06776 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 06776 Zip Code | Connecticut | U.S. |
Total Housing Units | 10,245, 100% | 1,356,206 | 116,211,092 |
Utility Gas | 216, 2.11%, see rank | 32.80% | 48.85% |
Bottled, Tank, or LP Gas | 482, 4.70%, see rank | 3.33% | 4.86% |
Electricity | 2,719, 26.54%, see rank | 15.36% | 36.68% |
Fuel Oil, Kerosene, etc. | 6,133, 59.86%, see rank | 45.24% | 5.86% |
Coal or Coke | 7, 0.07%, see rank | 0.12% | 0.12% |
Wood | 579, 5.65%, see rank | 2.16% | 2.12% |
Solar Energy | 8, 0.08%, see rank | 0.04% | 0.05% |
Other Fuel | 81, 0.79%, see rank | 0.67% | 0.47% |
No Fuel Used | 20, 0.20%, see rank | 0.28% | 1.00% |
ACS 2008-2012 data
| 06776 Zip Code | Connecticut | U.S. |
Total Housing Units | 10,229, 100% | 1,360,184 | 115,226,802 |
Utility Gas | 233, 2.28%, see rank | 31.75% | 49.42% |
Bottled, Tank, or LP Gas | 459, 4.49%, see rank | 3.00% | 5.03% |
Electricity | 2,819, 27.56%, see rank | 15.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 6,040, 59.05%, see rank | 47.37% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.09% | 0.12% |
Wood | 608, 5.94%, see rank | 1.90% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 64, 0.63%, see rank | 0.53% | 0.43% |
No Fuel Used | 6, 0.06%, see rank | 0.20% | 0.90% |
US Census 2000 data
| 06776 Zip Code | Connecticut | U.S. |
Total Housing Units | 9,582, 100% | 1,301,670 | 105,480,101 |
Utility Gas | 77, 0.80%, see rank | 29.01% | 51.22% |
Bottled, Tank, or LP Gas | 207, 2.16%, see rank | 2.39% | 6.52% |
Electricity | 3,218, 33.58%, see rank | 14.61% | 30.35% |
Fuel Oil, Kerosene, etc. | 5,718, 59.67%, see rank | 52.43% | 8.97% |
Coal or Coke | 33, 0.34%, see rank | 0.11% | 0.14% |
Wood | 303, 3.16%, see rank | 0.91% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 26, 0.27%, see rank | 0.35% | 0.39% |
No Fuel Used | 0, 0.00%, see rank | 0.18% | 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.