil, Kerosene, etc. | 1,090, 35.34%, see rank | 25.48% | 8.97% |
Coal or Coke | 2, 0.06%, see rank | 1.42% | 0.14% |
Wood | 25, 0.81%, see rank | 1.59% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 9, 0.29%, see rank | 0.43% | 0.39% |
No Fuel Used | 8, 0.26%, 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.