25401 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 25401 Zip Code | West Virginia | U.S. |
Total Housing Units | 5,918, 100% | 742,359 | 116,211,092 |
Utility Gas | 1,657, 28.00%, see rank | 41.48% | 48.85% |
Bottled, Tank, or LP Gas | 182, 3.08%, see rank | 4.38% | 4.86% |
Electricity | 3,071, 51.89%, see rank | 42.94% | 36.68% |
Fuel Oil, Kerosene, etc. | 817, 13.81%, see rank | 3.16% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.66% | 0.12% |
Wood | 127, 2.15%, see rank | 6.53% | 2.12% |
Solar Energy | 16, 0.27%, see rank | 0.03% | 0.05% |
Other Fuel | 33, 0.56%, see rank | 0.63% | 0.47% |
No Fuel Used | 15, 0.25%, see rank | 0.19% | 1.00% |
ACS 2008-2012 data
| 25401 Zip Code | West Virginia | U.S. |
Total Housing Units | 6,162, 100% | 742,674 | 115,226,802 |
Utility Gas | 1,731, 28.09%, see rank | 42.36% | 49.42% |
Bottled, Tank, or LP Gas | 176, 2.86%, see rank | 4.52% | 5.03% |
Electricity | 2,979, 48.34%, see rank | 41.36% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,132, 18.37%, see rank | 3.70% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.75% | 0.12% |
Wood | 75, 1.22%, see rank | 6.52% | 2.08% |
Solar Energy | 14, 0.23%, see rank | 0.03% | 0.04% |
Other Fuel | 42, 0.68%, see rank | 0.62% | 0.43% |
No Fuel Used | 13, 0.21%, see rank | 0.14% | 0.90% |
US Census 2000 data
| 25401 Zip Code | West Virginia | U.S. |
Total Housing Units | 17,422, 100% | 736,481 | 105,480,101 |
Utility Gas | 2,970, 17.05%, see rank | 47.78% | 51.22% |
Bottled, Tank, or LP Gas | 745, 4.28%, see rank | 5.64% | 6.52% |
Electricity | 9,143, 52.48%, see rank | 32.16% | 30.35% |
Fuel Oil, Kerosene, etc. | 3,955, 22.70%, see rank | 6.75% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 1.13% | 0.14% |
Wood | 495, 2.84%, see rank | 5.92% | 1.68% |
Solar Energy | 14, 0.08%, see rank | 0.02% | 0.04% |
Other Fuel | 71, 0.41%, see rank | 0.46% | 0.39% |
No Fuel Used | 29, 0.17%, see rank | 0.15% | 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.