Tag Archives: #rstudio

Moving from Excel to R-What Software Do I Need?

Everyone knows what Microsoft Excel is, right? Either you have a copy that came with your PC or you’re on the Office 365 subscription model at $69/year for a personal copy $99/year for 5 users (my subscription of choice). Money flows into Microsoft coffers, satisfying shareholders and most of the greater Seattle area given Microsoft’s reach. Make more Seattleites happy by ordering your copy through Amazon!

R is very different (free). It is open source software available under a public license and is maintained by a group of volunteers (free). Get your free copy here.

R on its own is usable. However, it was designed from the ground up to allow for additions to make it more useful.

RStudio, an open source integrated development environment for R, makes using R much easier for folks like me who are not full-time programmers (also free). RStudio sits on top of R and extends usability significantly. RStudio offers the same basic terminal R does but also gives you additional really useful windows and information. I’ll discuss RStudio in the future but if you can’t wait, here’s a link with more information about RStudio.

Here’s an article: 9 Reasons to use RStudio. Or Top 6 Reasons you need to be using RStudio. Get your free copy of RStudio here.

You can extend the usability of R by adding packages. Packages are bundles of R code with explanation and data examples. Data Camp has beginner’s guide for R Packages here. Managing packages is one of RStudio’s strengths, making it easy to install packages. These are free too.

ggplot is a package for creating graphics and should be the first package you download. Two more packages of interest to appraisers just getting into R are tidyverse, a collection of R packages for data science, and rmarkdown, a package for adding R output to documents. You can learn more about all three here.

To summarize, download for free R, RStudio, and the ggplot2, tidyverse, and rmarkdown packages. I’ll talk more about packages in the future as I explore R’s functionality.

Download Pages and Instructions

 

Why I’m Switching to R

I’ve come to rely heavily on Microsoft Excel over the years to do my work as a residential appraiser. So much so that I teach classes to other appraisers on how to use Excel in their work. However, after taking George Dell’s first R for Appraisers class recently, I’ve decided to completely revise my workflow and replace what I do in Excel as much as possible with R.

What’s R? might be your first question. R is a free data analytics software package used widely for data analysis. Most university economics programs teach with R these days. Here’s the official description (link). You can download a free copy here.

However, if you’re going to use R, you need to use RStudio, the free integrated development environment for R. It provides a way of seeing more and doing more with the basic R programming language and really extends what you can do with R. Free copy and more information here.

Why would someone who has invested heavily in developing skills in Excel move to a brand new software package? Here are my reasons:

  • Data Analytics vs. Spreadsheets Data Retention-R is software designed for data analytics from the ground up. That’s what appraisers do, relatively specialized data analytics. Spreadsheets were designed to replace paper ledgers. You can scribble all over a sheet. If you’re not careful, you’re very likely to write on your numbers and make a mess. This is a problem if you’re trying to preserve your data in the future, say if you need to maintain workfiles like appraisers are legally required to do. R solves this data retention issue.
  • Reusable Processes-R is designed from the ground up to be reusable. Drop your data in and get your results. I’ve done a lot to get Excel to work that way for me but I still do a ton of manual processes each time I work on an appraisal. Once I know what I’m doing in R, I’ll have a lot fewer manual processes to deal with. It will be easy for someone else to audit my analysis for appraising.
  • Superior Analysis-I use pivot tables a lot in Excel. In fact, I teach a class on using pivot tables for appraisers. The big drawback with Excel pivot tables is that I can’t include median values as part of my summaries without a lot of work (coding or buying someone else’s product). This is not an issue in R.
  • Personal Growth-R gives me an opportunity to learn new ways to analyze data, the underlying job function that has given me the most satisfaction throughout my career. I’m excited to learn new ways to do my job better and I expect big changes once I’ve completed the move to R. Also, if this appraising gig doesn’t work out, with R I’ll have a job skill in demand in other industries.

I plan to document my migration from Excel to R here. I’ll share resources I find useful and will discuss issues I run into. I also plan to describe the benefits and drawbacks. This is mainly for me, and maybe Abdur Abdul-Malik and Bruce Hahn, the other appraisers I know making the same journey. And maybe I can help George Dell come up with ideas on how to spread the word to the rest of the industry. Thanks again George for the inspiration.