10502 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 10502 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 2,566, 100% | 8,950,165 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 1,656, 64.54%, see rank | 53.60% | 76.41% |
| Car, Truck, or Van—Carpooled | 218, 8.50%, see rank | 6.81% | 9.59% |
| Public Transportation | 460, 17.93%, see rank | 27.40% | 5.06% |
| Walked | 84, 3.27%, see rank | 6.36% | 2.78% |
| Other Means | 22, 0.86%, see rank | 1.89% | 1.79% |
| Worked at Home | 126, 4.91%, see rank | 3.93% | 4.37% |
Mean Travel Time to Work, see rank| 10502 Zip Code | 34.3 minutes |
| New York | 32.5 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 10502 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 2,546, 100% | 8,877,453 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 1,589, 62.41%, see rank | 53.97% | 76.14% |
| Car, Truck, or Van—Carpooled | 290, 11.39%, see rank | 7.14% | 10.03% |
| Public Transportation | 375, 14.73%, see rank | 26.81% | 4.98% |
| Walked | 24, 0.94%, see rank | 6.40% | 2.82% |
| Other Means | 17, 0.67%, see rank | 1.81% | 1.76% |
| Worked at Home | 251, 9.86%, see rank | 3.88% | 4.27% |
Mean Travel Time to Work, see rank| 10502 Zip Code | 34.8 minutes |
| New York | 32.2 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 10502 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 2,355, 100% | 8,211,916 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 1,767, 75.03%, see rank | 56.26% | 75.70% |
| Car, Truck, or Van—Carpooled | 104, 4.42%, see rank | 9.22% | 12.19% |
| Public Transportation | 320, 13.59%, see rank | 24.43% | 4.73% |
| Walked | 13, 0.55%, see rank | 6.23% | 2.93% |
| Other Means | 23, 0.98%, see rank | 0.84% | 1.19% |
| Worked at Home | 128, 5.44%, see rank | 3.02% | 3.26% |
Mean Travel Time to Work, see rank| 10502 Zip Code | 33.7 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.
