Data Introduction- Hamilton County Audit

The leadership of Xavier University are interested in how the COVID-19 pandemic related economic policies have influenced the prices of residential properties in the Cincinnati neighborhoods adjacent to the university campus. Additionally, the city of Cincinnati has expressed concern surrounding housing affordability in the city at large. The data we will be analyzing will help better understand property sales, prices, and amenities in neighborhoods adjacent to the university community.

Data Preparation Description

The variable, “street_name” was classified as a number, but I reclassified the variable as a character because it would never make sense to take the average of the addresses even though they are numbers. Property months were changed to be ordered, so the can be seen in a certain order during grouping or visualizations.I also took out all NA values of house value which will be helpful with any arithmetic calculations. Property use was also changed to be a character instead of number as it appears because the numbers are dummy variables here. They do not numerically represent anything. I also got rid of the pound signs in that were preceding any unit_id. If i had not taken these out, these unit_ids would not have been able to be easily classified.

Variable Creation

Below, I will be creating variables for : A fully functional date vector capable of accepting requests using functions such as wday(),year(), month() and delete the now redundant month, day and year vectors in the original data. o A dummy variable indicating whether the property is a multifamily dwelling o A discrete variable indicating the following using a non-hardcoded formula: ▪ The property value is within 1 standard deviation of the mean value. ▪ The property value is more than 1 standard deviation above the mean value. ▪ The property value is less than 1 standard deviation below the mean value. ▪ The property value is missing.

Multi-family Dwelling

Creation of 1 standard deviation of mean value:

Property Value Mean

Visualizations

#3.1

From this scatter plot, we can see that single-family dwellings (510) are normally distributed, there are an immense amount of outlier data points present. Between 4000-8000 sqft is where most of the outliers lie.

#3.2 Avondale has the highest ratio of bedrooms to bathrooms, based on this graph. We can determine that this means that Avondale generally has a high number of bedrooms compared to bathrooms. This may be a problem for people wanting to live with a lot of people. Hyde Park has the lowest ratio of bedrooms to bathrooms meaning that there is almost 1 bathroom for every bedroom.

3.3

It appears that summer and fall have the highest valued transactions, especially inHyde Park, and Mount Adams. This would be my hypothesis as well because it is much easier and more convenient to move when the weather is nicer as one is typically outside hauling belongings in and out. Avondale, Clifton, Evanston, and North Avondale’s highest valued transactions are in the winter/ first couple months of the year. This is surprising, but most other transactions are aligned with the valued transactions of other neighborhoods.

4.1.1

If I were looking to sell a residential property and intended to sell for a higher price I would choose Hyde Park or Mount Adams. I chose to look at the highest values and from which neighborhood they came from. We can see from the data that the homes in these neighborhoods have the highest values.

If I were looking to sell a residential property and intended to sell for a higher price I would look at the square footage. We can clearly see that as square feet increases so does the value of the home in most cases. With higher square footage comes more bedrooms, bathrooms, or likely just larger size rooms. Individuals purchasing a home for a higher value would intend to buy a home with a lot of square footage to maximize the the cost per foot based on their purchase.

If I were looking to sell a residential property and intended to sell for a higher price I would, on average, want the home to be built around 1840, right before 1950, or around 2010. Though we can see that the average value for homes in 1860ish is a little over 2,000,000, there may only be one home built in that year that is valued at an immensely high rate. I chose to look at the average of the house values in given years because it would give the best indicator of a typical value per year in this area since we don’t know the exact neighborhood we are looking at. You could then choose to look at the highest averages and narrow down where the houses are from.

It does not matter what time of the month you plan to tell a house, a single family dwelling will always have the highest amount of transactions. Single Landominiums will always have the lowest. I chose to look at the count of each transactions on each day of the months (1-12) to determine any patterns that could be apparent over the course of a year. We can see that the 31st is the lowest among other dates. This makes sense becasue not all months have 31 days.

5.1 Housing Crisis Intro

In recent years, government officials for the city of Cincinnati have expressed concern at the growing number of investment firms purchasing residential homes in Cincinnati as investments with the intent of converting what would otherwise be owner occupied housing into rental properties. My findings will confirm that investors are contribuing to the large housing takeover more than individuals.

##          n
## 1 7.627119

7.62% of all residential properties are becoming owned by corporations rather than by individuals.

Though the city of Cincinnati claims that corporations are owning more residential properties therefore increasing the pricfe of housing in the area, from this graph, we can determine that this may not be true. On average, the value of homes individually owned in each neighborhood are higher than the values of homes owned by corporations. The price points for homes corporately owned vary much much more by neighborhood compared to homes owned by residents. Because the price point/ value or corporation owned housing is so high in Hyde Park and Mount Adams, this may drive away residents since corporations are moving to these areas. In the future, it could make housing prices higher since people will be able to move closer to work instead of being downtown, but as mentioned, the averga value of housing is still relatively higher in neighborhoods when owned by individual residents instead of corporations.

## # A tibble: 9 × 2
##   purchaser                                   `Most Purchase Transactions`
##   <chr>                                                              <int>
## 1 GREB LTD                                                               4
## 2 HECHT JONATHAN L & GLADYS ROSENBLUM                                    2
## 3 HOLZMAN MURIEL R TR                                                    2
## 4 KROMBHOLZ HEATHER O & HERBERT LEE JR C0-TRS                            2
## 5 MATKOWSKI BETTE                                                        2
## 6 MULTAN PROPERTIES LLC                                                  2
## 7 ONE REALTY GROUP LLC                                                   2
## 8 ROSANDER BRANDICE & JAN                                                2
## 9 TAMPIT LLC                                                             2

Here, we can see that 4 of the top 5 most valued transaction purchases were from investors because of “LLC” at the end. Large corporations are taking over at an alarming rate because of their ability to make large transactions at a high volume.