[r] Easy way to export multiple data.frame to multiple Excel worksheets

I am surprised to find that there is no easy way to export multiple data.frame to multiple worksheets of an Excel file? I tried xlsx package, seems it can only write to one sheet (override old sheet); I also tried WriteXLS package, but it gives me error all the time...

My code structure is like this: by design, for each iteration, the output dataframe (tempTable) and the sheetName (sn) got updated and exported into one tab.

for (i in 2 : ncol(code)){ 
        ...
        tempTable <- ...
        sn <- ...
        WriteXLS("tempTable", ExcelFileName = "C:/R_code/../file.xlsx",
              SheetNames = sn);
}

I can export to several cvs files, but there has to be an easy way to do that in Excel, right?

For me, WriteXLS provides the functionality you are looking for. Since you did not specify which errors it returns, I show you an example:

Example

library(WriteXLS)
x <- list(sheet_a = data.frame(a=letters), sheet_b = data.frame(b = LETTERS))
WriteXLS(x, "test.xlsx", names(x))

Explanation

If x is:

• a list of data frames, each one is written to a single sheet
• a character vector (of R objects), each object is written to a single sheet
• something else, then see also what the help states:

More on usage

?WriteXLS

shows:

`x`: A character vector or factor containing the names of one or
     more R data frames; A character vector or factor containing
     the name of a single list which contains one or more R data
     frames; a single list object of one or more data frames; a
     single data frame object.

Solution

For your example, you would need to collect all data.frames in a list during the loop, and use WriteXLS after the loop has finished.

Session info

• R 3.2.4
• WriteXLS 4.0.0

I'm not familiar with the package WriteXLS; I generally use XLConnect:

library(XLConnect)
##
newWB <- loadWorkbook(
  filename="F:/TempDir/tempwb.xlsx",
  create=TRUE)
##
for(i in 1:10){
  wsName <- paste0("newsheet",i)
  createSheet(
    newWB,
    name=wsName)
  ##
  writeWorksheet(
    newWB,
    data=data.frame(
      X=1:10,
      Dataframe=paste0("DF ",i)),
    sheet=wsName,
    header=TRUE,
    rownames=NULL)
}
saveWorkbook(newWB)

This can certainly be vectorized, as @joran noted above, but just for the sake of generating dynamic sheet names quickly, I used a for loop to demonstrate.

I used the create=TRUE argument in loadWorkbook since I was creating a new .xlsx file, but if your file already exists then you don't have to specify this, as the default value is FALSE.

Here are a few screenshots of the created workbook:

Many good answers here, but some of them are a little dated. If you want to add further worksheets to a single file then this is the approach I find works for me. For clarity, here is the workflow for openxlsx version 4.0

# Create a blank workbook
OUT <- createWorkbook()

# Add some sheets to the workbook
addWorksheet(OUT, "Sheet 1 Name")
addWorksheet(OUT, "Sheet 2 Name")

# Write the data to the sheets
writeData(OUT, sheet = "Sheet 1 Name", x = dataframe1)
writeData(OUT, sheet = "Sheet 2 Name", x = dataframe2)

# Export the file
saveWorkbook(OUT, "My output file.xlsx")

EDIT

I've now trialled a few other answers, and I actually really like @Syed's. It doesn't exploit all the functionality of openxlsx but if you want a quick-and-easy export method then that's probably the most straightforward.

I do it in this way for openxlsx using following function

mywritexlsx<-function(fname="temp.xlsx",sheetname="Sheet1",data,
                  startCol = 1, startRow = 1, colNames = TRUE, rowNames = FALSE)
{
  if(! file.exists(fname))
    wb = createWorkbook()
  else
   wb <- loadWorkbook(file =fname)
  sheet = addWorksheet(wb, sheetname)

  writeData(wb,sheet,data,startCol = startCol, startRow = startRow, 
          colNames = colNames, rowNames = rowNames)
  saveWorkbook(wb, fname,overwrite = TRUE)
}

I had this exact problem and I solved it this way:

library(openxlsx) # loads library and doesn't require Java installed

your_df_list <- c("df1", "df2", ..., "dfn")

for(name in your_df_list){
  write.xlsx(x = get(name), 
             file = "your_spreadsheet_name.xlsx", 
             sheetName = name)
}

That way you won't have to create a very long list manually if you have tons of dataframes to write to Excel.

You can also use the openxlsx library to export multiple datasets to multiple sheets in a single workbook.The advantage of openxlsx over xlsx is that openxlsx removes the dependencies on java libraries.

Write a list of data.frames to individual worksheets using list names as worksheet names.

require(openxlsx)
list_of_datasets <- list("Name of DataSheet1" = dataframe1, "Name of Datasheet2" = dataframe2)
write.xlsx(list_of_datasets, file = "writeXLSX2.xlsx")

I regularly use the packaged rio for exporting of all kinds. Using rio, you can input a list, naming each tab and specifying the dataset. rio compiles other in/out packages, and for export to Excel, uses openxlsx.

library(rio)

filename <- "C:/R_code/../file.xlsx"

export(list(sn1 = tempTable1, sn2 = tempTable2, sn3 = tempTable3), filename)

I do this all the time, all I do is

WriteXLS::WriteXLS(
    all.dataframes,
    ExcelFileName = xl.filename,
    AdjWidth = T,
    AutoFilter = T,
    FreezeRow = 1,
    FreezeCol = 2,
    BoldHeaderRow = T,
    verbose = F,
    na = '0'
  )

and all those data frames come from here

all.dataframes <- vector()
for (obj.iter in all.objects) {
  obj.name <- obj.iter
  obj.iter <- get(obj.iter)
  if (class(obj.iter) == 'data.frame') {
      all.dataframes <- c(all.dataframes, obj.name)
}

obviously sapply routine would be better here

Incase data size is small, R has many packages and functions which can be utilized as per your requirement.

write.xlsx, write.xlsx2, XLconnect also do the work but these are sometimes slow as compare to openxlsx.

So, if you are dealing with the large data sets and came across java errors. I would suggest to have a look of "openxlsx" which is really awesome and reduce the time to 1/12th.

I've tested all and finally i was really impressed with the performance of openxlsx capabilities.

Here are the steps for writing multiple datasets into multiple sheets.

 install.packages("openxlsx")
 library("openxlsx")

    start.time <- Sys.time()

    # Creating large data frame
    x <- as.data.frame(matrix(1:4000000,200000,20))
    y <- as.data.frame(matrix(1:4000000,200000,20))
    z <- as.data.frame(matrix(1:4000000,200000,20))

    # Creating a workbook
    wb <- createWorkbook("Example.xlsx")
    Sys.setenv("R_ZIPCMD" = "C:/Rtools/bin/zip.exe") ## path to zip.exe

Sys.setenv("R_ZIPCMD" = "C:/Rtools/bin/zip.exe") has to be static as it takes reference of some utility from Rtools.

Note: Incase Rtools is not installed on your system, please install it first for smooth experience. here is the link for your reference: (choose appropriate version)

https://cran.r-project.org/bin/windows/Rtools/ check the options as per link below (need to select all the check box while installation)

https://cloud.githubusercontent.com/assets/7400673/12230758/99fb2202-b8a6-11e5-82e6-836159440831.png

    # Adding a worksheets : parameters for addWorksheet are 1. Workbook Name 2. Sheet Name

    addWorksheet(wb, "Sheet 1")
    addWorksheet(wb, "Sheet 2")
    addWorksheet(wb, "Sheet 3")

    # Writing data in to respetive sheets: parameters for writeData are 1. Workbook Name 2. Sheet index/ sheet name 3. dataframe name

    writeData(wb, 1, x)

    # incase you would like to write sheet with filter available for ease of access you can pass the parameter withFilter = TRUE in writeData function.
    writeData(wb, 2, x = y, withFilter = TRUE)

    ## Similarly writeDataTable is another way for representing your data with table formatting:

    writeDataTable(wb, 3, z)

    saveWorkbook(wb, file = "Example.xlsx", overwrite = TRUE)

    end.time <- Sys.time()
    time.taken <- end.time - start.time
    time.taken

openxlsx package is really good for reading and writing huge data from/ in excel files and has lots of options for custom formatting within excel.

The interesting fact is that we dont have to bother about java heap memory here.

There's a new library in town, from rOpenSci: writexl

Portable, light-weight data frame to xlsx exporter based on libxlsxwriter. No Java or Excel required

I found it better and faster than the above suggestions (working with the dev version):

library(writexl)
sheets <- list("sheet1Name" = sheet1, "sheet2Name" = sheet2) #assume sheet1 and sheet2 are data frames
write_xlsx(sheets, "path/to/location")

for a lapply-friendly version..

library(data.table)
library(xlsx)

path2txtlist <- your.list.of.txt.files
wb <- createWorkbook()
lapply(seq_along(path2txtlist), function (j) {
sheet <- createSheet(wb, paste("sheetname", j))
addDataFrame(fread(path2txtlist[j]), sheet=sheet, startColumn=1, row.names=FALSE)
})

saveWorkbook(wb, "My_File.xlsx")