57103 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 57103 Zip Code | South Dakota | U.S. |
| Workers 16 Years and Over | 18,899, 100% | 420,700 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 16,071, 85.04%, see rank | 78.81% | 76.41% |
| Car, Truck, or Van—Carpooled | 1,579, 8.35%, see rank | 9.52% | 9.59% |
| Public Transportation | 296, 1.57%, see rank | 0.50% | 5.06% |
| Walked | 147, 0.78%, see rank | 4.13% | 2.78% |
| Other Means | 255, 1.35%, see rank | 1.58% | 1.79% |
| Worked at Home | 551, 2.92%, see rank | 5.46% | 4.37% |
Mean Travel Time to Work, see rank| 57103 Zip Code | 16.1 minutes |
| South Dakota | 16.2 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 57103 Zip Code | South Dakota | U.S. |
| Workers 16 Years and Over | 18,279, 100% | 412,161 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 15,515, 84.88%, see rank | 77.87% | 76.14% |
| Car, Truck, or Van—Carpooled | 1,323, 7.24%, see rank | 9.90% | 10.03% |
| Public Transportation | 232, 1.27%, see rank | 0.56% | 4.98% |
| Walked | 86, 0.47%, see rank | 4.27% | 2.82% |
| Other Means | 405, 2.22%, see rank | 1.71% | 1.76% |
| Worked at Home | 718, 3.93%, see rank | 5.69% | 4.27% |
Mean Travel Time to Work, see rank| 57103 Zip Code | 15.5 minutes |
| South Dakota | 16.1 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 57103 Zip Code | South Dakota | U.S. |
| Workers 16 Years and Over | 17,865, 100% | 372,648 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 15,060, 84.30%, see rank | 77.35% | 75.70% |
| Car, Truck, or Van—Carpooled | 1,785, 9.99%, see rank | 10.41% | 12.19% |
| Public Transportation | 151, 0.85%, see rank | 0.46% | 4.73% |
| Walked | 229, 1.28%, see rank | 4.50% | 2.93% |
| Other Means | 147, 0.82%, see rank | 0.80% | 1.19% |
| Worked at Home | 493, 2.76%, see rank | 6.48% | 3.26% |
Mean Travel Time to Work, see rank| 57103 Zip Code | 15.3 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.
