28463 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 28463 Zip Code | North Carolina | U.S. |
Total Housing Units | 3,703, 100% | 3,742,514 | 116,211,092 |
Utility Gas | 31, 0.84%, see rank | 24.68% | 48.85% |
Bottled, Tank, or LP Gas | 1,071, 28.92%, see rank | 8.00% | 4.86% |
Electricity | 2,369, 63.98%, see rank | 60.27% | 36.68% |
Fuel Oil, Kerosene, etc. | 127, 3.43%, see rank | 4.34% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 18, 0.49%, see rank | 2.17% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 26, 0.70%, see rank | 0.15% | 0.47% |
No Fuel Used | 61, 1.65%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 28463 Zip Code | North Carolina | U.S. |
Total Housing Units | 3,754, 100% | 3,693,221 | 115,226,802 |
Utility Gas | 67, 1.78%, see rank | 24.97% | 49.42% |
Bottled, Tank, or LP Gas | 1,251, 33.32%, see rank | 8.90% | 5.03% |
Electricity | 2,278, 60.68%, see rank | 58.26% | 35.51% |
Fuel Oil, Kerosene, etc. | 95, 2.53%, see rank | 5.24% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 19, 0.51%, see rank | 2.16% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 0, 0.00%, see rank | 0.14% | 0.43% |
No Fuel Used | 44, 1.17%, see rank | 0.29% | 0.90% |
US Census 2000 data
| 28463 Zip Code | North Carolina | U.S. |
Total Housing Units | 3,042, 100% | 3,132,013 | 105,480,101 |
Utility Gas | 59, 1.94%, see rank | 24.19% | 51.22% |
Bottled, Tank, or LP Gas | 1,293, 42.50%, see rank | 12.59% | 6.52% |
Electricity | 1,366, 44.90%, see rank | 48.81% | 30.35% |
Fuel Oil, Kerosene, etc. | 270, 8.88%, see rank | 11.76% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.14% |
Wood | 47, 1.55%, see rank | 2.10% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 5, 0.16%, see rank | 0.21% | 0.39% |
No Fuel Used | 2, 0.07%, see rank | 0.28% | 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.