02747 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 02747 Zip Code | Massachusetts | U.S. |
Total Housing Units | 6,481, 100% | 2,538,485 | 116,211,092 |
Utility Gas | 2,854, 44.04%, see rank | 49.70% | 48.85% |
Bottled, Tank, or LP Gas | 249, 3.84%, see rank | 2.86% | 4.86% |
Electricity | 468, 7.22%, see rank | 14.23% | 36.68% |
Fuel Oil, Kerosene, etc. | 2,644, 40.80%, see rank | 30.36% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.12% |
Wood | 152, 2.35%, see rank | 1.69% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 114, 1.76%, see rank | 0.65% | 0.47% |
No Fuel Used | 0, 0.00%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 02747 Zip Code | Massachusetts | U.S. |
Total Housing Units | 6,723, 100% | 2,525,694 | 115,226,802 |
Utility Gas | 2,849, 42.38%, see rank | 48.52% | 49.42% |
Bottled, Tank, or LP Gas | 287, 4.27%, see rank | 2.58% | 5.03% |
Electricity | 424, 6.31%, see rank | 13.69% | 35.51% |
Fuel Oil, Kerosene, etc. | 3,022, 44.95%, see rank | 32.78% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.12% | 0.12% |
Wood | 98, 1.46%, see rank | 1.52% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 26, 0.39%, see rank | 0.53% | 0.43% |
No Fuel Used | 17, 0.25%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 02747 Zip Code | Massachusetts | U.S. |
Total Housing Units | 5,980, 100% | 2,443,580 | 105,480,101 |
Utility Gas | 2,503, 41.86%, see rank | 43.89% | 51.22% |
Bottled, Tank, or LP Gas | 232, 3.88%, see rank | 2.63% | 6.52% |
Electricity | 193, 3.23%, see rank | 12.42% | 30.35% |
Fuel Oil, Kerosene, etc. | 2,946, 49.26%, see rank | 39.42% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.14% |
Wood | 90, 1.51%, see rank | 0.80% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 5, 0.08%, see rank | 0.44% | 0.39% |
No Fuel Used | 11, 0.18%, 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.