29543 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 29543 Zip Code | South Carolina | U.S. |
| Total Housing Units | 206, 100% | 1,795,715 | 116,211,092 |
| Utility Gas | 0, 0.00%, see rank | 23.19% | 48.85% |
| Bottled, Tank, or LP Gas | 21, 10.19%, see rank | 4.45% | 4.86% |
| Electricity | 185, 89.81%, see rank | 69.42% | 36.68% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 1.31% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.12% |
| Wood | 0, 0.00%, see rank | 1.13% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.01% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.11% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| | 29543 Zip Code | South Carolina | U.S. |
| Total Housing Units | 197, 100% | 1,768,255 | 115,226,802 |
| Utility Gas | 9, 4.57%, see rank | 24.20% | 49.42% |
| Bottled, Tank, or LP Gas | 30, 15.23%, see rank | 4.95% | 5.03% |
| Electricity | 158, 80.20%, see rank | 67.56% | 35.51% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 1.75% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
| Wood | 0, 0.00%, see rank | 1.12% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.10% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.30% | 0.90% |
US Census 2000 data
| | 29543 Zip Code | South Carolina | U.S. |
| Total Housing Units | 218, 100% | 1,533,854 | 105,480,101 |
| Utility Gas | 7, 3.21%, see rank | 26.24% | 51.22% |
| Bottled, Tank, or LP Gas | 69, 31.65%, see rank | 8.56% | 6.52% |
| Electricity | 127, 58.26%, see rank | 58.36% | 30.35% |
| Fuel Oil, Kerosene, etc. | 6, 2.75%, see rank | 5.11% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.14% |
| Wood | 8, 3.67%, see rank | 1.26% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
| Other Fuel | 1, 0.46%, see rank | 0.14% | 0.39% |
| No Fuel Used | 0, 0.00%, see rank | 0.29% | 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.
