19973 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 19973 Zip Code | Delaware | U.S. |
Total Housing Units | 8,689, 100% | 339,046 | 116,211,092 |
Utility Gas | 1,338, 15.40%, see rank | 40.46% | 48.85% |
Bottled, Tank, or LP Gas | 1,384, 15.93%, see rank | 10.27% | 4.86% |
Electricity | 3,854, 44.35%, see rank | 31.91% | 36.68% |
Fuel Oil, Kerosene, etc. | 1,815, 20.89%, see rank | 15.26% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
Wood | 162, 1.86%, see rank | 0.98% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.05% |
Other Fuel | 91, 1.05%, see rank | 0.63% | 0.47% |
No Fuel Used | 45, 0.52%, see rank | 0.34% | 1.00% |
ACS 2008-2012 data
| 19973 Zip Code | Delaware | U.S. |
Total Housing Units | 8,140, 100% | 334,076 | 115,226,802 |
Utility Gas | 1,498, 18.40%, see rank | 40.19% | 49.42% |
Bottled, Tank, or LP Gas | 1,150, 14.13%, see rank | 10.90% | 5.03% |
Electricity | 3,229, 39.67%, see rank | 29.95% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,995, 24.51%, see rank | 17.02% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.08% | 0.12% |
Wood | 160, 1.97%, see rank | 1.06% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 72, 0.88%, see rank | 0.51% | 0.43% |
No Fuel Used | 36, 0.44%, see rank | 0.25% | 0.90% |
US Census 2000 data
| 19973 Zip Code | Delaware | U.S. |
Total Housing Units | 8,084, 100% | 298,736 | 105,480,101 |
Utility Gas | 986, 12.20%, see rank | 36.80% | 51.22% |
Bottled, Tank, or LP Gas | 1,354, 16.75%, see rank | 10.29% | 6.52% |
Electricity | 2,715, 33.58%, see rank | 25.59% | 30.35% |
Fuel Oil, Kerosene, etc. | 2,889, 35.74%, see rank | 25.93% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.09% | 0.14% |
Wood | 121, 1.50%, see rank | 0.70% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 0, 0.00%, see rank | 0.38% | 0.39% |
No Fuel Used | 19, 0.24%, see rank | 0.19% | 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.