20037 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 20037 Zip Code | District of Columbia | U.S. |
Total Housing Units | 7,152, 100% | 267,415 | 116,211,092 |
Utility Gas | 3,184, 44.52%, see rank | 59.12% | 48.85% |
Bottled, Tank, or LP Gas | 72, 1.01%, see rank | 0.93% | 4.86% |
Electricity | 3,586, 50.14%, see rank | 35.97% | 36.68% |
Fuel Oil, Kerosene, etc. | 264, 3.69%, see rank | 2.45% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.12% |
Wood | 0, 0.00%, see rank | 0.01% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.05% | 0.05% |
Other Fuel | 7, 0.10%, see rank | 0.51% | 0.47% |
No Fuel Used | 39, 0.55%, see rank | 0.94% | 1.00% |
ACS 2008-2012 data
| 20037 Zip Code | District of Columbia | U.S. |
Total Housing Units | 6,743, 100% | 261,192 | 115,226,802 |
Utility Gas | 3,272, 48.52%, see rank | 61.97% | 49.42% |
Bottled, Tank, or LP Gas | 80, 1.19%, see rank | 0.94% | 5.03% |
Electricity | 3,009, 44.62%, see rank | 32.85% | 35.51% |
Fuel Oil, Kerosene, etc. | 299, 4.43%, see rank | 2.97% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.12% |
Wood | 0, 0.00%, see rank | 0.02% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 20, 0.30%, see rank | 0.52% | 0.43% |
No Fuel Used | 63, 0.93%, see rank | 0.70% | 0.90% |
US Census 2000 data
| 20037 Zip Code | District of Columbia | U.S. |
Total Housing Units | 6,840, 100% | 248,338 | 105,480,101 |
Utility Gas | 3,411, 49.87%, see rank | 65.42% | 51.22% |
Bottled, Tank, or LP Gas | 34, 0.50%, see rank | 1.78% | 6.52% |
Electricity | 2,780, 40.64%, see rank | 24.17% | 30.35% |
Fuel Oil, Kerosene, etc. | 537, 7.85%, see rank | 6.86% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.03% | 0.14% |
Wood | 9, 0.13%, see rank | 0.04% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 43, 0.63%, see rank | 0.69% | 0.39% |
No Fuel Used | 26, 0.38%, see rank | 1.00% | 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.