16063 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 16063 Zip Code | Pennsylvania | U.S. |
Occupied Units Paying Rent | 1,024, 100% | 1,418,302 | 39,201,928 |
$199 or Less | 14, 1.37%, see rank | 1.98% | 1.50% |
$200 to $299 | 11, 1.07%, see rank | 4.36% | 3.18% |
$300 to $499 | 162, 15.82%, see rank | 9.44% | 7.37% |
$500 to $699 | 223, 21.78%, see rank | 19.30% | 16.01% |
$700 to $999 | 347, 33.89%, see rank | 32.15% | 29.17% |
$1,000 to $1,499 | 159, 15.53%, see rank | 23.68% | 26.88% |
$1,500 to $1,999 | 32, 3.13%, see rank | 5.77% | 9.79% |
$2,000 or More | 76, 7.42%, see rank | 3.33% | 6.10% |
Median | $794, see rank | $832 | $920 |
ACS 2008-2012 data
Monthly Rental | 16063 Zip Code | Pennsylvania | U.S. |
Occupied Units Paying Rent | 1,072, 100% | 1,389,264 | 37,562,111 |
$199 or Less | 13, 1.21%, see rank | 2.38% | 1.76% |
$200 to $299 | 26, 2.43%, see rank | 4.39% | 3.29% |
$300 to $499 | 149, 13.90%, see rank | 10.69% | 8.20% |
$500 to $699 | 156, 14.55%, see rank | 21.57% | 17.39% |
$700 to $999 | 341, 31.81%, see rank | 32.16% | 29.40% |
$1,000 to $1,499 | 228, 21.27%, see rank | 21.06% | 25.73% |
$1,500 to $1,999 | 41, 3.82%, see rank | 5.02% | 8.92% |
$2,000 or More | 118, 11.01%, see rank | 2.74% | 5.30% |
Median | $842, see rank | $794 | $889 |
US Census 2000 data
Monthly Rental | 16063 Zip Code | Pennsylvania | U.S. |
Occupied Units Paying Rent | 1,134, 100% | 1,270,837 | 33,386,326 |
$199 or Less | 82, 7.23%, see rank | 6.72% | 5.52% |
$200 to $299 | 81, 7.14%, see rank | 7.04% | 5.45% |
$300 to $499 | 261, 23.02%, see rank | 30.62% | 23.18% |
$500 to $699 | 322, 28.40%, see rank | 30.50% | 29.57% |
$700 to $999 | 160, 14.11%, see rank | 18.43% | 24.06% |
$1,000 to $1,499 | 57, 5.03%, see rank | 5.13% | 9.15% |
$1,500 to $1,999 | 91, 8.02%, see rank | 1.01% | 2.05% |
$2,000 or More | 80, 7.05%, see rank | 0.55% | 1.02% |
Median | $575, see rank | $531 | $602 |
* 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.