59033 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 59033 Zip Code | Montana | U.S. |
| Total Housing Units | 105, 100% | 407,797 | 116,211,092 |
| Utility Gas | 50, 47.62%, see rank | 54.68% | 48.85% |
| Bottled, Tank, or LP Gas | 8, 7.62%, see rank | 12.11% | 4.86% |
| Electricity | 12, 11.43%, see rank | 21.42% | 36.68% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 1.30% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.18% | 0.12% |
| Wood | 33, 31.43%, see rank | 8.78% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.07% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 1.17% | 0.47% |
| No Fuel Used | 2, 1.90%, see rank | 0.30% | 1.00% |
ACS 2008-2012 data
| | 59033 Zip Code | Montana | U.S. |
| Total Housing Units | 92, 100% | 405,508 | 115,226,802 |
| Utility Gas | 44, 47.83%, see rank | 55.51% | 49.42% |
| Bottled, Tank, or LP Gas | 7, 7.61%, see rank | 12.38% | 5.03% |
| Electricity | 4, 4.35%, see rank | 20.16% | 35.51% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 1.64% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.21% | 0.12% |
| Wood | 33, 35.87%, see rank | 8.69% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.05% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 1.11% | 0.43% |
| No Fuel Used | 4, 4.35%, see rank | 0.25% | 0.90% |
US Census 2000 data
| | 59033 Zip Code | Montana | U.S. |
| Total Housing Units | 40, 100% | 358,667 | 105,480,101 |
| Utility Gas | 28, 70.00%, see rank | 59.09% | 51.22% |
| Bottled, Tank, or LP Gas | 5, 12.50%, see rank | 12.66% | 6.52% |
| Electricity | 2, 5.00%, see rank | 16.06% | 30.35% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 3.11% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.34% | 0.14% |
| Wood | 5, 12.50%, see rank | 7.54% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.05% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.95% | 0.39% |
| No Fuel Used | 0, 0.00%, see rank | 0.21% | 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.
