R/book_open.R

In skylics/stock_analysis: Predict how price of specific financial asset will change.

#' Bring yearly BS book data from sejong
#'
#' \code{book_open} returns major accounting book data

#' @param ticker a ticker code in the format as "000000" (use find_code())
#'
#' @return a data frame
#' @export
#'
#' @examples
#' find_code("stockname") %>% book_open
book_open <- function(ticker) {

  library(rebus, quietly = TRUE)

  url <- paste("http://www.sejongdata.com/business_include_fr/table_main0_bus_01.html?&no=", ticker, sep = "")

  html_sejong <- xml2::read_html(url, encoding = "UTF-8")

  sejongdata <- html_sejong %>% rvest::html_nodes(".bus_board_txt1") %>% html_text %>% data.frame

  date <- rvest::html_nodes(html_sejong, css = ".bus_board_tit1") %>% html_text %>% data.frame

  ## create empty frame
  data <- matrix(data = NA, nrow = 15, ncol = 10)

  ## column name / row name
  colnames(data) <- as.vector(date[2:11, ]) %>%
    str_match(capture(one_or_more(DGT) %R% "." %R% one_or_more(DGT)) %R%
                one_or_more(SPC) %R%
                capture("\\(" %R% one_or_more(WRD)) %R%
                one_or_more(SPC) %R%
                capture(one_or_more(WRD) %R% "\\)")) %>% (function(df) {paste(df[, 2], df[, 3], df[, 4], sep = " ")})

  tmp <- c(1, 12, 23, 34, 45, 56, 67, 78, 89, 100, 111, 122, 133, 144, 155)
  rownames(data) <- as.vector(sejongdata[tmp, 1])

  ## transpose
  data <- t(data)

  for (i in 1:15) {
    data[, i] <- sejongdata[((tmp[i] + 1):(tmp[i] + 1 + 9)), ] %>% as.vector %>%
      stringr::str_replace(",", "") %>% iconv(to = "UTF-8") %>% as.numeric %>%  (function(df) {df[is.na(df)] <- ""; df})
  }

  data <- t(data)
  data <- data %>% as.data.frame
  data
}

# c(15) %>% map(function(i) {
#   sejongdata[((tmp[i] + 1):(tmp[i] + 1 + 9)), ] %>% as.vector %>% stringr::str_replace(",", "") %>% iconv(to = "UTF-8") %>% as.numeric
# })