27884 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 27884 Zip Code | North Carolina | U.S. |
| Workers 16 Years and Over | 381, 100% | 4,280,414 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 273, 71.65%, see rank | 81.16% | 76.41% |
| Car, Truck, or Van—Carpooled | 63, 16.54%, see rank | 10.15% | 9.59% |
| Public Transportation | 0, 0.00%, see rank | 1.12% | 5.06% |
| Walked | 45, 11.81%, see rank | 1.78% | 2.78% |
| Other Means | 0, 0.00%, see rank | 1.31% | 1.79% |
| Worked at Home | 0, 0.00%, see rank | 4.48% | 4.37% |
Mean Travel Time to Work, see rank| 27884 Zip Code | 20.9 minutes |
| North Carolina | 23.5 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 27884 Zip Code | North Carolina | U.S. |
| Workers 16 Years and Over | 416, 100% | 4,237,689 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 320, 76.92%, see rank | 80.88% | 76.14% |
| Car, Truck, or Van—Carpooled | 67, 16.11%, see rank | 10.70% | 10.03% |
| Public Transportation | 0, 0.00%, see rank | 1.09% | 4.98% |
| Walked | 8, 1.92%, see rank | 1.79% | 2.82% |
| Other Means | 21, 5.05%, see rank | 1.28% | 1.76% |
| Worked at Home | 0, 0.00%, see rank | 4.26% | 4.27% |
Mean Travel Time to Work, see rank| 27884 Zip Code | 34.5 minutes |
| North Carolina | 23.2 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 27884 Zip Code | North Carolina | U.S. |
| Workers 16 Years and Over | 465, 100% | 3,837,773 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 393, 84.52%, see rank | 79.39% | 75.70% |
| Car, Truck, or Van—Carpooled | 38, 8.17%, see rank | 14.03% | 12.19% |
| Public Transportation | 0, 0.00%, see rank | 0.91% | 4.73% |
| Walked | 0, 0.00%, see rank | 1.93% | 2.93% |
| Other Means | 18, 3.87%, see rank | 1.07% | 1.19% |
| Worked at Home | 16, 3.44%, see rank | 2.68% | 3.26% |
Mean Travel Time to Work, see rank| 27884 Zip Code | 24.3 minutes |
| North Carolina | 23.2 minutes |
| U.S. | 25.1 minutes |
* 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.
