10595 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 10595 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 3,197, 100% | 8,950,165 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 2,202, 68.88%, see rank | 53.60% | 76.41% |
| Car, Truck, or Van—Carpooled | 260, 8.13%, see rank | 6.81% | 9.59% |
| Public Transportation | 410, 12.82%, see rank | 27.40% | 5.06% |
| Walked | 161, 5.04%, see rank | 6.36% | 2.78% |
| Other Means | 0, 0.00%, see rank | 1.89% | 1.79% |
| Worked at Home | 164, 5.13%, see rank | 3.93% | 4.37% |
Mean Travel Time to Work, see rank| 10595 Zip Code | 28.9 minutes |
| New York | 32.5 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 10595 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 2,954, 100% | 8,877,453 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 2,176, 73.66%, see rank | 53.97% | 76.14% |
| Car, Truck, or Van—Carpooled | 179, 6.06%, see rank | 7.14% | 10.03% |
| Public Transportation | 369, 12.49%, see rank | 26.81% | 4.98% |
| Walked | 93, 3.15%, see rank | 6.40% | 2.82% |
| Other Means | 0, 0.00%, see rank | 1.81% | 1.76% |
| Worked at Home | 137, 4.64%, see rank | 3.88% | 4.27% |
Mean Travel Time to Work, see rank| 10595 Zip Code | 29.5 minutes |
| New York | 32.2 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 10595 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 2,869, 100% | 8,211,916 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 2,214, 77.17%, see rank | 56.26% | 75.70% |
| Car, Truck, or Van—Carpooled | 135, 4.71%, see rank | 9.22% | 12.19% |
| Public Transportation | 336, 11.71%, see rank | 24.43% | 4.73% |
| Walked | 96, 3.35%, see rank | 6.23% | 2.93% |
| Other Means | 0, 0.00%, see rank | 0.84% | 1.19% |
| Worked at Home | 88, 3.07%, see rank | 3.02% | 3.26% |
Mean Travel Time to Work, see rank| 10595 Zip Code | 27.7 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.
