27803 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 27803 Zip Code | North Carolina | U.S. |
Total Housing Units | 8,179, 100% | 3,742,514 | 116,211,092 |
Utility Gas | 3,038, 37.14%, see rank | 24.68% | 48.85% |
Bottled, Tank, or LP Gas | 1,003, 12.26%, see rank | 8.00% | 4.86% |
Electricity | 3,939, 48.16%, see rank | 60.27% | 36.68% |
Fuel Oil, Kerosene, etc. | 122, 1.49%, see rank | 4.34% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 20, 0.24%, see rank | 2.17% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 0, 0.00%, see rank | 0.15% | 0.47% |
No Fuel Used | 57, 0.70%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 27803 Zip Code | North Carolina | U.S. |
Total Housing Units | 8,692, 100% | 3,693,221 | 115,226,802 |
Utility Gas | 3,314, 38.13%, see rank | 24.97% | 49.42% |
Bottled, Tank, or LP Gas | 957, 11.01%, see rank | 8.90% | 5.03% |
Electricity | 4,126, 47.47%, see rank | 58.26% | 35.51% |
Fuel Oil, Kerosene, etc. | 209, 2.40%, see rank | 5.24% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 57, 0.66%, 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 | 29, 0.33%, see rank | 0.29% | 0.90% |
US Census 2000 data
| 27803 Zip Code | North Carolina | U.S. |
Total Housing Units | 8,369, 100% | 3,132,013 | 105,480,101 |
Utility Gas | 3,871, 46.25%, see rank | 24.19% | 51.22% |
Bottled, Tank, or LP Gas | 1,199, 14.33%, see rank | 12.59% | 6.52% |
Electricity | 2,892, 34.56%, see rank | 48.81% | 30.35% |
Fuel Oil, Kerosene, etc. | 326, 3.90%, see rank | 11.76% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.14% |
Wood | 72, 0.86%, see rank | 2.10% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 0, 0.00%, see rank | 0.21% | 0.39% |
No Fuel Used | 9, 0.11%, 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.