82009 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 82009 Zip Code | Wyoming | U.S. |
| Workers 16 Years and Over | 16,585, 100% | 288,257 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 14,202, 85.63%, see rank | 76.60% | 76.41% |
| Car, Truck, or Van—Carpooled | 1,270, 7.66%, see rank | 11.19% | 9.59% |
| Public Transportation | 79, 0.48%, see rank | 1.61% | 5.06% |
| Walked | 155, 0.93%, see rank | 3.75% | 2.78% |
| Other Means | 237, 1.43%, see rank | 2.19% | 1.79% |
| Worked at Home | 642, 3.87%, see rank | 4.65% | 4.37% |
Mean Travel Time to Work, see rank| 82009 Zip Code | 15.7 minutes |
| Wyoming | 17.3 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 82009 Zip Code | Wyoming | U.S. |
| Workers 16 Years and Over | 16,478, 100% | 285,577 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 14,201, 86.18%, see rank | 76.16% | 76.14% |
| Car, Truck, or Van—Carpooled | 1,270, 7.71%, see rank | 11.50% | 10.03% |
| Public Transportation | 114, 0.69%, see rank | 1.65% | 4.98% |
| Walked | 159, 0.96%, see rank | 3.63% | 2.82% |
| Other Means | 215, 1.30%, see rank | 2.06% | 1.76% |
| Worked at Home | 519, 3.15%, see rank | 5.00% | 4.27% |
Mean Travel Time to Work, see rank| 82009 Zip Code | 16.7 minutes |
| Wyoming | 17.5 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 82009 Zip Code | Wyoming | U.S. |
| Workers 16 Years and Over | 13,974, 100% | 239,809 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 11,604, 83.04%, see rank | 75.37% | 75.70% |
| Car, Truck, or Van—Carpooled | 1,416, 10.13%, see rank | 13.19% | 12.19% |
| Public Transportation | 40, 0.29%, see rank | 1.43% | 4.73% |
| Walked | 184, 1.32%, see rank | 4.40% | 2.93% |
| Other Means | 82, 0.59%, see rank | 1.33% | 1.19% |
| Worked at Home | 648, 4.64%, see rank | 4.29% | 3.26% |
Mean Travel Time to Work, see rank| 82009 Zip Code | 15.2 minutes |
| Wyoming | 16.7 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.
