02864 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 02864 Zip Code | Rhode Island | U.S. |
Total Housing Units | 13,399, 100% | 409,569 | 116,211,092 |
Utility Gas | 7,564, 56.45%, see rank | 51.13% | 48.85% |
Bottled, Tank, or LP Gas | 232, 1.73%, see rank | 2.34% | 4.86% |
Electricity | 651, 4.86%, see rank | 9.15% | 36.68% |
Fuel Oil, Kerosene, etc. | 4,692, 35.02%, see rank | 34.82% | 5.86% |
Coal or Coke | 32, 0.24%, see rank | 0.11% | 0.12% |
Wood | 194, 1.45%, see rank | 1.75% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.05% |
Other Fuel | 34, 0.25%, see rank | 0.42% | 0.47% |
No Fuel Used | 0, 0.00%, see rank | 0.26% | 1.00% |
ACS 2008-2012 data
| 02864 Zip Code | Rhode Island | U.S. |
Total Housing Units | 12,917, 100% | 410,639 | 115,226,802 |
Utility Gas | 7,282, 56.38%, see rank | 49.86% | 49.42% |
Bottled, Tank, or LP Gas | 136, 1.05%, see rank | 2.00% | 5.03% |
Electricity | 607, 4.70%, see rank | 8.60% | 35.51% |
Fuel Oil, Kerosene, etc. | 4,756, 36.82%, see rank | 37.38% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.12% |
Wood | 123, 0.95%, see rank | 1.49% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 13, 0.10%, see rank | 0.30% | 0.43% |
No Fuel Used | 0, 0.00%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 02864 Zip Code | Rhode Island | U.S. |
Total Housing Units | 12,198, 100% | 408,424 | 105,480,101 |
Utility Gas | 5,683, 46.59%, see rank | 46.31% | 51.22% |
Bottled, Tank, or LP Gas | 168, 1.38%, see rank | 2.51% | 6.52% |
Electricity | 694, 5.69%, see rank | 7.64% | 30.35% |
Fuel Oil, Kerosene, etc. | 5,581, 45.75%, see rank | 42.08% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.08% | 0.14% |
Wood | 48, 0.39%, see rank | 0.88% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 24, 0.20%, see rank | 0.29% | 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.