- Preleminary tasks
- Copying data from Excel and import into R
- Importing Excel files into R using readxl package
- Importing Excel files using xlsx package
- Related articles
Previously, we described the essentials of R programming and some best practices for preparing your data. We also provided quick start guides for reading and writing txt and csv files using R base functions as well as using a most modern R package named readr, which is faster (X10) than R base functions.
In this article, you’ll learn how to read data from Excel xls or xlsx file formats into R. This can be done either by:
- copying data from Excel
- using readxl package
- or using xlsx package
Launch RStudio as described here: Running RStudio and setting up your working directory
Prepare your data as described here: Best practices for preparing your data
Copying data from Excel and import into R
On Windows system
Open the Excel file containing your data: select and copy the data (ctrl + c)
Type the R code below to import the copied data from the clipboard into R and store the data in a data frame (my_data):
my_data <- read.table(file = "clipboard", sep = "\t", header=TRUE)
On Mac OSX system
Select and copy the data (Cmd + c)
Use the function pipe(pbpaste) to import the data you’ve copied (with Cmd + c):
my_data <- read.table(pipe("pbpaste"), sep="\t", header = TRUE)
Importing Excel files into R using readxl package
The readxl package, developed by Hadley Wickham, can be used to easily import Excel files (xls|xlsx) into R without any external dependencies.
Installing and loading readxl package
Using readxl package
The readxl package comes with the function read_excel() to read xls and xlsx files
- Read both xls and xlsx files
# Loading library("readxl") # xls files my_data <- read_excel("my_file.xls") # xlsx files my_data <- read_excel("my_file.xlsx")
The above R code, assumes that the file “my_file.xls” and “my_file.xlsx” is in your current working directory. To know your current working directory, type the function getwd() in R console.
- It’s also possible to choose a file interactively using the function file.choose(), which I recommend if you’re a beginner in R programming:
my_data <- read_excel(file.choose())
If you use the R code above in RStudio, you will be asked to choose a file.
- Specify sheet with a number or name
# Specify sheet by its name my_data <- read_excel("my_file.xlsx", sheet = "data") # Specify sheet by its index my_data <- read_excel("my_file.xlsx", sheet = 2)
- Case of missing values: NA (not available). If NAs are represented by something (example: “—”) other than blank cells, set the na argument:
my_data <- read_excel("my_file.xlsx", na = "---")
Importing Excel files using xlsx package
The xlsx package, a java-based solution, is one of the powerful R packages to read, write and format Excel files.
Installing and loading xlsx package
Using xlsx package
There are two main functions in xlsx package for reading both xls and xlsx Excel files: read.xlsx() and read.xlsx2() [faster on big files compared to read.xlsx function].
The simplified formats are:
read.xlsx(file, sheetIndex, header=TRUE) read.xlsx2(file, sheetIndex, header=TRUE)
- file: file path
- sheetIndex: the index of the sheet to be read
- header: a logical value. If TRUE, the first row is used as column names.
Example of usage:
library("xlsx") my_data <- read.xlsx(file.choose(), 1) # read first sheet
Read more about for reading, writing and formatting Excel files:
Read Excel files using readxl package: read_excel(file.choose(), sheet = 1)
- Read Excel files using xlsx package: read.xlsx(file.choose(), sheetIndex = 1)
This analysis has been performed using R (ver. 3.2.3).
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