29630 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 29630 Zip Code | South Carolina | U.S. |
Total Housing Units | 5,726, 100% | 1,795,715 | 116,211,092 |
Utility Gas | 1,115, 19.47%, see rank | 23.19% | 48.85% |
Bottled, Tank, or LP Gas | 325, 5.68%, see rank | 4.45% | 4.86% |
Electricity | 4,117, 71.90%, see rank | 69.42% | 36.68% |
Fuel Oil, Kerosene, etc. | 70, 1.22%, see rank | 1.31% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.12% |
Wood | 80, 1.40%, see rank | 1.13% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.05% |
Other Fuel | 5, 0.09%, see rank | 0.11% | 0.47% |
No Fuel Used | 14, 0.24%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 29630 Zip Code | South Carolina | U.S. |
Total Housing Units | 5,777, 100% | 1,768,255 | 115,226,802 |
Utility Gas | 1,194, 20.67%, see rank | 24.20% | 49.42% |
Bottled, Tank, or LP Gas | 301, 5.21%, see rank | 4.95% | 5.03% |
Electricity | 4,049, 70.09%, see rank | 67.56% | 35.51% |
Fuel Oil, Kerosene, etc. | 95, 1.64%, see rank | 1.75% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 130, 2.25%, see rank | 1.12% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 4, 0.07%, see rank | 0.10% | 0.43% |
No Fuel Used | 4, 0.07%, see rank | 0.30% | 0.90% |
US Census 2000 data
| 29630 Zip Code | South Carolina | U.S. |
Total Housing Units | 4,832, 100% | 1,533,854 | 105,480,101 |
Utility Gas | 1,143, 23.65%, see rank | 26.24% | 51.22% |
Bottled, Tank, or LP Gas | 281, 5.82%, see rank | 8.56% | 6.52% |
Electricity | 3,020, 62.50%, see rank | 58.36% | 30.35% |
Fuel Oil, Kerosene, etc. | 205, 4.24%, see rank | 5.11% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.14% |
Wood | 167, 3.46%, see rank | 1.26% | 1.68% |
Solar Energy | 2, 0.04%, see rank | 0.03% | 0.04% |
Other Fuel | 3, 0.06%, see rank | 0.14% | 0.39% |
No Fuel Used | 11, 0.23%, 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.