57022 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 57022 Zip Code | South Dakota | U.S. |
| Workers 16 Years and Over | 2,556, 100% | 420,700 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 2,119, 82.90%, see rank | 78.81% | 76.41% |
| Car, Truck, or Van—Carpooled | 275, 10.76%, see rank | 9.52% | 9.59% |
| Public Transportation | 0, 0.00%, see rank | 0.50% | 5.06% |
| Walked | 36, 1.41%, see rank | 4.13% | 2.78% |
| Other Means | 19, 0.74%, see rank | 1.58% | 1.79% |
| Worked at Home | 107, 4.19%, see rank | 5.46% | 4.37% |
Mean Travel Time to Work, see rank| 57022 Zip Code | 22.6 minutes |
| South Dakota | 16.2 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 57022 Zip Code | South Dakota | U.S. |
| Workers 16 Years and Over | 2,516, 100% | 412,161 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 1,911, 75.95%, see rank | 77.87% | 76.14% |
| Car, Truck, or Van—Carpooled | 428, 17.01%, see rank | 9.90% | 10.03% |
| Public Transportation | 0, 0.00%, see rank | 0.56% | 4.98% |
| Walked | 56, 2.23%, see rank | 4.27% | 2.82% |
| Other Means | 13, 0.52%, see rank | 1.71% | 1.76% |
| Worked at Home | 108, 4.29%, see rank | 5.69% | 4.27% |
Mean Travel Time to Work, see rank| 57022 Zip Code | 22.5 minutes |
| South Dakota | 16.1 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 57022 Zip Code | South Dakota | U.S. |
| Workers 16 Years and Over | 2,168, 100% | 372,648 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 1,657, 76.43%, see rank | 77.35% | 75.70% |
| Car, Truck, or Van—Carpooled | 189, 8.72%, see rank | 10.41% | 12.19% |
| Public Transportation | 11, 0.51%, see rank | 0.46% | 4.73% |
| Walked | 113, 5.21%, see rank | 4.50% | 2.93% |
| Other Means | 4, 0.18%, see rank | 0.80% | 1.19% |
| Worked at Home | 194, 8.95%, see rank | 6.48% | 3.26% |
Mean Travel Time to Work, see rank| 57022 Zip Code | 19.9 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.
