Using R With Excel

Kevin Feasel



David Smith walks us through various ways to integrate R and Excel:

If you’re familiar with analyzing data in Excel and want to learn how to work with the same data in R, Alyssa Columbus has put together a very useful guide: How To Use R With Excel. In addition to providing you with a guide for installing and setting up R and the RStudio IDE, it provide a wealth of useful tips for working with Excel data in R, including:

  • To import Excel data into R, use the readxl package

  • To export Excel data from R, use the openxlsx package

  • How to remove symbols like “$” and “%” from currency and percentage columns in Excel, and convert them to numeric variables suitable for analysis in R

  • How to do computations on variables in R, and a list of common Excel functions (like RAND and VLOOKUP) with their R equivalents

  • How to emulate common Excel chart types (like histograms and line plots) using R plotting functions

David also shows how to run R within Excel.  One of the big benefits of readxl is that it doesn’t require Java; most other Excel readers do.

Related Posts

Donating To The R Foundation

Mark Niemann-Ross explains how you can donate to the R Foundation: I benefit from the work of the R Foundation. They oversee the language, but also encourage a healthy ecosystem. CRAN happens because of them. Updates to R happen because of them. useR! happens because of them. Every day, you and I are the recipients […]

Read More

Timing Means Of Groups With R

John Mount shares some performance measures pitting data.table against various dplyr methods for calculating grouped means: In this reproduction attempt we see:– The dplyr time being around 0.05 seconds. This is about 5 times slower than claimed.– The dplyr sum()/n() time is about 0.2 seconds, about 5 times faster than claimed.– The data.table time being around 0.004 seconds. This is about three times as […]

Read More


September 2018
« Aug Oct »