10472 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 10472 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 26,411, 100% | 8,950,165 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 5,050, 19.12%, see rank | 53.60% | 76.41% |
| Car, Truck, or Van—Carpooled | 1,022, 3.87%, see rank | 6.81% | 9.59% |
| Public Transportation | 17,221, 65.20%, see rank | 27.40% | 5.06% |
| Walked | 1,520, 5.76%, see rank | 6.36% | 2.78% |
| Other Means | 653, 2.47%, see rank | 1.89% | 1.79% |
| Worked at Home | 945, 3.58%, see rank | 3.93% | 4.37% |
Mean Travel Time to Work, see rank| 10472 Zip Code | 46.7 minutes |
| New York | 32.5 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 10472 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 25,751, 100% | 8,877,453 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 4,777, 18.55%, see rank | 53.97% | 76.14% |
| Car, Truck, or Van—Carpooled | 1,091, 4.24%, see rank | 7.14% | 10.03% |
| Public Transportation | 16,834, 65.37%, see rank | 26.81% | 4.98% |
| Walked | 1,232, 4.78%, see rank | 6.40% | 2.82% |
| Other Means | 807, 3.13%, see rank | 1.81% | 1.76% |
| Worked at Home | 1,010, 3.92%, see rank | 3.88% | 4.27% |
Mean Travel Time to Work, see rank| 10472 Zip Code | 47.1 minutes |
| New York | 32.2 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 10472 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 18,495, 100% | 8,211,916 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 4,498, 24.32%, see rank | 56.26% | 75.70% |
| Car, Truck, or Van—Carpooled | 1,725, 9.33%, see rank | 9.22% | 12.19% |
| Public Transportation | 10,810, 58.45%, see rank | 24.43% | 4.73% |
| Walked | 927, 5.01%, see rank | 6.23% | 2.93% |
| Other Means | 160, 0.87%, see rank | 0.84% | 1.19% |
| Worked at Home | 375, 2.03%, see rank | 3.02% | 3.26% |
Mean Travel Time to Work, see rank| 10472 Zip Code | 45.8 minutes |
| New York | 31.7 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.
