21784 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 21784 Zip Code | Maryland | U.S. |
Occupied Units Paying Rent | 1,709, 100% | 682,566 | 39,201,928 |
$199 or Less | 38, 2.22%, see rank | 1.63% | 1.50% |
$200 to $299 | 10, 0.59%, see rank | 2.77% | 3.18% |
$300 to $499 | 89, 5.21%, see rank | 3.76% | 7.37% |
$500 to $699 | 123, 7.20%, see rank | 5.52% | 16.01% |
$700 to $999 | 463, 27.09%, see rank | 18.21% | 29.17% |
$1,000 to $1,499 | 700, 40.96%, see rank | 37.53% | 26.88% |
$1,500 to $1,999 | 184, 10.77%, see rank | 19.46% | 9.79% |
$2,000 or More | 102, 5.97%, see rank | 11.13% | 6.10% |
Median | $1,101, see rank | $1,218 | $920 |
ACS 2008-2012 data
Monthly Rental | 21784 Zip Code | Maryland | U.S. |
Occupied Units Paying Rent | 1,504, 100% | 657,078 | 37,562,111 |
$199 or Less | 25, 1.66%, see rank | 2.03% | 1.76% |
$200 to $299 | 20, 1.33%, see rank | 2.62% | 3.29% |
$300 to $499 | 31, 2.06%, see rank | 3.96% | 8.20% |
$500 to $699 | 82, 5.45%, see rank | 6.23% | 17.39% |
$700 to $999 | 422, 28.06%, see rank | 20.52% | 29.40% |
$1,000 to $1,499 | 723, 48.07%, see rank | 38.02% | 25.73% |
$1,500 to $1,999 | 128, 8.51%, see rank | 17.17% | 8.92% |
$2,000 or More | 73, 4.85%, see rank | 9.46% | 5.30% |
Median | $1,103, see rank | $1,172 | $889 |
US Census 2000 data
Monthly Rental | 21784 Zip Code | Maryland | U.S. |
Occupied Units Paying Rent | 1,450, 100% | 605,225 | 33,386,326 |
$199 or Less | 18, 1.24%, see rank | 5.32% | 5.52% |
$200 to $299 | 41, 2.83%, see rank | 3.80% | 5.45% |
$300 to $499 | 106, 7.31%, see rank | 14.85% | 23.18% |
$500 to $699 | 480, 33.10%, see rank | 27.64% | 29.57% |
$700 to $999 | 492, 33.93%, see rank | 32.78% | 24.06% |
$1,000 to $1,499 | 129, 8.90%, see rank | 12.41% | 9.15% |
$1,500 to $1,999 | 70, 4.83%, see rank | 2.14% | 2.05% |
$2,000 or More | 114, 7.86%, see rank | 1.05% | 1.02% |
Median | $722, 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.