57201 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 57201 Zip Code | South Dakota | U.S. |
Total Housing Units | 10,651, 100% | 327,101 | 116,211,092 |
Utility Gas | 6,934, 65.10%, see rank | 48.20% | 48.85% |
Bottled, Tank, or LP Gas | 394, 3.70%, see rank | 16.53% | 4.86% |
Electricity | 2,952, 27.72%, see rank | 28.34% | 36.68% |
Fuel Oil, Kerosene, etc. | 72, 0.68%, see rank | 2.70% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.08% | 0.12% |
Wood | 56, 0.53%, see rank | 1.94% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.05% | 0.05% |
Other Fuel | 217, 2.04%, see rank | 1.52% | 0.47% |
No Fuel Used | 26, 0.24%, see rank | 0.63% | 1.00% |
ACS 2008-2012 data
| 57201 Zip Code | South Dakota | U.S. |
Total Housing Units | 10,548, 100% | 320,467 | 115,226,802 |
Utility Gas | 6,845, 64.89%, see rank | 49.23% | 49.42% |
Bottled, Tank, or LP Gas | 405, 3.84%, see rank | 17.01% | 5.03% |
Electricity | 2,993, 28.38%, see rank | 26.60% | 35.51% |
Fuel Oil, Kerosene, etc. | 66, 0.63%, see rank | 3.21% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.08% | 0.12% |
Wood | 56, 0.53%, see rank | 1.94% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 141, 1.34%, see rank | 1.34% | 0.43% |
No Fuel Used | 42, 0.40%, see rank | 0.56% | 0.90% |
US Census 2000 data
| 57201 Zip Code | South Dakota | U.S. |
Total Housing Units | 9,518, 100% | 290,245 | 105,480,101 |
Utility Gas | 6,698, 70.37%, see rank | 48.34% | 51.22% |
Bottled, Tank, or LP Gas | 420, 4.41%, see rank | 21.69% | 6.52% |
Electricity | 2,160, 22.69%, see rank | 19.74% | 30.35% |
Fuel Oil, Kerosene, etc. | 111, 1.17%, see rank | 7.04% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.14% |
Wood | 42, 0.44%, see rank | 1.68% | 1.68% |
Solar Energy | 18, 0.19%, see rank | 0.03% | 0.04% |
Other Fuel | 47, 0.49%, see rank | 0.92% | 0.39% |
No Fuel Used | 22, 0.23%, 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.