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#' Parse an html table into a data frame.
#'
#' @section Assumptions:
#'
#' `html_table` currently makes a few assumptions:
#'
#' \itemize{
#' \item No cells span multiple rows
#' \item Headers are in the first row
#' }
#' @param x A node, node set or document.
#' @param header Use first row as header? If `NA`, will use first row
#' if it consists of `<th>` tags.
#' @param trim Remove leading and trailing whitespace within each cell?
#' @param fill If `TRUE`, automatically fill rows with fewer than
#' the maximum number of columns with `NA`s.
#' @param dec The character used as decimal mark.
#' @export
#' @examples
#' sample1 <- minimal_html("<table>
#' <tr><th>Col A</th><th>Col B</th></tr>
#' <tr><td>1</td><td>x</td></tr>
#' <tr><td>4</td><td>y</td></tr>
#' <tr><td>10</td><td>z</td></tr>
#' </table>")
#' sample1 %>%
#' html_node("table") %>%
#' html_table()
#'
#' # Values in merged cells will be duplicated
#' sample2 <- minimal_html("<table>
#' <tr><th>A</th><th>B</th><th>C</th></tr>
#' <tr><td>1</td><td>2</td><td>3</td></tr>
#' <tr><td colspan='2'>4</td><td>5</td></tr>
#' <tr><td>6</td><td colspan='2'>7</td></tr>
#' </table>")
#'
#' sample2 %>%
#' html_node("table") %>%
#' html_table()
#'
#' # If the table is badly formed, and has different number of columns
#' # in each row, use `fill = TRUE` to fill in the missing values
#' sample3 <- minimal_html("<table>
#' <tr><th>A</th><th>B</th><th>C</th></tr>
#' <tr><td colspan='2'>1</td><td>2</td></tr>
#' <tr><td colspan='2'>3</td></tr>
#' <tr><td>4</td></tr>
#' </table>")
#'
#' sample3 %>%
#' html_node("table") %>%
#' html_table(fill = TRUE)
html_table <- function(x, header = NA, trim = TRUE, fill = FALSE, dec = ".") {
UseMethod("html_table")
}
#' @export
html_table.xml_document <- function(x, header = NA, trim = TRUE, fill = FALSE,
dec = ".") {
tables <- xml2::xml_find_all(x, ".//table")
lapply(tables, html_table, header = header, trim = trim, fill = fill, dec = dec)
}
#' @export
html_table.xml_nodeset <- function(x, header = NA, trim = TRUE, fill = FALSE,
dec = ".") {
# FIXME: guess useful names
lapply(x, html_table, header = header, trim = trim, fill = fill, dec = dec)
}
#' @export
html_table.xml_node <- function(x, header = NA, trim = TRUE,
fill = FALSE, dec = ".") {
stopifnot(html_name(x) == "table")
# Throw error if any rowspan/colspan present
rows <- html_nodes(x, "tr")
n <- length(rows)
cells <- lapply(rows, "html_nodes", xpath = ".//td|.//th")
ncols <- lapply(cells, html_attr, "colspan", default = "1")
ncols <- lapply(ncols, as.integer)
nrows <- lapply(cells, html_attr, "rowspan", default = "1")
nrows <- lapply(nrows, as.integer)
p <- unique(vapply(ncols, sum, integer(1)))
maxp <- max(p)
if (length(p) > 1 & maxp * n != sum(unlist(nrows)) &
maxp * n != sum(unlist(ncols))) {
# then malformed table is not parsable by smart filling solution
if (!fill) { # fill must then be specified to allow filling with NAs
stop("Table has inconsistent number of columns. ",
"Do you want fill = TRUE?", call. = FALSE)
}
}
values <- lapply(cells, html_text, trim = trim)
out <- matrix(NA_character_, nrow = n, ncol = maxp)
# fill colspans right with repetition
for (i in seq_len(n)) {
row <- values[[i]]
ncol <- ncols[[i]]
col <- 1
for (j in seq_len(length(ncol))) {
out[i, col:(col+ncol[j]-1)] <- row[[j]]
col <- col + ncol[j]
}
}
# fill rowspans down with repetition
for (i in seq_len(maxp)) {
for (j in seq_len(n)) {
rowspan <- nrows[[j]][i]; colspan <- ncols[[j]][i]
if (!is.na(rowspan) & (rowspan > 1)) {
if (!is.na(colspan) & (colspan > 1)) {
# special case of colspan and rowspan in same cell
nrows[[j]] <- c(utils::head(nrows[[j]], i),
rep(rowspan, colspan-1),
utils::tail(nrows[[j]], length(rowspan)-(i+1)))
rowspan <- nrows[[j]][i]
}
for (k in seq_len(rowspan - 1)) {
l <- utils::head(out[j+k, ], i-1)
r <- utils::tail(out[j+k, ], maxp-i+1)
out[j + k, ] <- utils::head(c(l, out[j, i], r), maxp)
}
}
}
}
if (is.na(header)) {
header <- all(html_name(cells[[1]]) == "th")
}
if (header) {
col_names <- out[1, , drop = FALSE]
out <- out[-1, , drop = FALSE]
} else {
col_names <- paste0("X", seq_len(ncol(out)))
}
# Convert matrix to list to data frame
df <- lapply(seq_len(maxp), function(i) {
utils::type.convert(out[, i], as.is = TRUE, dec = dec)
})
names(df) <- col_names
class(df) <- "data.frame"
attr(df, "row.names") <- .set_row_names(length(df[[1]]))
if (length(unique(col_names)) < length(col_names)) {
warning('At least two columns have the same name')
}
df
}
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