30336 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 30336 Zip Code | Georgia | U.S. |
| Total Housing Units | 181, 100% | 3,540,690 | 116,211,092 |
| Utility Gas | 0, 0.00%, see rank | 40.63% | 48.85% |
| Bottled, Tank, or LP Gas | 0, 0.00%, see rank | 5.27% | 4.86% |
| Electricity | 181, 100.00%, see rank | 52.46% | 36.68% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 0.22% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
| Wood | 0, 0.00%, see rank | 0.99% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.01% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.08% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.32% | 1.00% |
ACS 2008-2012 data
| | 30336 Zip Code | Georgia | U.S. |
| Total Housing Units | 202, 100% | 3,508,477 | 115,226,802 |
| Utility Gas | 0, 0.00%, see rank | 41.92% | 49.42% |
| Bottled, Tank, or LP Gas | 0, 0.00%, see rank | 5.83% | 5.03% |
| Electricity | 202, 100.00%, see rank | 50.64% | 35.51% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 0.26% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.00% | 0.12% |
| Wood | 0, 0.00%, see rank | 0.99% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.08% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.26% | 0.90% |
US Census 2000 data
| | 30336 Zip Code | Georgia | U.S. |
| Total Housing Units | 46, 100% | 3,006,369 | 105,480,101 |
| Utility Gas | 34, 73.91%, see rank | 48.92% | 51.22% |
| Bottled, Tank, or LP Gas | 5, 10.87%, see rank | 10.78% | 6.52% |
| Electricity | 0, 0.00%, see rank | 38.30% | 30.35% |
| Fuel Oil, Kerosene, etc. | 7, 15.22%, see rank | 0.62% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.14% |
| Wood | 0, 0.00%, see rank | 0.97% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.08% | 0.39% |
| No Fuel Used | 0, 0.00%, see rank | 0.30% | 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.
