58463 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 58463 Zip Code | North Dakota | U.S. |
| Total Housing Units | 269, 100% | 292,616 | 116,211,092 |
| Utility Gas | 19, 7.06%, see rank | 40.94% | 48.85% |
| Bottled, Tank, or LP Gas | 95, 35.32%, see rank | 13.27% | 4.86% |
| Electricity | 108, 40.15%, see rank | 38.79% | 36.68% |
| Fuel Oil, Kerosene, etc. | 23, 8.55%, see rank | 3.70% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.36% | 0.12% |
| Wood | 2, 0.74%, see rank | 0.57% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.05% |
| Other Fuel | 22, 8.18%, see rank | 1.43% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.91% | 1.00% |
ACS 2008-2012 data
| | 58463 Zip Code | North Dakota | U.S. |
| Total Housing Units | 277, 100% | 282,667 | 115,226,802 |
| Utility Gas | 5, 1.81%, see rank | 41.57% | 49.42% |
| Bottled, Tank, or LP Gas | 88, 31.77%, see rank | 13.65% | 5.03% |
| Electricity | 114, 41.16%, see rank | 37.05% | 35.51% |
| Fuel Oil, Kerosene, etc. | 25, 9.03%, see rank | 4.58% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.37% | 0.12% |
| Wood | 0, 0.00%, see rank | 0.60% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 45, 16.25%, see rank | 1.38% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.78% | 0.90% |
US Census 2000 data
| | 58463 Zip Code | North Dakota | U.S. |
| Total Housing Units | 355, 100% | 257,152 | 105,480,101 |
| Utility Gas | 3, 0.85%, see rank | 43.07% | 51.22% |
| Bottled, Tank, or LP Gas | 180, 50.70%, see rank | 15.71% | 6.52% |
| Electricity | 70, 19.72%, see rank | 28.81% | 30.35% |
| Fuel Oil, Kerosene, etc. | 87, 24.51%, see rank | 9.18% | 8.97% |
| Coal or Coke | 9, 2.54%, see rank | 0.73% | 0.14% |
| Wood | 2, 0.56%, see rank | 0.53% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 4, 1.13%, see rank | 1.29% | 0.39% |
| No Fuel Used | 0, 0.00%, see rank | 0.67% | 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.
