11368 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 11368 Zip Code | New York | U.S. |
Total Housing Units | 29,031, 100% | 7,255,528 | 116,211,092 |
Utility Gas | 17,447, 60.10%, see rank | 56.12% | 48.85% |
Bottled, Tank, or LP Gas | 424, 1.46%, see rank | 3.36% | 4.86% |
Electricity | 3,687, 12.70%, see rank | 10.26% | 36.68% |
Fuel Oil, Kerosene, etc. | 7,152, 24.64%, 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 | 148, 0.51%, see rank | 0.97% | 0.47% |
No Fuel Used | 173, 0.60%, see rank | 0.72% | 1.00% |
ACS 2008-2012 data
| 11368 Zip Code | New York | U.S. |
Total Housing Units | 27,854, 100% | 7,230,896 | 115,226,802 |
Utility Gas | 17,295, 62.09%, see rank | 54.92% | 49.42% |
Bottled, Tank, or LP Gas | 399, 1.43%, see rank | 3.16% | 5.03% |
Electricity | 3,749, 13.46%, see rank | 9.44% | 35.51% |
Fuel Oil, Kerosene, etc. | 6,132, 22.01%, 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 | 104, 0.37%, see rank | 0.86% | 0.43% |
No Fuel Used | 175, 0.63%, see rank | 0.57% | 0.90% |
US Census 2000 data
| 11368 Zip Code | New York | U.S. |
Total Housing Units | 27,603, 100% | 7,056,860 | 105,480,101 |
Utility Gas | 14,973, 54.24%, see rank | 51.75% | 51.22% |
Bottled, Tank, or LP Gas | 1,631, 5.91%, see rank | 3.37% | 6.52% |
Electricity | 4,509, 16.34%, see rank | 8.72% | 30.35% |
Fuel Oil, Kerosene, etc. | 5,739, 20.79%, see rank | 33.11% | 8.97% |
Coal or Coke | 14, 0.05%, 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 | 330, 1.20%, see rank | 1.04% | 0.39% |
No Fuel Used | 407, 1.47%, 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.