17764 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 17764 Zip Code | Pennsylvania | U.S. |
| Workers 16 Years and Over | 692, 100% | 5,826,933 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 549, 79.34%, see rank | 76.64% | 76.41% |
| Car, Truck, or Van—Carpooled | 89, 12.86%, see rank | 8.77% | 9.59% |
| Public Transportation | 3, 0.43%, see rank | 5.50% | 5.06% |
| Walked | 34, 4.91%, see rank | 3.85% | 2.78% |
| Other Means | 6, 0.87%, see rank | 1.34% | 1.79% |
| Worked at Home | 11, 1.59%, see rank | 3.89% | 4.37% |
Mean Travel Time to Work, see rank| 17764 Zip Code | 27.8 minutes |
| Pennsylvania | 26.0 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 17764 Zip Code | Pennsylvania | U.S. |
| Workers 16 Years and Over | 693, 100% | 5,808,681 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 517, 74.60%, see rank | 76.48% | 76.14% |
| Car, Truck, or Van—Carpooled | 97, 14.00%, see rank | 9.18% | 10.03% |
| Public Transportation | 2, 0.29%, see rank | 5.43% | 4.98% |
| Walked | 45, 6.49%, see rank | 3.90% | 2.82% |
| Other Means | 23, 3.32%, see rank | 1.31% | 1.76% |
| Worked at Home | 9, 1.30%, see rank | 3.70% | 4.27% |
Mean Travel Time to Work, see rank| 17764 Zip Code | 29.4 minutes |
| Pennsylvania | 25.7 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 17764 Zip Code | Pennsylvania | U.S. |
| Workers 16 Years and Over | 993, 100% | 5,556,311 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 721, 72.61%, see rank | 76.45% | 75.70% |
| Car, Truck, or Van—Carpooled | 172, 17.32%, see rank | 10.39% | 12.19% |
| Public Transportation | 5, 0.50%, see rank | 5.21% | 4.73% |
| Walked | 59, 5.94%, see rank | 4.13% | 2.93% |
| Other Means | 11, 1.11%, see rank | 0.85% | 1.19% |
| Worked at Home | 25, 2.52%, see rank | 2.96% | 3.26% |
Mean Travel Time to Work, see rank| 17764 Zip Code | 30.9 minutes |
| Pennsylvania | 24.7 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.
