53215 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 53215 Zip Code | Wisconsin | U.S. |
| Workers 16 Years and Over | 23,486, 100% | 2,804,563 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 15,432, 65.71%, see rank | 80.43% | 76.41% |
| Car, Truck, or Van—Carpooled | 4,472, 19.04%, see rank | 8.62% | 9.59% |
| Public Transportation | 1,868, 7.95%, see rank | 1.84% | 5.06% |
| Walked | 1,013, 4.31%, see rank | 3.33% | 2.78% |
| Other Means | 238, 1.01%, see rank | 1.70% | 1.79% |
| Worked at Home | 463, 1.97%, see rank | 4.08% | 4.37% |
Mean Travel Time to Work, see rank| 53215 Zip Code | 22.4 minutes |
| Wisconsin | 21.4 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 53215 Zip Code | Wisconsin | U.S. |
| Workers 16 Years and Over | 22,327, 100% | 2,807,856 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 15,153, 67.87%, see rank | 79.92% | 76.14% |
| Car, Truck, or Van—Carpooled | 4,155, 18.61%, see rank | 9.20% | 10.03% |
| Public Transportation | 1,644, 7.36%, see rank | 1.81% | 4.98% |
| Walked | 895, 4.01%, see rank | 3.31% | 2.82% |
| Other Means | 227, 1.02%, see rank | 1.72% | 1.76% |
| Worked at Home | 253, 1.13%, see rank | 4.03% | 4.27% |
Mean Travel Time to Work, see rank| 53215 Zip Code | 22.5 minutes |
| Wisconsin | 21.2 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 53215 Zip Code | Wisconsin | U.S. |
| Workers 16 Years and Over | 20,770, 100% | 2,690,704 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 14,022, 67.51%, see rank | 79.49% | 75.70% |
| Car, Truck, or Van—Carpooled | 3,730, 17.96%, see rank | 9.94% | 12.19% |
| Public Transportation | 1,845, 8.88%, see rank | 1.98% | 4.73% |
| Walked | 680, 3.27%, see rank | 3.73% | 2.93% |
| Other Means | 252, 1.21%, see rank | 0.94% | 1.19% |
| Worked at Home | 241, 1.16%, see rank | 3.92% | 3.26% |
Mean Travel Time to Work, see rank| 53215 Zip Code | 22.0 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.
