27401 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 27401 Zip Code | North Carolina | U.S. |
Total Housing Units | 7,562, 100% | 3,742,514 | 116,211,092 |
Utility Gas | 3,238, 42.82%, see rank | 24.68% | 48.85% |
Bottled, Tank, or LP Gas | 93, 1.23%, see rank | 8.00% | 4.86% |
Electricity | 4,008, 53.00%, see rank | 60.27% | 36.68% |
Fuel Oil, Kerosene, etc. | 189, 2.50%, see rank | 4.34% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 18, 0.24%, see rank | 2.17% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 6, 0.08%, see rank | 0.15% | 0.47% |
No Fuel Used | 10, 0.13%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 27401 Zip Code | North Carolina | U.S. |
Total Housing Units | 7,793, 100% | 3,693,221 | 115,226,802 |
Utility Gas | 3,413, 43.80%, see rank | 24.97% | 49.42% |
Bottled, Tank, or LP Gas | 54, 0.69%, see rank | 8.90% | 5.03% |
Electricity | 4,057, 52.06%, see rank | 58.26% | 35.51% |
Fuel Oil, Kerosene, etc. | 221, 2.84%, see rank | 5.24% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 17, 0.22%, 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 | 31, 0.40%, see rank | 0.29% | 0.90% |
US Census 2000 data
| 27401 Zip Code | North Carolina | U.S. |
Total Housing Units | 7,415, 100% | 3,132,013 | 105,480,101 |
Utility Gas | 4,272, 57.61%, see rank | 24.19% | 51.22% |
Bottled, Tank, or LP Gas | 165, 2.23%, see rank | 12.59% | 6.52% |
Electricity | 2,505, 33.78%, see rank | 48.81% | 30.35% |
Fuel Oil, Kerosene, etc. | 385, 5.19%, see rank | 11.76% | 8.97% |
Coal or Coke | 6, 0.08%, see rank | 0.01% | 0.14% |
Wood | 16, 0.22%, see rank | 2.10% | 1.68% |
Solar Energy | 7, 0.09%, see rank | 0.04% | 0.04% |
Other Fuel | 53, 0.71%, see rank | 0.21% | 0.39% |
No Fuel Used | 6, 0.08%, 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.