14860 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 14860 Zip Code | New York | U.S. |
| Total Housing Units | 480, 100% | 7,255,528 | 116,211,092 |
| Utility Gas | 10, 2.08%, see rank | 56.12% | 48.85% |
| Bottled, Tank, or LP Gas | 217, 45.21%, see rank | 3.36% | 4.86% |
| Electricity | 24, 5.00%, see rank | 10.26% | 36.68% |
| Fuel Oil, Kerosene, etc. | 116, 24.17%, see rank | 26.24% | 5.86% |
| Coal or Coke | 50, 10.42%, see rank | 0.26% | 0.12% |
| Wood | 40, 8.33%, see rank | 2.04% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
| Other Fuel | 16, 3.33%, see rank | 0.97% | 0.47% |
| No Fuel Used | 7, 1.46%, see rank | 0.72% | 1.00% |
ACS 2008-2012 data
| | 14860 Zip Code | New York | U.S. |
| Total Housing Units | 467, 100% | 7,230,896 | 115,226,802 |
| Utility Gas | 12, 2.57%, see rank | 54.92% | 49.42% |
| Bottled, Tank, or LP Gas | 206, 44.11%, see rank | 3.16% | 5.03% |
| Electricity | 43, 9.21%, see rank | 9.44% | 35.51% |
| Fuel Oil, Kerosene, etc. | 137, 29.34%, see rank | 28.80% | 6.46% |
| Coal or Coke | 25, 5.35%, see rank | 0.26% | 0.12% |
| Wood | 41, 8.78%, see rank | 1.96% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 3, 0.64%, see rank | 0.86% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.57% | 0.90% |
US Census 2000 data
| | 14860 Zip Code | New York | U.S. |
| Total Housing Units | 434, 100% | 7,056,860 | 105,480,101 |
| Utility Gas | 2, 0.46%, see rank | 51.75% | 51.22% |
| Bottled, Tank, or LP Gas | 121, 27.88%, see rank | 3.37% | 6.52% |
| Electricity | 37, 8.53%, see rank | 8.72% | 30.35% |
| Fuel Oil, Kerosene, etc. | 207, 47.70%, see rank | 33.11% | 8.97% |
| Coal or Coke | 40, 9.22%, see rank | 0.14% | 0.14% |
| Wood | 22, 5.07%, see rank | 1.17% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
| Other Fuel | 2, 0.46%, see rank | 1.04% | 0.39% |
| No Fuel Used | 3, 0.69%, see rank | 0.66% | 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.
