54915 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 54915 Zip Code | Wisconsin | U.S. |
Total Housing Units | 16,029, 100% | 2,293,250 | 116,211,092 |
Utility Gas | 12,921, 80.61%, see rank | 65.30% | 48.85% |
Bottled, Tank, or LP Gas | 229, 1.43%, see rank | 10.88% | 4.86% |
Electricity | 2,093, 13.06%, see rank | 14.81% | 36.68% |
Fuel Oil, Kerosene, etc. | 202, 1.26%, see rank | 3.02% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 288, 1.80%, see rank | 4.57% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 192, 1.20%, see rank | 0.94% | 0.47% |
No Fuel Used | 104, 0.65%, see rank | 0.44% | 1.00% |
ACS 2008-2012 data
| 54915 Zip Code | Wisconsin | U.S. |
Total Housing Units | 15,450, 100% | 2,286,339 | 115,226,802 |
Utility Gas | 12,653, 81.90%, see rank | 65.77% | 49.42% |
Bottled, Tank, or LP Gas | 170, 1.10%, see rank | 10.80% | 5.03% |
Electricity | 1,930, 12.49%, see rank | 13.95% | 35.51% |
Fuel Oil, Kerosene, etc. | 232, 1.50%, see rank | 3.63% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 294, 1.90%, see rank | 4.56% | 2.08% |
Solar Energy | 12, 0.08%, see rank | 0.02% | 0.04% |
Other Fuel | 139, 0.90%, see rank | 0.89% | 0.43% |
No Fuel Used | 20, 0.13%, see rank | 0.36% | 0.90% |
US Census 2000 data
| 54915 Zip Code | Wisconsin | U.S. |
Total Housing Units | 14,042, 100% | 2,084,544 | 105,480,101 |
Utility Gas | 11,483, 81.78%, see rank | 66.40% | 51.22% |
Bottled, Tank, or LP Gas | 151, 1.08%, see rank | 10.96% | 6.52% |
Electricity | 1,574, 11.21%, see rank | 11.36% | 30.35% |
Fuel Oil, Kerosene, etc. | 599, 4.27%, see rank | 7.60% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.14% |
Wood | 6, 0.04%, see rank | 2.73% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 171, 1.22%, see rank | 0.64% | 0.39% |
No Fuel Used | 58, 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.