Niskayuna, NY Historical Type of Heating Fuel in a House Data
ACS 2006-2010 data
| | Niskayuna, NY | New York | U.S. |
| Total Housing Units | 1,764, 100% | 7,205,740 | 114,235,996 |
| Utility Gas | 1,521, 86.22%, see rank | 53.35% | 49.91% |
| Bottled, Tank, or LP Gas | 14, 0.79%, see rank | 3.13% | 5.38% |
| Electricity | 45, 2.55%, see rank | 8.86% | 34.20% |
| Fuel Oil, Kerosene, etc. | 162, 9.18%, see rank | 31.29% | 7.07% |
| Coal or Coke | 0, 0.00%, see rank | 0.25% | 0.12% |
| Wood | 22, 1.25%, see rank | 1.76% | 1.97% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.03% |
| Other Fuel | 0, 0.00%, see rank | 0.82% | 0.42% |
| No Fuel Used | 0, 0.00%, see rank | 0.52% | 0.90% |
ACS 2005-2009 data
| | Niskayuna, NY | New York | U.S. |
| Total Housing Units | 1,843, 100% | 7,137,013 | 112,611,029 |
| Utility Gas | 1,560, 84.64%, see rank | 52.57% | 50.14% |
| Bottled, Tank, or LP Gas | 14, 0.76%, see rank | 3.14% | 5.58% |
| Electricity | 44, 2.39%, see rank | 8.64% | 33.56% |
| Fuel Oil, Kerosene, etc. | 203, 11.01%, see rank | 32.47% | 7.38% |
| Coal or Coke | 0, 0.00%, see rank | 0.22% | 0.12% |
| Wood | 22, 1.19%, see rank | 1.64% | 1.89% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.03% |
| Other Fuel | 0, 0.00%, see rank | 0.80% | 0.42% |
| No Fuel Used | 0, 0.00%, see rank | 0.51% | 0.88% |
US Census 2000 data
| | Niskayuna, NY | New York | U.S. |
| Total Housing Units | 1,919, 100% | 7,056,860 | 105,480,101 |
| Utility Gas | 1,671, 87.08%, see rank | 51.75% | 51.22% |
| Bottled, Tank, or LP Gas | 0, 0.00%, see rank | 3.37% | 6.52% |
| Electricity | 25, 1.30%, see rank | 8.72% | 30.35% |
| Fuel Oil, Kerosene, etc. | 223, 11.62%, 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 | 0, 0.00%, see rank | 1.04% | 0.39% |
| No Fuel Used | 0, 0.00%, 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.
