Previously, we described the essentials of R programming and 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. We also described different ways for reading data from Excel files into R.
Launch RStudio as described here: Running RStudio and setting up your working directory
Writing 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 writing both xls and xlsx Excel files: write.xlsx() and write.xlsx2() [faster on big files compared to write.xlsx function].
The simplified formats are:
write.xlsx(x, file, sheetName = "Sheet1", col.names = TRUE, row.names = TRUE, append = FALSE) write.xlsx2(x, file, sheetName = "Sheet1", col.names = TRUE, row.names = TRUE, append = FALSE)
- x: a data.frame to be written into the workbook
- file: the path to the output file
- sheetName: a character string to use for the sheet name.
- col.names, row.names: a logical value specifying whether the column names/row names of x are to be written to the file
- append: a logical value indicating if x should be appended to an existing file.
Example of usage: the following R code will write the R built-in data sets - USArrests, mtcars and iris - into the same Excel file:
library("xlsx") # Write the first data set in a new workbook write.xlsx(USArrests, file = "myworkbook.xlsx", sheetName = "USA-ARRESTS", append = FALSE) # Add a second data set in a new worksheet write.xlsx(mtcars, file = "myworkbook.xlsx", sheetName="MTCARS", append=TRUE) # Add a third data set write.xlsx(iris, file = "myworkbook.xlsx", sheetName="IRIS", append=TRUE)
Read more about for reading, writing and formatting Excel files:
This analysis has been performed using R (ver. 3.2.3).
Show me some love with the like buttons below... Thank you and please don't forget to share and comment below!!
Montrez-moi un peu d'amour avec les like ci-dessous ... Merci et n'oubliez pas, s'il vous plaît, de partager et de commenter ci-dessous!
Recommended for You!
R Graphics Essentials for Great Data Visualization: 200 Practical Examples You Want to Know for Data Science
Want to Learn More on R Programming and Data Science?
Follow us by Email On Social Networks: