53066 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 53066 Zip Code | Wisconsin | U.S. |
Total Housing Units | 13,043, 100% | 2,293,250 | 116,211,092 |
Utility Gas | 10,483, 80.37%, see rank | 65.30% | 48.85% |
Bottled, Tank, or LP Gas | 617, 4.73%, see rank | 10.88% | 4.86% |
Electricity | 1,289, 9.88%, see rank | 14.81% | 36.68% |
Fuel Oil, Kerosene, etc. | 274, 2.10%, see rank | 3.02% | 5.86% |
Coal or Coke | 11, 0.08%, see rank | 0.01% | 0.12% |
Wood | 232, 1.78%, see rank | 4.57% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 94, 0.72%, see rank | 0.94% | 0.47% |
No Fuel Used | 43, 0.33%, see rank | 0.44% | 1.00% |
ACS 2008-2012 data
| 53066 Zip Code | Wisconsin | U.S. |
Total Housing Units | 13,012, 100% | 2,286,339 | 115,226,802 |
Utility Gas | 10,180, 78.24%, see rank | 65.77% | 49.42% |
Bottled, Tank, or LP Gas | 592, 4.55%, see rank | 10.80% | 5.03% |
Electricity | 1,330, 10.22%, see rank | 13.95% | 35.51% |
Fuel Oil, Kerosene, etc. | 539, 4.14%, see rank | 3.63% | 6.46% |
Coal or Coke | 9, 0.07%, see rank | 0.01% | 0.12% |
Wood | 255, 1.96%, see rank | 4.56% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 69, 0.53%, see rank | 0.89% | 0.43% |
No Fuel Used | 38, 0.29%, see rank | 0.36% | 0.90% |
US Census 2000 data
| 53066 Zip Code | Wisconsin | U.S. |
Total Housing Units | 10,534, 100% | 2,084,544 | 105,480,101 |
Utility Gas | 8,135, 77.23%, see rank | 66.40% | 51.22% |
Bottled, Tank, or LP Gas | 431, 4.09%, see rank | 10.96% | 6.52% |
Electricity | 996, 9.46%, see rank | 11.36% | 30.35% |
Fuel Oil, Kerosene, etc. | 904, 8.58%, see rank | 7.60% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.14% |
Wood | 48, 0.46%, see rank | 2.73% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 20, 0.19%, see rank | 0.64% | 0.39% |
No Fuel Used | 0, 0.00%, 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.