Angola Micro Area Historical Amount of Bedrooms in a House Data
ACS 2010-2014 data
| | Angola Area | Indiana | U.S. |
| Total Housing Units | 19,418, 100% | 2,811,617 | 132,741,033 |
| No Bedroom | 92, 0.47%, see rank | 1.38% | 2.17% |
| 1 Bedroom | 1,759, 9.06%, see rank | 9.26% | 11.16% |
| 2 Bedrooms | 4,838, 24.92%, see rank | 26.57% | 26.69% |
| 3 Bedrooms | 9,147, 47.11%, see rank | 44.05% | 39.70% |
| 4 Bedrooms | 2,796, 14.40%, see rank | 15.33% | 16.05% |
| 5 or More Bedrooms | 786, 4.05%, see rank | 3.40% | 4.22% |
ACS 2008-2012 data
| | Angola Area | Indiana | U.S. |
| Total Housing Units | 19,379, 100% | 2,797,237 | 131,642,457 |
| No Bedroom | 132, 0.68%, see rank | 1.29% | 2.16% |
| 1 Bedroom | 1,460, 7.53%, see rank | 9.16% | 11.12% |
| 2 Bedrooms | 5,126, 26.45%, see rank | 26.81% | 26.85% |
| 3 Bedrooms | 8,935, 46.11%, see rank | 44.04% | 39.76% |
| 4 Bedrooms | 2,920, 15.07%, see rank | 15.35% | 15.95% |
| 5 or More Bedrooms | 806, 4.16%, see rank | 3.36% | 4.16% |
ACS 2006-2010 data
| | Angola Area | Indiana | U.S. |
| Total Housing Units | 19,280, 100% | 2,778,459 | 130,038,080 |
| No Bedroom | 143, 0.74%, see rank | 0.98% | 1.84% |
| 1 Bedroom | 1,323, 6.86%, see rank | 9.40% | 11.32% |
| 2 Bedrooms | 5,280, 27.39%, see rank | 27.14% | 27.20% |
| 3 Bedrooms | 8,743, 45.35%, see rank | 44.10% | 39.80% |
| 4 Bedrooms | 2,893, 15.01%, see rank | 15.12% | 15.80% |
| 5 or More Bedrooms | 898, 4.66%, see rank | 3.25% | 4.04% |
ACS 2005-2009 data
| | Angola Area | Indiana | U.S. |
| Total Housing Units | 19,246, 100% | 2,775,849 | 127,699,712 |
| No Bedroom | 173, 0.90%, see rank | 0.88% | 1.66% |
| 1 Bedroom | 1,556, 8.08%, see rank | 9.62% | 11.48% |
| 2 Bedrooms | 5,452, 28.33%, see rank | 27.62% | 27.48% |
| 3 Bedrooms | 8,482, 44.07%, see rank | 43.76% | 39.79% |
| 4 Bedrooms | 2,804, 14.57%, see rank | 14.95% | 15.64% |
| 5 or More Bedrooms | 779, 4.05%, see rank | 3.17% | 3.94% |
* 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.
