Extract tables from Word files that are in different subfolders, then combine them.

extract-word-tables.R

# Extract and combine tables from multiple Word files

# This script creates some dummy docx files in temporary subfolders to mimic a 
# user's filesystem. It then uses docxtractr::read_docx() to extract all the
# tables, and combines them with rbind().

# A follow-up to my blogpost:
#   https://www.rostrum.blog/2023/06/07/rectangular-officer/

# Attach packages (all are available from CRAN)
library(docxtractr)  # to extract tables from docx files
library(officer)  # to create dummy docx files
library(charlatan)  # to generate fake data

# Create multiple dummy docs files in separate temporary folders

my_folder <- tempdir()  # temporary locations to store the files
n_files <- 5  # the number of dummy files to generate

for (i in seq(n_files)) {
  
  # Create subfolders
  subfolder_name <- paste0("subfolder_", i)
  dir.create(file.path(my_folder, subfolder_name))
  
  # Create dummy dataframe
  
  n_fake <- 10  # number of fake data items to generate
  
  temp_df <- data.frame(
    name = ch_name(n_fake),
    job = ch_job(n_fake),
    phone = ch_phone_number(n_fake)
  )
  
  # Add dummy dataframe to a docx file and save it
  path <- file.path(my_folder, subfolder_name, paste0("df_", i, ".docx"))
  officer::read_docx() |> body_add_table(temp_df) |> print(target = path)
  
}

# Get the file paths to all the docx files
docx_paths <- list.files(
  my_folder,
  pattern = ".docx$",
  full.names = TRUE,  # return full filepaths
  recursive = TRUE  # look in all subfolders
)

# Preallocate a list to be filled with extracted tables, one element per file
extracted_tables <- vector("list", n_files)

# Extract tables and add to the list (not tested: I think that read_docx will
# read .doc files, but only if you have LibreOffice installed.
for (i in docx_paths) {
  tables <- docxtractr::read_docx(i) |> docx_extract_all_tbls()
  extracted_tables[basename(i)] <- tables
}

# In this simple demo, the dataframes in each list element can be appended
# because they all have the same column names and types.
do.call(rbind, extracted_tables)