16423 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 16423 Zip Code | Pennsylvania | U.S. |
| Workers 16 Years and Over | 2,097, 100% | 5,826,933 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 1,755, 83.69%, see rank | 76.64% | 76.41% |
| Car, Truck, or Van—Carpooled | 204, 9.73%, see rank | 8.77% | 9.59% |
| Public Transportation | 7, 0.33%, see rank | 5.50% | 5.06% |
| Walked | 49, 2.34%, see rank | 3.85% | 2.78% |
| Other Means | 25, 1.19%, see rank | 1.34% | 1.79% |
| Worked at Home | 57, 2.72%, see rank | 3.89% | 4.37% |
Mean Travel Time to Work, see rank| 16423 Zip Code | 23.2 minutes |
| Pennsylvania | 26.0 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 16423 Zip Code | Pennsylvania | U.S. |
| Workers 16 Years and Over | 2,015, 100% | 5,808,681 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 1,757, 87.20%, see rank | 76.48% | 76.14% |
| Car, Truck, or Van—Carpooled | 160, 7.94%, see rank | 9.18% | 10.03% |
| Public Transportation | 1, 0.05%, see rank | 5.43% | 4.98% |
| Walked | 28, 1.39%, see rank | 3.90% | 2.82% |
| Other Means | 35, 1.74%, see rank | 1.31% | 1.76% |
| Worked at Home | 34, 1.69%, see rank | 3.70% | 4.27% |
Mean Travel Time to Work, see rank| 16423 Zip Code | 21.4 minutes |
| Pennsylvania | 25.7 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 16423 Zip Code | Pennsylvania | U.S. |
| Workers 16 Years and Over | 1,966, 100% | 5,556,311 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 1,596, 81.18%, see rank | 76.45% | 75.70% |
| Car, Truck, or Van—Carpooled | 284, 14.45%, see rank | 10.39% | 12.19% |
| Public Transportation | 3, 0.15%, see rank | 5.21% | 4.73% |
| Walked | 12, 0.61%, see rank | 4.13% | 2.93% |
| Other Means | 6, 0.31%, see rank | 0.85% | 1.19% |
| Worked at Home | 65, 3.31%, see rank | 2.96% | 3.26% |
Mean Travel Time to Work, see rank| 16423 Zip Code | 19.1 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.
