53154 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 53154 Zip Code | Wisconsin | U.S. |
Total Housing Units | 14,140, 100% | 2,293,250 | 116,211,092 |
Utility Gas | 10,703, 75.69%, see rank | 65.30% | 48.85% |
Bottled, Tank, or LP Gas | 207, 1.46%, see rank | 10.88% | 4.86% |
Electricity | 2,910, 20.58%, see rank | 14.81% | 36.68% |
Fuel Oil, Kerosene, etc. | 108, 0.76%, see rank | 3.02% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 96, 0.68%, see rank | 4.57% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 57, 0.40%, see rank | 0.94% | 0.47% |
No Fuel Used | 59, 0.42%, see rank | 0.44% | 1.00% |
ACS 2008-2012 data
| 53154 Zip Code | Wisconsin | U.S. |
Total Housing Units | 13,719, 100% | 2,286,339 | 115,226,802 |
Utility Gas | 10,445, 76.14%, see rank | 65.77% | 49.42% |
Bottled, Tank, or LP Gas | 175, 1.28%, see rank | 10.80% | 5.03% |
Electricity | 2,845, 20.74%, see rank | 13.95% | 35.51% |
Fuel Oil, Kerosene, etc. | 78, 0.57%, see rank | 3.63% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 89, 0.65%, see rank | 4.56% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 43, 0.31%, see rank | 0.89% | 0.43% |
No Fuel Used | 44, 0.32%, see rank | 0.36% | 0.90% |
US Census 2000 data
| 53154 Zip Code | Wisconsin | U.S. |
Total Housing Units | 11,198, 100% | 2,084,544 | 105,480,101 |
Utility Gas | 9,103, 81.29%, see rank | 66.40% | 51.22% |
Bottled, Tank, or LP Gas | 68, 0.61%, see rank | 10.96% | 6.52% |
Electricity | 1,647, 14.71%, see rank | 11.36% | 30.35% |
Fuel Oil, Kerosene, etc. | 303, 2.71%, see rank | 7.60% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.14% |
Wood | 10, 0.09%, see rank | 2.73% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 24, 0.21%, see rank | 0.64% | 0.39% |
No Fuel Used | 43, 0.38%, 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.