57747 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 57747 Zip Code | South Dakota | U.S. |
| Workers 16 Years and Over | 2,577, 100% | 420,700 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 1,850, 71.79%, see rank | 78.81% | 76.41% |
| Car, Truck, or Van—Carpooled | 410, 15.91%, see rank | 9.52% | 9.59% |
| Public Transportation | 2, 0.08%, see rank | 0.50% | 5.06% |
| Walked | 138, 5.36%, see rank | 4.13% | 2.78% |
| Other Means | 93, 3.61%, see rank | 1.58% | 1.79% |
| Worked at Home | 84, 3.26%, see rank | 5.46% | 4.37% |
Mean Travel Time to Work, see rank| 57747 Zip Code | 14.7 minutes |
| South Dakota | 16.2 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 57747 Zip Code | South Dakota | U.S. |
| Workers 16 Years and Over | 2,321, 100% | 412,161 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 1,803, 77.68%, see rank | 77.87% | 76.14% |
| Car, Truck, or Van—Carpooled | 283, 12.19%, see rank | 9.90% | 10.03% |
| Public Transportation | 1, 0.04%, see rank | 0.56% | 4.98% |
| Walked | 156, 6.72%, see rank | 4.27% | 2.82% |
| Other Means | 25, 1.08%, see rank | 1.71% | 1.76% |
| Worked at Home | 53, 2.28%, see rank | 5.69% | 4.27% |
Mean Travel Time to Work, see rank| 57747 Zip Code | 15.4 minutes |
| South Dakota | 16.1 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 57747 Zip Code | South Dakota | U.S. |
| Workers 16 Years and Over | 2,374, 100% | 372,648 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 1,810, 76.24%, see rank | 77.35% | 75.70% |
| Car, Truck, or Van—Carpooled | 318, 13.40%, see rank | 10.41% | 12.19% |
| Public Transportation | 0, 0.00%, see rank | 0.46% | 4.73% |
| Walked | 115, 4.84%, see rank | 4.50% | 2.93% |
| Other Means | 25, 1.05%, see rank | 0.80% | 1.19% |
| Worked at Home | 106, 4.47%, see rank | 6.48% | 3.26% |
Mean Travel Time to Work, see rank| 57747 Zip Code | 18.6 minutes |
| South Dakota | 15.7 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.
