Quickly export multiple R objects to an Excel Workbook

[This article was first published on statMethods blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Working with a business audience, I am frequently called upon to send analytic results to clients in the form of Excel Workbooks. The xlsx package facilitates exporting tables and datasets Excel, but I wanted a very simple function that would let me easily export an arbitrary number of R objects to an Excel Workbook in a single call. Each object should appear on in own worksheet, and the worksheets should be named after their objects.

Specifically, the function

save.xlsx("myworkbook.xlsx", mtcars, Titanic, AirPassengers, state.x77)

should save the R objects mtcars (a data frame),  Titanic (a table),  AirPassengers (a time series) and state.x77 (a matrix) to the workbook myworkbook.xlsx. Each object should be in it’s own worksheet and the worksheet should take on the name of the object.

One solution was to write a wrapper for write.xlsx() function in the xlsx package.

save.xlsx <- function (file, ...)
  {
      require(xlsx, quietly = TRUE)
      objects <- list(...)
      fargs <- as.list(match.call(expand.dots = TRUE))
      objnames <- as.character(fargs)[-c(1, 2)]
      nobjects <- length(objects)
      for (i in 1:nobjects) {
          if (i == 1)
              write.xlsx(objects[[i]], file, sheetName = objnames[i])
          else write.xlsx(objects[[i]], file, sheetName = objnames[i],
              append = TRUE)
      }
      print(paste("Workbook", file, "has", nobjects, "worksheets."))
}

Then

save.xlsx("myworkbook.xlsx", mtcars, Titanic, AirPassengers, state.x77)
[1] "Workbook myworkbook.xlsx has 4 worksheets."

spreadsheet

The method will work for data frames, matrices, time series, and tables, and has simplified my workflow greatly.

To leave a comment for the author, please follow the link and comment on their blog: statMethods blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)