Read multiple xlsx files with multiple sheets into one R data frame

7
votes

I have been reading up on how to read and combine multiple xlsx files into one R data frame and have come across some very good suggestions like, How to read multiple xlsx file in R using loop with specific rows and columns, but non fits my data set so far.

I would like R to read in multiple xlsx files with that have multiple sheets. All sheets and files have the same columns but not the same length and NA's should be excluded. I want to skip the first 3 rows and only take in columns 1:6, 8:10, 12:17, 19.

So far I tried:

file.list <- list.files(recursive=T,pattern='*.xlsx')

dat = lapply(file.list, function(i){
    x = read.xlsx(i, sheetIndex=1, sheetName=NULL, startRow=4,
              endRow=NULL, as.data.frame=TRUE, header=F)
# Column select 
    x = x[, c(1:6,8:10,12:17,19)]
# Create column with file name  
    x$file = i
# Return data
    x
  })

  dat = do.call("rbind.data.frame", dat)

But this only takes all the first sheet of every file

Does anyone know how to get all the sheets and files together in one R data frame?

Also, what packages would you recommend for large sets of data? So far I tried readxl and XLConnect.

4
rexcelxlsxreadxlopenxlsx
You have explicitly asked for only the first sheet in your function: x = read.xlsx(i, sheetIndex=1,....) - mkt
Also, if you're looking to optimize speed for large datasets, it's worth looking up the data.table package. Among other things, its fread function allows you to only read in the columns that you need, instead of reading all columns and then subsetting. But I'm not sure that it will work with .xlsx files. - mkt
Your lapply has looped over files, you need to ass a second loop over sheets to get what you want. - Choubi
Thanks for the suggestion. Do you know if there is a way to ask for all sheets with with read.xlsx? - Elisah

4 Answers

4
votes

I would use a nested loop like this to go through each sheet of each file. It might not be the fastest solution but it is the simplest.

require(xlsx)    
file.list <- list.files(recursive=T,pattern='*.xlsx')  #get files list from folder

for (i in 1:length(files.list)){                                           
  wb <- loadWorkbook(files.list[i])           #select a file & load workbook
  sheet <- getSheets(wb)                      #get sheet list

  for (j in 1:length(sheet)){ 
    tmp<-read.xlsx(files.list[i], sheetIndex=j, colIndex= c(1:6,8:10,12:17,19),
                   sheetName=NULL, startRow=4, endRow=NULL,
                   as.data.frame=TRUE, header=F)   
    if (i==1&j==1) dataset<-tmp else dataset<-rbind(dataset,tmp)   #happend to previous

  }
}

You can clean NA values after the loading phase.

7
votes

openxlsx solution:

filename <-"myFilePath"

sheets <- openxlsx::getSheetNames(filename)
SheetList <- lapply(sheets,openxlsx::read.xlsx,xlsxFile=filename)
names(SheetList) <- sheets
4
votes

Here's a tidyverse and readxl driven option that returns a data frame with columns for file and sheet names for each file.

In this example, not every file has the same sheets or columns; test2.xlsx has only one sheet and test3.xlsx sheet1 does not have col3.

library(tidyverse)
library(readxl)

dir_path <- "~/test_dir/"         # target directory path where the xlsx files are located. 
re_file <- "^test[0-9]\\.xlsx"    # regex pattern to match the file name format, in this case 'test1.xlsx', 'test2.xlsx' etc, but could simply be 'xlsx'.

read_sheets <- function(dir_path, file){
  xlsx_file <- paste0(dir_path, file)
  xlsx_file %>%
    excel_sheets() %>%
    set_names() %>%
    map_df(read_excel, path = xlsx_file, .id = 'sheet_name') %>% 
    mutate(file_name = file) %>% 
    select(file_name, sheet_name, everything())
}

df <- list.files(dir_path, re_file) %>% 
  map_df(~ read_sheets(dir_path, .))

# A tibble: 15 x 5
   file_name  sheet_name  col1  col2  col3
   <chr>      <chr>      <dbl> <dbl> <dbl>
 1 test1.xlsx Sheet1         1     2     4
 2 test1.xlsx Sheet1         3     2     3
 3 test1.xlsx Sheet1         2     4     4
 4 test1.xlsx Sheet2         3     3     1
 5 test1.xlsx Sheet2         2     2     2
 6 test1.xlsx Sheet2         4     3     4
 7 test2.xlsx Sheet1         1     3     5
 8 test2.xlsx Sheet1         4     4     3
 9 test2.xlsx Sheet1         1     2     2
10 test3.xlsx Sheet1         3     9    NA
11 test3.xlsx Sheet1         4     7    NA
12 test3.xlsx Sheet1         5     3    NA
13 test3.xlsx Sheet2         1     3     4
14 test3.xlsx Sheet2         2     5     9
15 test3.xlsx Sheet2         4     3     1
0
votes

One more solution from this "rio" package :

library("rio")

# import and rbind all worksheets
DT <- import_list(SINGLE_XLSX_PATH, rbind = TRUE)

source : rdrr.io