11365 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 11365 Zip Code | New York | U.S. |
Total Housing Units | 15,382, 100% | 7,255,528 | 116,211,092 |
Utility Gas | 9,588, 62.33%, see rank | 56.12% | 48.85% |
Bottled, Tank, or LP Gas | 437, 2.84%, see rank | 3.36% | 4.86% |
Electricity | 1,662, 10.80%, see rank | 10.26% | 36.68% |
Fuel Oil, Kerosene, etc. | 3,438, 22.35%, see rank | 26.24% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.26% | 0.12% |
Wood | 0, 0.00%, see rank | 2.04% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 118, 0.77%, see rank | 0.97% | 0.47% |
No Fuel Used | 139, 0.90%, see rank | 0.72% | 1.00% |
ACS 2008-2012 data
| 11365 Zip Code | New York | U.S. |
Total Housing Units | 15,241, 100% | 7,230,896 | 115,226,802 |
Utility Gas | 9,215, 60.46%, see rank | 54.92% | 49.42% |
Bottled, Tank, or LP Gas | 339, 2.22%, see rank | 3.16% | 5.03% |
Electricity | 1,713, 11.24%, see rank | 9.44% | 35.51% |
Fuel Oil, Kerosene, etc. | 3,747, 24.59%, see rank | 28.80% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.26% | 0.12% |
Wood | 0, 0.00%, see rank | 1.96% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 113, 0.74%, see rank | 0.86% | 0.43% |
No Fuel Used | 114, 0.75%, see rank | 0.57% | 0.90% |
US Census 2000 data
| 11365 Zip Code | New York | U.S. |
Total Housing Units | 15,944, 100% | 7,056,860 | 105,480,101 |
Utility Gas | 8,414, 52.77%, see rank | 51.75% | 51.22% |
Bottled, Tank, or LP Gas | 229, 1.44%, see rank | 3.37% | 6.52% |
Electricity | 1,122, 7.04%, see rank | 8.72% | 30.35% |
Fuel Oil, Kerosene, etc. | 5,769, 36.18%, see rank | 33.11% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.14% | 0.14% |
Wood | 0, 0.00%, see rank | 1.17% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 138, 0.87%, see rank | 1.04% | 0.39% |
No Fuel Used | 272, 1.71%, 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.