29475 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 29475 Zip Code | South Carolina | U.S. |
| Workers 16 Years and Over | 871, 100% | 2,022,019 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 773, 88.75%, see rank | 82.69% | 76.41% |
| Car, Truck, or Van—Carpooled | 70, 8.04%, see rank | 9.32% | 9.59% |
| Public Transportation | 0, 0.00%, see rank | 0.61% | 5.06% |
| Walked | 7, 0.80%, see rank | 2.10% | 2.78% |
| Other Means | 21, 2.41%, see rank | 1.66% | 1.79% |
| Worked at Home | 0, 0.00%, see rank | 3.61% | 4.37% |
Mean Travel Time to Work, see rank| 29475 Zip Code | 34.3 minutes |
| South Carolina | 23.5 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 29475 Zip Code | South Carolina | U.S. |
| Workers 16 Years and Over | 1,245, 100% | 1,988,444 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 1,079, 86.67%, see rank | 82.19% | 76.14% |
| Car, Truck, or Van—Carpooled | 90, 7.23%, see rank | 9.91% | 10.03% |
| Public Transportation | 0, 0.00%, see rank | 0.60% | 4.98% |
| Walked | 41, 3.29%, see rank | 2.03% | 2.82% |
| Other Means | 35, 2.81%, see rank | 1.62% | 1.76% |
| Worked at Home | 0, 0.00%, see rank | 3.65% | 4.27% |
Mean Travel Time to Work, see rank| 29475 Zip Code | 26.3 minutes |
| South Carolina | 23.2 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 29475 Zip Code | South Carolina | U.S. |
| Workers 16 Years and Over | 993, 100% | 1,822,969 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 705, 71.00%, see rank | 79.39% | 75.70% |
| Car, Truck, or Van—Carpooled | 211, 21.25%, see rank | 14.04% | 12.19% |
| Public Transportation | 21, 2.11%, see rank | 0.85% | 4.73% |
| Walked | 0, 0.00%, see rank | 2.34% | 2.93% |
| Other Means | 23, 2.32%, see rank | 1.29% | 1.19% |
| Worked at Home | 33, 3.32%, see rank | 2.10% | 3.26% |
Mean Travel Time to Work, see rank| 29475 Zip Code | 35.2 minutes |
| South Carolina | 23.5 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.
