20872 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 20872 Zip Code | Maryland | U.S. |
| Workers 16 Years and Over | 6,800, 100% | 2,913,869 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 5,498, 80.85%, see rank | 73.56% | 76.41% |
| Car, Truck, or Van—Carpooled | 638, 9.38%, see rank | 9.81% | 9.59% |
| Public Transportation | 247, 3.63%, see rank | 8.93% | 5.06% |
| Walked | 26, 0.38%, see rank | 2.34% | 2.78% |
| Other Means | 10, 0.15%, see rank | 1.18% | 1.79% |
| Worked at Home | 381, 5.60%, see rank | 4.19% | 4.37% |
Mean Travel Time to Work, see rank| 20872 Zip Code | 40.3 minutes |
| Maryland | 32.8 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 20872 Zip Code | Maryland | U.S. |
| Workers 16 Years and Over | 6,640, 100% | 2,889,278 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 5,224, 78.67%, see rank | 73.18% | 76.14% |
| Car, Truck, or Van—Carpooled | 598, 9.01%, see rank | 10.41% | 10.03% |
| Public Transportation | 252, 3.80%, see rank | 8.83% | 4.98% |
| Walked | 97, 1.46%, see rank | 2.36% | 2.82% |
| Other Means | 46, 0.69%, see rank | 1.15% | 1.76% |
| Worked at Home | 423, 6.37%, see rank | 4.07% | 4.27% |
Mean Travel Time to Work, see rank| 20872 Zip Code | 38.3 minutes |
| Maryland | 32.4 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 20872 Zip Code | Maryland | U.S. |
| Workers 16 Years and Over | 6,195, 100% | 2,591,670 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 4,940, 79.74%, see rank | 73.73% | 75.70% |
| Car, Truck, or Van—Carpooled | 690, 11.14%, see rank | 12.39% | 12.19% |
| Public Transportation | 141, 2.28%, see rank | 7.22% | 4.73% |
| Walked | 126, 2.03%, see rank | 2.50% | 2.93% |
| Other Means | 22, 0.36%, see rank | 0.81% | 1.19% |
| Worked at Home | 276, 4.46%, see rank | 3.35% | 3.26% |
Mean Travel Time to Work, see rank| 20872 Zip Code | 36.2 minutes |
| Maryland | 31.2 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.
