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Thanks @schaunwheeler codes to read xlsx files. I had remove all dependence and parse the xml files with text regular expression. It will be much faster to read large xlsx files.
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#' Read xlsx files | |
#' | |
#' @param file The path to xlsx file | |
#' @param keep_sheets A vector of sheet name | |
#' @param header Whether include the head in the sheet | |
#' @param empty_row Whether to remove the empty rows | |
#' @export | |
xlsxToR <- function(file, keep_sheets = NULL, header = TRUE, empty_row = TRUE) | |
{ | |
suppressWarnings(file.remove(tempdir())) | |
file.copy(file, tempdir()) | |
new_file <- list.files(tempdir(), full.name = TRUE, pattern = basename(file)) | |
new_file_rename <- gsub("xlsx$", "zip", new_file) | |
file.rename(new_file, new_file_rename) | |
unzip(new_file_rename, exdir = tempdir()) | |
# Get OS | |
mac <- readLines(paste0(tempdir(), "/docProps/app.xml"), warn = FALSE) | |
mac <- grep("Macintosh", mac) | |
if (length(mac) > 0) | |
{ | |
os_origin <- "1899-12-30" # documentation says should be "1904-01-01" | |
} else | |
{ | |
os_origin <- "1899-12-30" | |
} | |
# Get names of sheets | |
sheet_names_str <- readLines(paste0(tempdir(), "/xl/workbook.xml"), warn = FALSE)[2] | |
sheet_names_str <- gsub('.*<sheets>(.*)</sheets>.*', '\\1', sheet_names_str) | |
sheet_names_str <- strsplit(sheet_names_str, '/>')[[1]] | |
sheet_names <- NULL | |
sheet_names$name <- gsub('.* name="(.*)"( sheetId.*)', '\\1', sheet_names_str) | |
sheet_names$sheetId <- gsub('.* sheetId="(\\d+)" +.*', '\\1', sheet_names_str) | |
sheet_names$id <- gsub('.* r:id="(.*)"$', '\\1', sheet_names_str) | |
sheet_names <- as.data.frame(sheet_names,stringsAsFactors = FALSE) | |
sheet_names$id <- gsub("\\D", "", sheet_names$id) | |
if(!is.null(keep_sheets)) | |
{ | |
sheet_names <- sheet_names[sheet_names$name %in% keep_sheets,] | |
} | |
entries <- readLines(paste0(tempdir(), "/xl/sharedStrings.xml"), warn = FALSE)[2] | |
entries <- gsub('^<sst .*">(<si>.*)</sst>$', '\\1', entries) | |
entries <- strsplit(entries, '</si>')[[1]] | |
entries <- gsub('^.*<t.*>(.+)</t>$', '\\1', entries) | |
entries[grep('<t/>', entries)] <- NA | |
names(entries) <- seq_along(entries) - 1 | |
# Get column classes | |
styles <- readLines(paste0(tempdir(), '/xl/styles.xml'), warn = FALSE)[2] | |
numFmtId <- gsub('^.*<cellXfs count="\\d+">(.*)</cellXfs>.*$', '\\1', styles) | |
numFmtId <- strsplit(numFmtId, '<xf')[[1]] | |
numFmtId <- numFmtId[nchar(numFmtId) > 0] | |
numFmtId <- as.numeric(gsub('.*numFmtId="(\\d+)".*', '\\1', numFmtId)) | |
cell_style <- as.data.frame(list(id = seq(0, by = 1, along = numFmtId), | |
numFmtId = numFmtId), stringsAsFactors = FALSE) | |
# Custom style | |
numFmt <- gsub('^.*<numFmts count="\\d+">(.*)</numFmts>.*$', '\\1', styles) | |
if (length(numFmt) > 0) | |
{ | |
numFmt <- strsplit(numFmt, '/><numFmt')[[1]] | |
numFmt_cid <- as.numeric(gsub('.*numFmtId="(\\d+)".*', '\\1', numFmt)) | |
cid_type <- rep(NA, length(numFmt_cid)) | |
formatCode <- gsub('.*formatCode="(.*)".*', '\\1', numFmt) | |
pos <- grep('y|m|d', formatCode) | |
if (length(pos) > 0) | |
{ | |
date_format <- formatCode[grep('y|m|d', formatCode)] | |
pos <- grep('h', date_format) | |
if (length(pos) > 0) | |
{ | |
date_format <- date_format[-pos] | |
} | |
pos <- cell_style$numFmtId %in% numFmt_cid[formatCode %in% date_format] | |
cell_style$numFmtId[pos] <- 14 | |
} | |
} | |
worksheet_paths <- paste0(tempdir(), "/xl/worksheets/sheet", | |
sheet_names$id, '.xml') | |
worksheets <- as.list(NULL) | |
for (i in seq(along = worksheet_paths)) | |
{ | |
tryCatch({ | |
sheet_data <- readLines(worksheet_paths[i], warn = FALSE)[2] | |
sheet_data <- gsub('(.*<sheetData>)(.*)(</sheetData>.*)', '\\2', sheet_data) | |
sheet_data <- strsplit(sheet_data, '</row>')[[1]] | |
sheet_data <- sheet_data[grep('</c>', sheet_data)] | |
if (length(sheet_data) == 0) | |
{ | |
next | |
} | |
sheet_data <- strsplit(sheet_data, '</c>') | |
sheet_data <- unlist(sheet_data) | |
sheet_data <- gsub('(.*<row.*>)(<c.*)', '\\2', sheet_data) | |
res <- NULL | |
res$r <- gsub('.*r="(\\w+\\d+)".*', '\\1', sheet_data) | |
res$v <- rep(NA, length(sheet_data)) | |
pos <- grep('.*<v>(.*)</v>.*', sheet_data) | |
res$v[pos] <- gsub('.*<v>(.*)</v>.*', '\\1', sheet_data[pos]) | |
res$s <- rep(NA, length(sheet_data)) | |
pos <- grep('.* s="(\\d+|\\w+)"( |>).*', sheet_data) | |
res$s[pos] <- gsub('.* s="(\\d+|\\w+)"( |>).*', '\\1', sheet_data[pos]) | |
res$t <- rep(NA, length(sheet_data)) | |
pos <- grep('.* t="(\\d+|\\w+)"( |>).*', sheet_data) | |
res$t[pos] <- gsub('.* t="(\\d+|\\w+)"( |>).*', '\\1', sheet_data[pos]) | |
res <- as.data.frame(res, stringsAsFactors = FALSE) | |
res$sheet <- sheet_names[sheet_names$id == i, 'name'] | |
entries_match <- entries[match(res$v, names(entries))] | |
res$v[res$t == "s" & !is.na(res$t)] <- | |
entries_match[res$t == "s"& !is.na(res$t)] | |
res$cols <- match(gsub("\\d", "", res$r), LETTERS) | |
res$rows <- as.numeric(gsub("\\D", "", res$r)) | |
nrow <- max(res$rows) | |
ncol <- max(res$cols) | |
if (header) | |
{ | |
nrow <- nrow - 1 | |
} | |
res_df <- as.data.frame(matrix(rep(NA, ncol * nrow), ncol = ncol), | |
stringsAsFactors = FALSE) | |
style_df <- as.data.frame(matrix(rep(NA, ncol * nrow), ncol = ncol), | |
stringsAsFactors = FALSE) | |
if (header) | |
{ | |
header_df <- res[res$rows == 1,] | |
header_name <- paste0('V', seq(ncol)) | |
header_name[header_df$cols] <- header_df$v | |
names(res_df) <- header_name | |
res <- res[res$rows != 1,] | |
res$rows <- res$rows - 1 | |
} | |
if (nrow(res) > 0) | |
{ | |
res_df[as.matrix(res[,c('rows', 'cols')])] <- res$v | |
s <- as.numeric(res$s) | |
s <- cell_style$numFmtId[match(s, cell_style$id)] | |
style_df[as.matrix(res[,c('rows', 'cols')])] <- s | |
} | |
style_df <- sapply(style_df, function(x) | |
{ | |
ifelse(length(unique(x[!is.na(x)])) == 1, unique(x[!is.na(x)]), NA) | |
}) | |
style_col <- rep('character', length(style_df)) | |
style_col[style_df %in% 14:17] <- "date" | |
style_col[style_df %in% c(18:21, 45:47)] <- "time" | |
style_col[style_df %in% 22] <- "datetime" | |
style_col[is.na(style_df) & !sapply(res_df, function(x) any(grepl("\\D", x)))] <- "numeric" | |
number2date <- function(x) | |
{ | |
if (class(x) == 'character') | |
{ | |
pos <- !(is.na(x)) & !(x == 'NA') | |
} else | |
{ | |
stop('NOT implemented to check class of column date in xlsxToR') | |
} | |
res <- rep(NA, length = length(x)) | |
res[pos] <- as.numeric(x[pos]) | |
res <- as.Date(res, origin = os_origin) | |
res | |
} | |
res_df[] <- lapply(seq_along(res_df), function(j) | |
{ | |
switch(style_col[j], | |
character = res_df[,j], | |
numeric = as.numeric(res_df[,j]), | |
date = number2date(res_df[,j]), | |
time = strftime(as.POSIXct(as.numeric(res_df[,j]), origin = os_origin), format = "%H:%M:%S"), | |
datetime = as.POSIXct(as.numeric(res_df[,j]), origin = os_origin)) | |
}) | |
if (empty_row) | |
{ | |
pos <- apply(res_df, 1, function(x) sum(is.na(x))) != ncol(res_df) | |
if (ncol(res_df) == 1) | |
{ | |
col_name <- names(res_df) | |
res_df <- data.frame(res_df[pos,]) | |
names(res_df) <- col_name | |
} else | |
{ | |
res_df <- res_df[pos,] | |
} | |
} | |
sheet_n <- sheet_names$name[sheet_names$id == i] | |
worksheets[[sheet_n]] <- res_df | |
}, warning = function(w) | |
{ | |
print(style_col) | |
stop(paste0('Warning messsage for sheet ', sheet_names$name[sheet_names$id == i], '\n', w)) | |
}) | |
} | |
if(length(worksheets) == 1) | |
{ | |
worksheets <- worksheets[[1]] | |
} | |
worksheets | |
} | |
"Error in unzip(new_file_rename, exdir = tempdir()) :
invalid zip name argument
Calls: xlsxToR -> unzip
Execution halted"
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Thanks, this is much faster :-) (4x for the 537 kb workbook that I am trying to import). I suggest you replace LETTERS with XL_LETTERS (as defined below) as it otherwise fails for worksheets with more than 26 columns.