53590 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 53590 Zip Code | Wisconsin | U.S. |
Total Housing Units | 14,251, 100% | 2,293,250 | 116,211,092 |
Utility Gas | 10,214, 71.67%, see rank | 65.30% | 48.85% |
Bottled, Tank, or LP Gas | 513, 3.60%, see rank | 10.88% | 4.86% |
Electricity | 3,217, 22.57%, see rank | 14.81% | 36.68% |
Fuel Oil, Kerosene, etc. | 92, 0.65%, see rank | 3.02% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 110, 0.77%, see rank | 4.57% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 89, 0.62%, see rank | 0.94% | 0.47% |
No Fuel Used | 16, 0.11%, see rank | 0.44% | 1.00% |
ACS 2008-2012 data
| 53590 Zip Code | Wisconsin | U.S. |
Total Housing Units | 13,886, 100% | 2,286,339 | 115,226,802 |
Utility Gas | 10,016, 72.13%, see rank | 65.77% | 49.42% |
Bottled, Tank, or LP Gas | 557, 4.01%, see rank | 10.80% | 5.03% |
Electricity | 2,904, 20.91%, see rank | 13.95% | 35.51% |
Fuel Oil, Kerosene, etc. | 204, 1.47%, see rank | 3.63% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 85, 0.61%, see rank | 4.56% | 2.08% |
Solar Energy | 6, 0.04%, see rank | 0.02% | 0.04% |
Other Fuel | 50, 0.36%, see rank | 0.89% | 0.43% |
No Fuel Used | 64, 0.46%, see rank | 0.36% | 0.90% |
US Census 2000 data
| 53590 Zip Code | Wisconsin | U.S. |
Total Housing Units | 9,816, 100% | 2,084,544 | 105,480,101 |
Utility Gas | 7,355, 74.93%, see rank | 66.40% | 51.22% |
Bottled, Tank, or LP Gas | 411, 4.19%, see rank | 10.96% | 6.52% |
Electricity | 1,684, 17.16%, see rank | 11.36% | 30.35% |
Fuel Oil, Kerosene, etc. | 257, 2.62%, see rank | 7.60% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.14% |
Wood | 18, 0.18%, see rank | 2.73% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 51, 0.52%, see rank | 0.64% | 0.39% |
No Fuel Used | 40, 0.41%, see rank | 0.27% | 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.