58075 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 58075 Zip Code | North Dakota | U.S. |
| Workers 16 Years and Over | 4,999, 100% | 377,678 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 4,246, 84.94%, see rank | 79.89% | 76.41% |
| Car, Truck, or Van—Carpooled | 302, 6.04%, see rank | 9.24% | 9.59% |
| Public Transportation | 0, 0.00%, see rank | 0.55% | 5.06% |
| Walked | 224, 4.48%, see rank | 3.87% | 2.78% |
| Other Means | 59, 1.18%, see rank | 1.32% | 1.79% |
| Worked at Home | 168, 3.36%, see rank | 5.14% | 4.37% |
Mean Travel Time to Work, see rank| 58075 Zip Code | 12.8 minutes |
| North Dakota | 16.3 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 58075 Zip Code | North Dakota | U.S. |
| Workers 16 Years and Over | 4,759, 100% | 363,094 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 4,000, 84.05%, see rank | 78.98% | 76.14% |
| Car, Truck, or Van—Carpooled | 349, 7.33%, see rank | 9.54% | 10.03% |
| Public Transportation | 0, 0.00%, see rank | 0.50% | 4.98% |
| Walked | 186, 3.91%, see rank | 3.88% | 2.82% |
| Other Means | 21, 0.44%, see rank | 1.44% | 1.76% |
| Worked at Home | 203, 4.27%, see rank | 5.66% | 4.27% |
Mean Travel Time to Work, see rank| 58075 Zip Code | 12.2 minutes |
| North Dakota | 15.8 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 58075 Zip Code | North Dakota | U.S. |
| Workers 16 Years and Over | 5,066, 100% | 319,481 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 4,009, 79.14%, see rank | 77.71% | 75.70% |
| Car, Truck, or Van—Carpooled | 513, 10.13%, see rank | 10.02% | 12.19% |
| Public Transportation | 0, 0.00%, see rank | 0.41% | 4.73% |
| Walked | 325, 6.42%, see rank | 5.04% | 2.93% |
| Other Means | 60, 1.18%, see rank | 0.84% | 1.19% |
| Worked at Home | 159, 3.14%, see rank | 5.98% | 3.26% |
Mean Travel Time to Work, see rank| 58075 Zip Code | 13.6 minutes |
| North Dakota | 14.9 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.
