I was assigned to examine the housing demographics for the area. I looked at housing units, occupancy, and vacancy status and units in structure for the detailed study area. From this data, you can learn a lot about who lives in the area, and trends in housing. Some of these including high vacancy rates, how many single-family homes and how many multifamily homes, and finally how many housing units are there are in the area over time. I learned that the largest type of housing in the area is definitely single-family homes. Over time, the most common types of housing would be one unit and 50+ units. This shows that the area is not completely homogeneous in hosing types despite there being many more single-family homes than any other type of housing. The following graphics show how through time the number of different housing types has changed in the study area over time. The final pie chart shows just how large a portion of the housing is single-family homes.

In the tables below, the housing data for Kansas City is provided followed by the data for the study area from 1990 to 2018. From this, we can gather trends that may relate to the study area. For example, the study area experienced a sharp drop in total housing units from 1990 to 2000, while in the city as a whole the total housing units increased. In the city, the number of single-family housing units is a larger part of the total housing than in the study area. Kansas City also experienced a spike in vacancy in 2008-2013 that the study area did not experience.

Kansas City, MO 1990-2018

Study Area, 1990-2018

When looking at vacancy rates in the maps below, it is clear that census tracts 178 block group 3 and tract 162 block group 1 have the highest levels of vacancy. It is likely that in these areas the median household income will also be lower. You will notice other differences between the highest vacancy rate tracts and the lowest vacancy tracts. Such as workforce participation and median household values.

Finally, simply looking at the number of households can largely inform a researcher on the place they’re studying. If you notice that the number of housing units is decreasing over time it can be inferred that the population is shrinking, if it is growing then it is clear there is a high demand to live in the area. In the map below, we can see in exactly which block groups have the highest percentage of single-family housing. Troost Park is highlighted with a pale green box. This tells us which areas are mostly residential and likely lower density. Overall, housing data tells us a lot about who lives in the area, and what kind of economic situation these areas are in.

Social Explorer Dataset (SE), Census 1990-2018, Social Explorer; U.S. Census Bureau