57450 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 57450 Zip Code | South Dakota | U.S. |
| Total Housing Units | 284, 100% | 327,101 | 116,211,092 |
| Utility Gas | 3, 1.06%, see rank | 48.20% | 48.85% |
| Bottled, Tank, or LP Gas | 95, 33.45%, see rank | 16.53% | 4.86% |
| Electricity | 104, 36.62%, see rank | 28.34% | 36.68% |
| Fuel Oil, Kerosene, etc. | 55, 19.37%, see rank | 2.70% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.08% | 0.12% |
| Wood | 9, 3.17%, see rank | 1.94% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.05% | 0.05% |
| Other Fuel | 9, 3.17%, see rank | 1.52% | 0.47% |
| No Fuel Used | 9, 3.17%, see rank | 0.63% | 1.00% |
ACS 2008-2012 data
| | 57450 Zip Code | South Dakota | U.S. |
| Total Housing Units | 277, 100% | 320,467 | 115,226,802 |
| Utility Gas | 5, 1.81%, see rank | 49.23% | 49.42% |
| Bottled, Tank, or LP Gas | 102, 36.82%, see rank | 17.01% | 5.03% |
| Electricity | 79, 28.52%, see rank | 26.60% | 35.51% |
| Fuel Oil, Kerosene, etc. | 68, 24.55%, see rank | 3.21% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.08% | 0.12% |
| Wood | 5, 1.81%, see rank | 1.94% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
| Other Fuel | 12, 4.33%, see rank | 1.34% | 0.43% |
| No Fuel Used | 6, 2.17%, see rank | 0.56% | 0.90% |
US Census 2000 data
| | 57450 Zip Code | South Dakota | U.S. |
| Total Housing Units | 360, 100% | 290,245 | 105,480,101 |
| Utility Gas | 2, 0.56%, see rank | 48.34% | 51.22% |
| Bottled, Tank, or LP Gas | 108, 30.00%, see rank | 21.69% | 6.52% |
| Electricity | 76, 21.11%, see rank | 19.74% | 30.35% |
| Fuel Oil, Kerosene, etc. | 165, 45.83%, see rank | 7.04% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.14% |
| Wood | 0, 0.00%, see rank | 1.68% | 1.68% |
| Solar Energy | 5, 1.39%, see rank | 0.03% | 0.04% |
| Other Fuel | 2, 0.56%, see rank | 0.92% | 0.39% |
| No Fuel Used | 2, 0.56%, see rank | 0.43% | 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.
