10580 Zip Code Historical Commuting to Work Data
ACS 2010-2014 data
| | 10580 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 6,554, 100% | 8,950,165 | 141,337,148 |
| Car, Truck, or Van—Drove Alone | 3,336, 50.90%, see rank | 53.60% | 76.41% |
| Car, Truck, or Van—Carpooled | 290, 4.42%, see rank | 6.81% | 9.59% |
| Public Transportation | 2,159, 32.94%, see rank | 27.40% | 5.06% |
| Walked | 146, 2.23%, see rank | 6.36% | 2.78% |
| Other Means | 117, 1.79%, see rank | 1.89% | 1.79% |
| Worked at Home | 506, 7.72%, see rank | 3.93% | 4.37% |
Mean Travel Time to Work, see rank| 10580 Zip Code | 38.0 minutes |
| New York | 32.5 minutes |
| U.S. | 25.7 minutes |
ACS 2008-2012 data
| | 10580 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 6,456, 100% | 8,877,453 | 139,893,639 |
| Car, Truck, or Van—Drove Alone | 3,409, 52.80%, see rank | 53.97% | 76.14% |
| Car, Truck, or Van—Carpooled | 207, 3.21%, see rank | 7.14% | 10.03% |
| Public Transportation | 2,088, 32.34%, see rank | 26.81% | 4.98% |
| Walked | 93, 1.44%, see rank | 6.40% | 2.82% |
| Other Means | 140, 2.17%, see rank | 1.81% | 1.76% |
| Worked at Home | 519, 8.04%, see rank | 3.88% | 4.27% |
Mean Travel Time to Work, see rank| 10580 Zip Code | 37.8 minutes |
| New York | 32.2 minutes |
| U.S. | 25.4 minutes |
US Census 2000 data
| | 10580 Zip Code | New York | U.S. |
| Workers 16 Years and Over | 7,160, 100% | 8,211,916 | 128,279,228 |
| Car, Truck, or Van—Drove Alone | 4,031, 56.30%, see rank | 56.26% | 75.70% |
| Car, Truck, or Van—Carpooled | 228, 3.18%, see rank | 9.22% | 12.19% |
| Public Transportation | 2,202, 30.75%, see rank | 24.43% | 4.73% |
| Walked | 153, 2.14%, see rank | 6.23% | 2.93% |
| Other Means | 38, 0.53%, see rank | 0.84% | 1.19% |
| Worked at Home | 508, 7.09%, see rank | 3.02% | 3.26% |
Mean Travel Time to Work, see rank| 10580 Zip Code | 36.2 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.
