Far Southwest—Neighborhood Analysis of Single-Family Residential Homes (August 2019)

The Far Southwest neighborhood is just that—far southwest! It represents one of the periphery neighborhoods of the City of Portland. The neighborhood is largely dominated by the Portland Community College Sylvania Campus. The campus was opened in 1968 and has approximately 28,000 students enrolled each year.

Aerial Small

Appraisers endeavor to take the measure of a neighborhood with a variety of tables, charts, and graphs. It helps them to frame the value opinion and see how the subject property relates to the neighborhood as a whole. Before we dive in, a…

Quick Note

The following information is based on detached single-family residential homes that were sold and/or listed on the open market as reported by RMLS—the primary MLS service for the City of Portland. Data was pulled from the year 2000 to the present date. The data export was checked, validated, and scrubbed of obvious errors using custom tools developed by the author. With that out of the way, let’s look at some neighborhood stats.

Neighborhood Statistics Overview

The following table summarizes important metrics for the neighborhood. Each column is independent of the others and the basement square foot column reflects only properties with a basement.

2019-08-11_17-37-32

Approximately 6% of sales in the neighborhood were new constructions.

The following scatter plot shows all closed-sale detached single-family residences  (with a red trendline):

2019-08-11_18-00-32

The neighborhood suffered during the housing crisis, but has recovered with prices generally higher than they were before the crash. The red trendline shows prices have leveled and have even dipped a bit. This is further borne out by a review of average and median sales prices over the last two years:

Quarters

Percentile rank is a way of seeing price bands for the neighborhood. For instance, the 50th percentile, or median rank, shows that half of all sales since the year 2000 have been under $340,350. Prices are fairly clustered all the way up to the 90th percentile:

Percentile

The following table shows important marketing information for both the last two years and since the year 2000:

OLP

The “SP/OLP” label stands for “sales price/original list price” ratio. This is an important metric, as it shows what the particular property sold for relative to the original list price that was advertised. The “SP/LP” column tracks what the sales price was relative to the final published list price. This column, while not as important as the first one, still yields important insights as to the direction of negotiations. The “DOM” column tracks the days on market for all properties sold and listed and helps frame expected marketing time. Finally, the “CtL” label stands for “contract-to-list” ratio. It is the number of pending sales divided by the total number of listings. A low ratio means many properties are sitting on the open market waiting for offers. A high ratio indicates properties are being absorbed by the market quickly, commonly referred to as a “seller’s market.”

As of this post date, there are more properties waiting for offers than are under contract.

The following table more closely examines DOM as well as CDOM (cumulative days on market). CDOM is also an important metric as homes are often taken off the market and then subsequently relisted (typically at a lower price). The CDOM metric can give you a better idea of total expected marketing time. The table breaks out DOM & CDOM by price segment:

CDOM

Let’s wrap up the neighborhood statistics overview with the following table showing the sales terms in the market over the last two years:

Sale Terms

While conventional financing is predominant, there is a substantial cash market.

Let’s conclude our tour of South Portland with a histogram analysis of the neighborhood:

Histogram Analysis

Age

Age

Most properties in the neighborhood are between 10-44 years of age.

Bathroom Count

Bath

A home with two full bathrooms and one half bathroom (powder room) is the most typical for the market.

Bedroom Count

Bedroom

The vast majority of homes are have either three of four bedrooms.

Garage Stall Count

Garage

Most homes in the neighborhood have a two-car garage.

Total Square Footage

TSF

This metric includes above-grade living area and basement space for a combined figure. The median total square footage for the neighborhood is ~2,400 sq. ft.

Gross Living Area

GLA

Gross living area only consider non-basement living space. Often the market reacts more strongly to gross living area, usually applying a discount to basement space. Median gross living area is approximately 1,880 sq. ft.

Level Count

Levels

The majority of properties are two levels in this neighborhood.

Lot Size

Lot

The median lot size for home in the neighborhood is ~10,000 sq. ft. 

Sales Price

Sales Price

This histogram includes sales prices over a 20-year period. The median sales price over the last 20 years is: ~$340,000; and the median sales price over the last 2 years is: $437,000.

The highest sales price obtained in the neighborhood (on the open market) was $1,095,000 on 10/16/2018. The home was a new construction at the time of the sale and has 4,050 total square feet.

# of Sales

# of Sales

The number of sales in the neighborhood have been trending higher this year as compared to the previous one.

So, there you have it, a market overview for the Far Southwest neighborhood!

Appraisal Reports

If you are a homeowner and are looking to sell your home, you would greatly benefit from a prelisting appraisal. Our firm will bring high-level analytics to your report and give you a sound understanding of the current market.

If you are an agent and need detailed neighborhood analysis, or analysis of specific areas or specific segments of the market, please contact us and we can generate a custom report to help you frame a listing price for your client!

Lake Oswego—Neighborhood Analysis of Waterfront Single-Family Residential Homes (July 2019)

Oswego Lake is a scenic and picturesque former channel of the Tualatin River. It is a natural feature, but has been enlarged due to a dam to its present size of  ~395 acres. Lake Oswego-SmallMany homes rim the lake as well as the smaller bays connected to it. Some of the properties surrounding Oswego Lake are among the more expensive in the Greater Portland Area.

Appraisers endeavor to take the measure of a neighborhood with a variety of tables, charts, and graphs. It helps them to frame the value opinion and see how the subject property relates to the neighborhood as a whole. Let’s examine waterfront properties on Oswego Lake (including the bays). But before we dive in, a…

Quick Note

The following information is based on detached single-family residential homes that were sold and/or listed on the open market as reported by RMLS—the primary MLS service for the City of Lake Oswego. Data was pulled from the year 2000 to the July 2019. The data export was checked, validated, and scrubbed of obvious errors using custom tools developed by the author. With that out of the way, let’s look at some neighborhood stats.

Neighborhood Statistics Overview

The following table summarizes important metrics for the neighborhood. Each column is independent of the others and the basement square foot column reflects only properties with a basement.

Neigh Stats

There has been relatively little new construction along the lake with ~3.8% of all sales/listings over the past 20 years having been new homes.

The following scatter plot shows all closed-sale detached single-family residences  (with a red trendline):

2019-08-03_16-59-16

The neighborhood suffered during the housing crisis, but has recovered with prices generally higher than they were before the crash. The red trendline shows prices have leveled and have even dipped a bit. This is further borne out by a review of average and median sales prices over the last two years.

Two Years

Percentile rank is a way of seeing price bands for the neighborhood. For instance, the 50th percentile, or median rank, shows that half of all sales since the year 2000 have been under $1.29 million. Prices are fairly clustered up to the 70th percentile where the upper range begins to balloon:

Percentile

The following table shows important marketing information for both the last two years and since the year 2000:

2019-08-03_17-39-01

The “SP/OLP” label stands for “sales price/original list price” ratio. This is an important metric, as it shows what the particular property sold for relative to the original list price that was advertised. The “SP/LP” column tracks what the sales price was relative to the final published list price. This column, while not as important as the first one, still yields important insights as to the direction of negotiations. The “DOM” column tracks the days on market for all properties sold and listed and helps frame expected marketing time. Finally, the “CtL” label stands for “contract-to-list” ratio. It is the number of pending sales divided by the total number of listings. A low ratio means many properties are sitting on the open market waiting for offers. A high ratio indicates properties are being absorbed by the market quickly, commonly referred to as a “seller’s market.”

As of this post date, there are more properties waiting for offers than are under contract.

The following table more closely examines DOM as well as CDOM (cumulative days on market). CDOM is also an important metric as homes are often taken off the market and then subsequently relisted (typically at a lower price). The CDOM metric can give you a better idea of total expected marketing time. The table breaks out DOM & CDOM by price segment:

2019-08-03_17-52-20

Let’s wrap up the neighborhood statistics overview with the following table showing the sales terms in the market over the last two years:

2019-08-03_17-58-54

Unsurprisingly, there is a substantial cash market among waterfront homes.

Let’s conclude our tour of waterfront properties in Lake Oswego with a histogram analysis of the market:

Histogram Analysis

Age

Age

The median age for the waterfront market is 55 years; however, a substantial number of properties are 35 years old or newer.

Bathroom Count

Bath

Two to four bathroom homes are typical for the market.

Bedroom Count

BR

The vast majority of homes have between three to five bedrooms.

Garage Stall Count

Gar

Most properties have either a two or three-car garage.

Total Square Footage

Total SF

This metric includes above-grade living area and basement space for a combined figure. The median total square footage around the lake is ~3,600 sq. ft.

Gross Living Area

GLA

Gross living area only consider non-basement living space. Often the market reacts more strongly to gross living area, usually applying a discount to basement space. Median gross living area is approximately 2,900 sq. ft.

Level Count

Levels

The majority of properties are two to three levels.

Lot Size

Lot

There are some acreage properties along the lake, however, the median lot size is 0.21 acres (~9,150 sq. ft.).

# of Sales

# Per Yr

The number of sales along the lake have been trending higher this year as compared to the previous two.

Sales Price

Sales Price

This histogram includes sales prices over a 20-year period. The median sales price over the last 20 years is: $1,290,000; and the median sales price over the last two years is: $1,765,000.

The highest sales price obtained among waterfront properties in Lake Oswego (on the open market) is $6,950,000 on 6/20/2000. The home is nearly 14,000 square feet; sits on 1.65 acres; has 7 bedrooms; 9 full bathrooms and 4 half bathrooms (powder rooms) and custom European-style architecture.

The highest listing was for $19,500,000. This was for the property on Jantzen Island.

Jantzen-sm

It is the only private island on Oswego Lake. The home sits on 5 acres, is 13,500 square feet, and is reachable by a gated private bridge. According to an article in the The Oregonian, the property was purchased for $2.2 million in cash back in 1987. $5 million was spent improving the property and it was listed on 9/08/2008 for nearly $20 million. It stayed on the market for that price for more than a year and a half before the listing was cancelled. It was relisted again about a half year later at a reduced price of $15 million, but it stayed on the market for over three years without selling. Had, it sold for even $10 million, it would have set a record for the Lake Oswego market.

So, there you have it, a market overview of waterfront properties on Oswego Lake!

Appraisal Reports

If you are a homeowner and are looking to sell your home, you would greatly benefit from a prelisting appraisal. Our firm will bring high-level analytics to your report and give you a sound understanding of the current market.

If you are an agent and need detailed neighborhood analysis, or analysis of specific areas or specific segments of the market, please contact us and we can generate a custom report to help you frame a listing price for your client!

South Portland—Neighborhood Analysis of Single-Family Residential Homes (July 2019)

The South Portland neighborhood is one of Portland’s waterfront communities, bordering the Willamette River. It is connected to the east side of the city via four bridges and boasts some of the city’s modern skyscrapers—including the John Ross Tower, Portland’s largest residential structure. Shopping, fine dining, numerous parks, recreation, OHSU with its aerial tramway, and major employment centers are all features of this dynamic neighborhood.

2019-07-27_8-02-02

Despite being part of Portland’s urban core, the South Portland neighborhood has a thriving detached single-family home market.

Appraisers endeavor to take the measure of a neighborhood with a variety of tables, charts, and graphs. It helps them to frame the value opinion and see how the subject property relates to the neighborhood as a whole. Before we dive in, a…

Quick Note

The following information is based on detached single-family residential homes that were sold and/or listed on the open market as reported by RMLS—the primary MLS service for the City of Portland. Data was pulled from the year 2000 to the present date. The data export was checked, validated, and scrubbed of obvious errors using custom tools developed by the author. With that out of the way, let’s look at some neighborhood stats.

Neighborhood Statistics Overview

The following table summarizes important metrics for the neighborhood. Each column is independent of the others and the basement square foot column reflects only properties with a basement.

Neigh Stats Corrected

There has been relatively little new construction in the neighborhood with ~5.8% of all sales having been new homes.

The following scatter plot shows all closed-sale detached single-family residences  (with a red trendline):

DOS vs SP

The neighborhood suffered during the housing crisis, but has recovered with prices generally higher than they were before the crash. The red trendline shows prices have leveled and have even dipped a bit. This is further borne out by a review of average and median sales prices over the last two years:

Two Years

Percentile rank is a way of seeing price bands for the neighborhood. For instance, the 50th percentile, or median rank, shows that half of all sales since the year 2000 have been under $359,000. Prices are fairly clustered up to the 90th percentile where the upper range begins to balloon:

Percentiles-2

The following table shows important marketing information for both the last two years and since the year 2000:

OLP

The “SP/OLP” label stands for “sales price/original list price” ratio. This is an important metric, as it shows what the particular property sold for relative to the original list price that was advertised. The “SP/LP” column tracks what the sales price was relative to the final published list price. This column, while not as important as the first one, still yields important insights as to the direction of negotiations. The “DOM” column tracks the days on market for all properties sold and listed and helps frame expected marketing time. Finally, the “CtL” label stands for “contract-to-list” ratio. It is the number of pending sales divided by the total number of listings. A low ratio means many properties are sitting on the open market waiting for offers. A high ratio indicates properties are being absorbed by the market quickly, commonly referred to as a “seller’s market.”

As of this post date, there are more properties waiting for offers than are under contract. The CtL is a fluid metric, however, and may not be indicative of long-term trends.

The following table more closely examines DOM as well as CDOM (cumulative days on market). CDOM is also an important metric as homes are often taken off the market and then subsequently relisted (typically at a lower price). The CDOM metric can give you a better idea of total expected marketing time. The table breaks out DOM & CDOM by price segment:

By Segments

Let’s wrap up the neighborhood statistics overview with the following table showing the sales terms in the market over the last two years:

2019-07-27_9-57-18

While conventional financing is predominant, there is a substantial cash market.

Let’s conclude our tour of South Portland with a histogram analysis of the neighborhood:

Histogram Analysis

Age

Age

Most properties in the neighborhood are over a half century old. With the oldest home being a 920 sq. ft. cottage built while Abraham Lincoln was still president of the United States.

Bathroom Count

Bathroom

A two-bathroom home is the most typical for the market, with a single bathroom being fairly common as well.

Bedroom Count

BR

The vast majority of homes are have three bedrooms.

Garage Stall Count

Gar Fixed

There is near parity between properties with no garage and a one-car garage. A two-car garage is not uncommon either.

Total Square Footage

2019-07-27_10-43-38

This metric includes above-grade living area and basement space for a combined figure. The median total square footage for the neighborhood is ~2,200 sq. ft.

Gross Living Area

GLA

Gross living area only consider non-basement living space. Often the market reacts more strongly to gross living area, usually applying a discount to basement space. Median gross living area is approximately 1,550 sq. ft.

Level Count

Levels

The majority of properties are three levels in this neighborhood.

Lot Size

Lot Size

The lion’s share of properties are on lots 0.06 ac – 0.119 acres (~2,610 sq. ft. – ~5,180 sq. ft.). 

Sales Price

Sales Price

This histogram includes sales prices over a 20-year period. The median sales price over the last 20 years is: $359,000; and the median sales price over the last 2 years is: $530,533.

The highest sales price obtained in the neighborhood (on the open market) was $1,500,000 on 6/13/2018. The home is over 6,000 total square feet; sits on one of the larger lots for the neighborhood; has a sauna & pool; and has a studio!

# of Sales

Sales Per Yr

The number of sales in the neighborhood have been trending lower this year as compared to the previous two.

So, there you have it, a market overview for the South Portland neighborhood!

Appraisal Reports

If you are a homeowner and are looking to sell your home, you would greatly benefit from a prelisting appraisal. Our firm will bring high-level analytics to your report and give you a sound understanding of the current market.

If you are an agent and need detailed neighborhood analysis, or analysis of specific areas or specific segments of the market, please contact us and we can generate a custom report to help you frame a listing price for your client!

 

What is a Histogram? Why is it Important in Real Estate Data Analysis for Portland, Oregon?

Appraisers endeavor to take the measure of a neighborhood with a variety of charts and graphs. It helps them to frame the value opinion and see how the subject property relates to the neighborhood or market area as a whole. 

A histogram is a graphical display of data using bars of varying heights. In a histogram, each bar groups data for a single variable into ranges (or bins). Taller bars show that more data falls in that range. A histogram may be used to display the shape and spread of the data of the real estate market and illustrate trends of properties that have sold and/or are listed. They’re a great visual tool!

Example

Lot Size

The above histogram depicts the various lot sizes for detached single-family residences in the Ladd’s Addition historic district. The data represents sales and/or listings in the RMLS database from the year 2000 to July 2019. What can we learn from the above chart?

1) There is a tight uniformity of lot sizes in this district. 57% of the data falls into just one bin! 
2) 87% of the data falls into the bins representing lots from 0.08 acres to 0.159 acres (~3,485 sq. ft. – ~6,926 sq. ft.). This shows that large lots in Ladd’s addition are rare.
3) Properties outside the aforementioned bins would require more careful analysis by the appraiser (or agent).
4) Dealing with extreme outliers (properties on tiny lots or larger ones for the district) may require the use of a number of data science and appraisal techniques as comparable properties would be hard to find.
5) There is little developer potential for subdividing lots as virtually no lot is large enough to be reasonably partitioned.

Portland Real Estate Market

As you can see, you can squeeze a lot of information out of just one histogram. These charts can be used to display many different variables: age, gross living area, bedroom & bathroom count, sales prices, etc. By evaluating histograms of several key metrics, one can quickly see how a particular property fits into a neighborhood (or district) as a whole.

The Portland market is eclectic and appraising unusual properties requires the careful application of local expertise, the tools of statistics and data science, and sound judgement.  

Appraisal Reports

If you are a homeowner and are looking to sell your home, you would greatly benefit from a prelisting appraisal. Our firm will bring high-level analytics to your report and give you a sound understanding of the current market.

If you are an agent and need detailed neighborhood analysis, or analysis of specific areas or specific segments of the market, please contact us and we can generate a custom report to help you frame a listing price for your client!

Ladd’s Addition—Neighborhood Analysis of Single-Family Residential Homes (July 2019)

Ladd’s Addition is a unique historic district in the city of Portland that is known for its diagonal street pattern radiating from a central park spoke—the Ladd Circle Park & Rose Gardens. Ladd’s addition is named after the 19th century Portland mayor, William S. Ladd. This historic district is part of the Hosford-Abernethy neighborhood. The street layout is easy to spot from aerial maps of the city and clearly delineates the district’s boundaries.

2018-11-07_18-10-38

Appraisers endeavor to take the measure of a neighborhood with a variety of charts and graphs. It helps them to frame the value opinion and see how the subject property relates to the neighborhood as a whole. For this blog post we will use the venerable histogram to better understand the single-family residential market for Ladd’s Addition.

A histogram is a graphical display of data using bars of different heights. In a histogram, each bar groups numbers into ranges. Taller bars show that more data falls in that range. A histogram may be used to display the shape and spread of the data of the real estate market and illustrate trends of properties that have sold and/or are listed. They’re a great visual tool!

The following information is based on detached single-family residential homes that were sold and/or listed on the open market as reported by RMLS—the primary MLS service for the City of Portland. Data was pulled from the year 2000 to the present date.

Age

Age

Most properties within Ladd’s Addition were built around 1900-1930. This is reflected in the age histogram showing most of the homes falling in the 91-97 years bracket. New/newer constructions in Ladd’s addition is nearly unheard of.

35 different homes that sold over the last 20 years were on the National Register of Historic Places.

Bathroom Count

Bathroom

Most homes in the neighborhood have two bathrooms; but a home with only one bathroom is not uncommon. One home had the equivalent of 5 & 1/2 bathrooms. There is no waiting in that house!

Bedroom Count

Bedroom

Two to four bedrooms is the norm, with a few outliers having either one or 6-7 bedrooms.

Garage Stall Count

GAR

A one-car garage is the norm for Ladd’s Addition. However, a substantial number of homes in the dataset have either no garage at all or an extra garage stall.

Total Square Footage

Total SF

This metric includes above-grade living area and basement space for a combined figure. The median total square footage for the neighborhood is 2,500 sq. ft. There are some larger homes in the area, with 32 sales/listings being at or above 4,800 sq. ft.

Gross Living Area

GLA

Gross living area only consider non-basement living space. Often the market reacts more strongly to gross living area, usually applying a discount to basement space. Median gross living area is approximately 1,700 sq. ft.

Level Count

# of Levels

The majority of properties are three levels in this neighborhood.

Lot Size

Lot Size

The vast majority of properties are on lots 0.120 ac – 0.129 acres (~5,227 sq. ft. – ~5,619 sq. ft.). There is substantial uniformity of lot sizes in this neighborhood.

Sales Price

Sales Price

This histogram includes sales prices over a 20-year period. The highest sales price obtained in the neighborhood (on the open market) was $1,105,000 on 3/17/2017.

# of Sales

# of Sales

Ladd’s Addition doesn’t have a substantial turnover of homes each year. The fewest sales in a year was back in 2015, when only 10 single-family residential homes sold. 2016-2018 averaged 20 sales per year. This year looks to be trending lower. Year-to-date sales are only 8 and, if the trend holds, 2019 may signal a cooling off of the number of sales.

So, there you have it, a brief histogram overview of one of Portland’s most iconic neighborhoods!

Appraisal Reports

If you are a homeowner and are looking to sell your home, you would greatly benefit from a prelisting appraisal. Our firm will bring high-level analytics to your report and give you a sound understanding of the current market.

If you are an agent and need detailed neighborhood analysis, or analysis of specific areas or specific segments of the market, please contact us and we can generate a custom report to help you frame a listing price for your client!

Using the R Programming Language to Produce Correlation Matrices & Correlograms for Residential Appraisal Reports

As I mention in the bio for this blog, one of the most influential individuals in my professional development as an appraiser is George Dell. He is a nationally recognized valuation expert who teaches a method he calls “Evidence Based Valuation©.”

(If you’ve never taken a class from George, stop reading this blog post, go to his website, register for one of his classes—oh, it’s on the other side of the country? So what? Register!—and then resume reading this post. You’re back? Great.)

George’s classes emphasizes reproducible appraisal findings and deemphasizes subjectivity and guessing. Reports that follow George’s tenets are clearer, more logical, and more convincing to the end user. I can personally attest to a substantial increase in work quality.

George is on a bit of a crusade to get appraisers to use more sophisticated analytical tools. One such tool is the programming language R.

R can be a bit intimidating for appraisers—even for those who possess advanced Excel skills. However, one does not have to be a seasoned computer programmer to immediately start using it to produce charts and graphs that can aid in analysis and improve a report’s quality.

Let me walk you through the steps needed to produce this chart, known as a correlogram:

Rplot

 

Per the STHDA website, a website that shares information on statistical tools, a correlation test is “used to evaluate the association between two or more variables.” Typically, a number is assigned that can range from -1 to +1. If two variables, say “Close_Price” and “Total_SF” have a correlation of +0.74, that means there is a strong positive association between the two. (In reports, this is often expressed as a percentage.) If the number were negative, it would mean as one variable goes up the other goes in the opposite direction. A good example of this in my market is the relationship between “Year_Built” and “Acres.” Newer homes tend to be on smaller lots as often a larger lot is purchased and partitioned by a developer.

A correlation matrix, per STHDA, “is used to investigate the dependence between multiple variables at the same time. The result is a table containing the correlation coefficients between each variable and the others.”

A correlogram is a visualization of the correlation statistics.

Once you get the hang of the process, you can start producing correlograms in under 5 minutes using R. It allows for fantastic support in an appraisal report.

Correlation matrices do, however, have their limitations and need to be used carefully. Again, I strongly recommend taking George Dell’s “Stats, Graphs & Data Science¹” class to obtain a better understanding.

Without further ado, let’s begin:

Step 1:

Install the R programming language: https://cran.r-project.org/

R runs on Windows, Mac, and Linux.

Step 2:

Download R Studio (a graphical overlay to R) from this site.  R Studio is a free program. Make sure you choose the desktop option. (If the site is asking you to pay $30,000 a year, you accidentally clicked on the commercial license product . 😊)

Step 3:

Install the “PerformanceAnalytics” package.

Click the “Packages” tab in the bottom-right pane. Click “Install.” Type in the name of the package (it will autocomplete based on what is available on CRAN).

2

Note: You can customize the look of R Studio, I’ve chosen a darker theme as it is easier on the eyes, so don’t be concerned if my screenshots don’t exactly match what you see.

Step 4:

Open the R script file that contains the code.

You have a number of options here. To save yourself time, you can simply click this link to download a prepared R script file I am hosting on Dropbox. On Dropbox, click the download button on the upper right-hand corner and you will get a file that looks something like this, depending on your folder view settings:

2018-12-07_13-30-07

When you double-click on the R script file R Studio will automatically open if it is closed or, if already open, simply add the code to the top-left pane. The code is just three lines long and will look something like this on your display:

zzzzz

The first 5 lines in blue are just comments I’ve added and are not code. By putting a “#” sign in front of comments, I am telling the program not to treat the text as code.

If you prefer not to download the prepared file, simply copy the text from the Dropbox display and paste it into a new R script.

Step 5:

Import the data from an Excel file. Click on the “Import Dataset” tab in the top right-hand pane, and click “From Excel…”:

a

If you try to import a CSV file you’ll get this error:

CSV

Future versions of R Studio may be able to handle CSV files directly, but for now, just make sure the file is an actual Excel file.

You’ll get a preview of your data that looks like this:

b

For appraisal work, you’ll want to start off working with variables that can be put in the “double” type format (a computer variable type that permits greater numerical precision). The type of variables we will want in our correlation matrix are, in brief, ones that are interval or ratio variables like “Close_Price” where it makes sense to say that a home is twice as expensive as another. (Working with a class of variables known as “categorical variables” is beyond the scope of this blog post—a Q3 home is not twice as nice as a Q6 home.)

I’ve made some custom Excel templates that allows me to take the data exported from my local MLS and it put it into the format I want. I then save just that tab’s information to a separate file labeled “Correlation Data.”

Pro Tips: a) For column headers, use the underscore to separate words rather than a blank space. So, “Total_SF” rather than “Total SF” is safer. b) Don’t use the “#” sign for any headers as that can mess up some R package’s ability to interpret. So rather than “#_Acres” put “No_Acres” or just “Acres.” c) Make sure “Close_Date” is in Excel “serial date” format.

Once, you’ve looked the data over, simply click the “Import” button at the bottom right to bring it into R.

Step 5:

Highlight the three lines of code and click the “Run” button:

c

Well, that part was easy!

(If you highlighted the comments above the code, it will have no effect on the outcome.)

Your graph will appear in the “Plots” tab at the bottom-right pane. Simpy click the “Export” option and you can save as an image or PDF and stick it in your report:

d

Once your templates are all set up, you can produce this chart in just minutes.

Correlograms can be very powerful. Reading from the top row, “Close_Price,” and reading across allows you to see how all the other variables correlate with “Close_Price.” If, “Acres” and “Close_Price” show virtually no correlation, you can point to the correlogram as proof that no lot size adjustment is needed.

There are many different types of correlograms that you can do with R. In a future post, I’ll review a number of them!

Let me know your thoughts in the comments section. If you have a question, don’t hesitate to ask!

And, finally, take George Dell’s class!