20876 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 20876 Zip Code | Maryland | U.S. |
Occupied Units Paying Rent | 2,555, 100% | 682,566 | 39,201,928 |
$199 or Less | 25, 0.98%, see rank | 1.63% | 1.50% |
$200 to $299 | 0, 0.00%, see rank | 2.77% | 3.18% |
$300 to $499 | 26, 1.02%, see rank | 3.76% | 7.37% |
$500 to $699 | 88, 3.44%, see rank | 5.52% | 16.01% |
$700 to $999 | 233, 9.12%, see rank | 18.21% | 29.17% |
$1,000 to $1,499 | 529, 20.70%, see rank | 37.53% | 26.88% |
$1,500 to $1,999 | 1,153, 45.13%, see rank | 19.46% | 9.79% |
$2,000 or More | 501, 19.61%, see rank | 11.13% | 6.10% |
Median | $1,663, see rank | $1,218 | $920 |
ACS 2008-2012 data
Monthly Rental | 20876 Zip Code | Maryland | U.S. |
Occupied Units Paying Rent | 2,498, 100% | 657,078 | 37,562,111 |
$199 or Less | 0, 0.00%, see rank | 2.03% | 1.76% |
$200 to $299 | 27, 1.08%, see rank | 2.62% | 3.29% |
$300 to $499 | 26, 1.04%, see rank | 3.96% | 8.20% |
$500 to $699 | 47, 1.88%, see rank | 6.23% | 17.39% |
$700 to $999 | 135, 5.40%, see rank | 20.52% | 29.40% |
$1,000 to $1,499 | 401, 16.05%, see rank | 38.02% | 25.73% |
$1,500 to $1,999 | 1,452, 58.13%, see rank | 17.17% | 8.92% |
$2,000 or More | 410, 16.41%, see rank | 9.46% | 5.30% |
Median | $1,711, see rank | $1,172 | $889 |
US Census 2000 data
Monthly Rental | 20876 Zip Code | Maryland | U.S. |
Occupied Units Paying Rent | 2,031, 100% | 605,225 | 33,386,326 |
$199 or Less | 22, 1.08%, see rank | 5.32% | 5.52% |
$200 to $299 | 17, 0.84%, see rank | 3.80% | 5.45% |
$300 to $499 | 38, 1.87%, see rank | 14.85% | 23.18% |
$500 to $699 | 97, 4.78%, see rank | 27.64% | 29.57% |
$700 to $999 | 878, 43.23%, see rank | 32.78% | 24.06% |
$1,000 to $1,499 | 901, 44.36%, see rank | 12.41% | 9.15% |
$1,500 to $1,999 | 50, 2.46%, see rank | 2.14% | 2.05% |
$2,000 or More | 28, 1.38%, see rank | 1.05% | 1.02% |
Median | $991, see rank | $689 | $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.