53083 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 53083 Zip Code | Wisconsin | U.S. |
| Workers 16 Years and Over | 11,137, 100% | 2,804,563 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 10,045, 90.19%, see rank | 80.43% | 76.41% |
| Car, Truck, or Van—Carpooled | 637, 5.72%, see rank | 8.62% | 9.59% |
| Public Transportation | 45, 0.40%, see rank | 1.84% | 5.06% |
| Walked | 99, 0.89%, see rank | 3.33% | 2.78% |
| Other Means | 71, 0.64%, see rank | 1.70% | 1.79% |
| Worked at Home | 240, 2.15%, see rank | 4.08% | 4.37% |
Mean Travel Time to Work, see rank| 53083 Zip Code | 15.3 minutes |
| Wisconsin | 21.4 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 53083 Zip Code | Wisconsin | U.S. |
| Workers 16 Years and Over | 11,142, 100% | 2,807,856 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 10,037, 90.08%, see rank | 79.92% | 76.14% |
| Car, Truck, or Van—Carpooled | 590, 5.30%, see rank | 9.20% | 10.03% |
| Public Transportation | 25, 0.22%, see rank | 1.81% | 4.98% |
| Walked | 167, 1.50%, see rank | 3.31% | 2.82% |
| Other Means | 86, 0.77%, see rank | 1.72% | 1.76% |
| Worked at Home | 237, 2.13%, see rank | 4.03% | 4.27% |
Mean Travel Time to Work, see rank| 53083 Zip Code | 16.0 minutes |
| Wisconsin | 21.2 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 53083 Zip Code | Wisconsin | U.S. |
| Workers 16 Years and Over | 10,589, 100% | 2,690,704 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 9,026, 85.24%, see rank | 79.49% | 75.70% |
| Car, Truck, or Van—Carpooled | 878, 8.29%, see rank | 9.94% | 12.19% |
| Public Transportation | 54, 0.51%, see rank | 1.98% | 4.73% |
| Walked | 239, 2.26%, see rank | 3.73% | 2.93% |
| Other Means | 159, 1.50%, see rank | 0.94% | 1.19% |
| Worked at Home | 233, 2.20%, see rank | 3.92% | 3.26% |
Mean Travel Time to Work, see rank| 53083 Zip Code | 14.5 minutes |
| Wisconsin | 20.1 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.
