Pleasanton, NM Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | Pleasanton, NM | New Mexico | U.S. |
| Total Housing Units | 34, 100% | 764,684 | 116,211,092 |
| Utility Gas | 4, 11.76%, see rank | 66.93% | 48.85% |
| Bottled, Tank, or LP Gas | 27, 79.41%, see rank | 8.60% | 4.86% |
| Electricity | 0, 0.00%, see rank | 16.11% | 36.68% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 0.13% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.04% | 0.12% |
| Wood | 3, 8.82%, see rank | 6.80% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.26% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.94% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.19% | 1.00% |
ACS 2008-2012 data
| | Pleasanton, NM | New Mexico | U.S. |
| Total Housing Units | 36, 100% | 763,844 | 115,226,802 |
| Utility Gas | 0, 0.00%, see rank | 67.49% | 49.42% |
| Bottled, Tank, or LP Gas | 36, 100.00%, see rank | 9.61% | 5.03% |
| Electricity | 0, 0.00%, see rank | 14.88% | 35.51% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 0.13% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.06% | 0.12% |
| Wood | 0, 0.00%, see rank | 6.62% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.30% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.75% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.17% | 0.90% |
ACS 2006-2010 data
| | Pleasanton, NM | New Mexico | U.S. |
| Total Housing Units | 111, 100% | 756,112 | 114,235,996 |
| Utility Gas | 0, 0.00%, see rank | 67.51% | 49.91% |
| Bottled, Tank, or LP Gas | 89, 80.18%, see rank | 10.76% | 5.38% |
| Electricity | 0, 0.00%, see rank | 13.96% | 34.20% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 0.14% | 7.07% |
| Coal or Coke | 0, 0.00%, see rank | 0.07% | 0.12% |
| Wood | 22, 19.82%, see rank | 6.44% | 1.97% |
| Solar Energy | 0, 0.00%, see rank | 0.33% | 0.03% |
| Other Fuel | 0, 0.00%, see rank | 0.61% | 0.42% |
| No Fuel Used | 0, 0.00%, see rank | 0.17% | 0.90% |
* 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.
