Multiple Excel Spreadsheets Import to R - r

Question

I have an Excel file with hundreds of spreadsheets.
I have read a few postings on stackoverflow where it is answered how to import them into R using read.xl packages and so on...
But I need to do something extra for this file. Each spreadsheet has 2 rows of header on the top and first row in the header has 5 digits of number that I need to extract and insert it to the table.
For example, header has 11111 ABC Corp. and its dataset below.
It should look like this:
11111 ABC Corp.
Product# | Description | Quantity Order | Price | Unit Price
Here, I want to import the data as below:
ID# | Product # | Description | Quantity Order | Price | Unit Price
11111 | 2813A | Whatever | 100
11111 | 2222B
11111 | 7721CD
So as you see above, the five digits of number should be copied to the first column of the table for each spreadsheet. Each spreadsheet has different five digit numbers to be copied to its table.
I was thinking if I have a way to extract the first five digits, then I can probably do this by using loop.
So 1. Extract the first five digits.
2. Design a loop by which I can insert into first column and import in to R.
What are the good functions I can use?
Thank you.

Answer 1

R is a great tool for so, so, so many things! In this specific case, I would manipulate the data in Excel, and then import one large merged range into R. I always believe in using the right tool for the specific task you are tacking. So, start by downloading and installing the AddIn from here.
https://www.rondebruin.nl/win/addins/rdbmerge.htm
So, merge all worksheets (hundreds) into one massive worksheet. Set First Cell to A2 till last cell on worksheet. Once all those hundreds of sheets are merged into one sheet, save that as a CSV, and import it into R.
mydata <- read.table("c:/mydata.csv", header=TRUE, sep=",", row.names="id")

Answer 2

The key to iteration is solve it for one and then apply to all. Once you've figured out how to do it for one sheet the rest is easy.
Here is my guess based on your description of your files.
library(readxl) # to read excel files
library(readr) # for type_convert
fname <- "test.xlsx"
## get sheet names
sheets <- excel_sheets(fname)
## function to process a single sheet
processSheet <- function(sheet, file) {
all <- read_excel(file, sheet) # read all data
id <- na.omit(names(all)) # extract the ID
names(all) <- unlist(all[1, ]) # make the first row the names
all <- all [-1, ] # get rid of the first row
data.frame(ID = id, # add id column
type_convert(all) # convert to appropriate column types
)
}
## apply the function to each sheet, collecting the results into a
## data.frame
test.data <- do.call(rbind,
lapply(sheets,
processSheet,
file = fname))
You could of course use something other than readxl to read the Excel files. Something that can read a specific range would make the re-arranging of the data easier. The reason I went with readxl is that I've found it "just work", whereas others depend on Java or Perl and tend to break more often in my experience.