34285 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 34285 Zip Code | Florida | U.S. |
| Total Housing Units | 9,883, 100% | 7,217,508 | 116,211,092 |
| Utility Gas | 208, 2.10%, see rank | 4.53% | 48.85% |
| Bottled, Tank, or LP Gas | 39, 0.39%, see rank | 1.12% | 4.86% |
| Electricity | 9,523, 96.36%, see rank | 92.30% | 36.68% |
| Fuel Oil, Kerosene, etc. | 8, 0.08%, see rank | 0.22% | 5.86% |
| Coal or Coke | 8, 0.08%, see rank | 0.01% | 0.12% |
| Wood | 6, 0.06%, see rank | 0.20% | 2.12% |
| Solar Energy | 15, 0.15%, see rank | 0.03% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.04% | 0.47% |
| No Fuel Used | 76, 0.77%, see rank | 1.56% | 1.00% |
ACS 2008-2012 data
| | 34285 Zip Code | Florida | U.S. |
| Total Housing Units | 9,524, 100% | 7,147,013 | 115,226,802 |
| Utility Gas | 165, 1.73%, see rank | 4.57% | 49.42% |
| Bottled, Tank, or LP Gas | 62, 0.65%, see rank | 1.27% | 5.03% |
| Electricity | 9,169, 96.27%, see rank | 92.17% | 35.51% |
| Fuel Oil, Kerosene, etc. | 18, 0.19%, see rank | 0.27% | 6.46% |
| Coal or Coke | 3, 0.03%, see rank | 0.00% | 0.12% |
| Wood | 10, 0.10%, see rank | 0.21% | 2.08% |
| Solar Energy | 20, 0.21%, see rank | 0.02% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.04% | 0.43% |
| No Fuel Used | 77, 0.81%, see rank | 1.44% | 0.90% |
US Census 2000 data
| | 34285 Zip Code | Florida | U.S. |
| Total Housing Units | 4,518, 100% | 6,337,929 | 105,480,101 |
| Utility Gas | 121, 2.68%, see rank | 5.95% | 51.22% |
| Bottled, Tank, or LP Gas | 85, 1.88%, see rank | 3.57% | 6.52% |
| Electricity | 4,229, 93.60%, see rank | 87.22% | 30.35% |
| Fuel Oil, Kerosene, etc. | 68, 1.51%, see rank | 1.11% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.00% | 0.14% |
| Wood | 0, 0.00%, see rank | 0.26% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.07% | 0.39% |
| No Fuel Used | 15, 0.33%, see rank | 1.76% | 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.
