12601 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 12601 Zip Code | New York | U.S. |
Total Housing Units | 15,323, 100% | 7,255,528 | 116,211,092 |
Utility Gas | 6,486, 42.33%, see rank | 56.12% | 48.85% |
Bottled, Tank, or LP Gas | 456, 2.98%, see rank | 3.36% | 4.86% |
Electricity | 3,588, 23.42%, see rank | 10.26% | 36.68% |
Fuel Oil, Kerosene, etc. | 4,411, 28.79%, see rank | 26.24% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.26% | 0.12% |
Wood | 197, 1.29%, see rank | 2.04% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 89, 0.58%, see rank | 0.97% | 0.47% |
No Fuel Used | 96, 0.63%, see rank | 0.72% | 1.00% |
ACS 2008-2012 data
| 12601 Zip Code | New York | U.S. |
Total Housing Units | 16,060, 100% | 7,230,896 | 115,226,802 |
Utility Gas | 7,157, 44.56%, see rank | 54.92% | 49.42% |
Bottled, Tank, or LP Gas | 389, 2.42%, see rank | 3.16% | 5.03% |
Electricity | 2,981, 18.56%, see rank | 9.44% | 35.51% |
Fuel Oil, Kerosene, etc. | 5,116, 31.86%, see rank | 28.80% | 6.46% |
Coal or Coke | 15, 0.09%, see rank | 0.26% | 0.12% |
Wood | 188, 1.17%, see rank | 1.96% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 129, 0.80%, see rank | 0.86% | 0.43% |
No Fuel Used | 85, 0.53%, see rank | 0.57% | 0.90% |
US Census 2000 data
| 12601 Zip Code | New York | U.S. |
Total Housing Units | 15,274, 100% | 7,056,860 | 105,480,101 |
Utility Gas | 5,893, 38.58%, see rank | 51.75% | 51.22% |
Bottled, Tank, or LP Gas | 416, 2.72%, see rank | 3.37% | 6.52% |
Electricity | 2,620, 17.15%, see rank | 8.72% | 30.35% |
Fuel Oil, Kerosene, etc. | 6,122, 40.08%, see rank | 33.11% | 8.97% |
Coal or Coke | 31, 0.20%, see rank | 0.14% | 0.14% |
Wood | 47, 0.31%, see rank | 1.17% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 109, 0.71%, see rank | 1.04% | 0.39% |
No Fuel Used | 36, 0.24%, 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.