58249 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 58249 Zip Code | North Dakota | U.S. |
| Workers 16 Years and Over | 1,274, 100% | 377,678 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 1,041, 81.71%, see rank | 79.89% | 76.41% |
| Car, Truck, or Van—Carpooled | 103, 8.08%, see rank | 9.24% | 9.59% |
| Public Transportation | 0, 0.00%, see rank | 0.55% | 5.06% |
| Walked | 57, 4.47%, see rank | 3.87% | 2.78% |
| Other Means | 15, 1.18%, see rank | 1.32% | 1.79% |
| Worked at Home | 58, 4.55%, see rank | 5.14% | 4.37% |
Mean Travel Time to Work, see rank| 58249 Zip Code | 10.9 minutes |
| North Dakota | 16.3 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 58249 Zip Code | North Dakota | U.S. |
| Workers 16 Years and Over | 1,229, 100% | 363,094 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 984, 80.07%, see rank | 78.98% | 76.14% |
| Car, Truck, or Van—Carpooled | 123, 10.01%, see rank | 9.54% | 10.03% |
| Public Transportation | 0, 0.00%, see rank | 0.50% | 4.98% |
| Walked | 40, 3.25%, see rank | 3.88% | 2.82% |
| Other Means | 15, 1.22%, see rank | 1.44% | 1.76% |
| Worked at Home | 67, 5.45%, see rank | 5.66% | 4.27% |
Mean Travel Time to Work, see rank| 58249 Zip Code | 9.7 minutes |
| North Dakota | 15.8 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 58249 Zip Code | North Dakota | U.S. |
| Workers 16 Years and Over | 1,371, 100% | 319,481 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 1,100, 80.23%, see rank | 77.71% | 75.70% |
| Car, Truck, or Van—Carpooled | 108, 7.88%, see rank | 10.02% | 12.19% |
| Public Transportation | 0, 0.00%, see rank | 0.41% | 4.73% |
| Walked | 89, 6.49%, see rank | 5.04% | 2.93% |
| Other Means | 13, 0.95%, see rank | 0.84% | 1.19% |
| Worked at Home | 61, 4.45%, see rank | 5.98% | 3.26% |
Mean Travel Time to Work, see rank| 58249 Zip Code | 9.9 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.
