R/timeslice.R

In massimoaria/bibliometrix: Comprehensive Science Mapping Analysis

#' Bibliographic data frame time slice
#'
#' Divide a bibliographic data frame into time slice
#'
#'
#'
#' @param M is a bibliographic data frame obtained by the converting function \code{\link{convert2df}}.
#'        It is a data matrix with cases corresponding to manuscripts and variables to Field Tag in the original SCOPUS and Clarivate Analytics WoS file.
#' @param breaks is a numeric vector of two or more unique cut points.
#' @param k is an integer value giving the number of intervals into which the data frame is to be cut. \code{k} is used only in case \code{breaks} argument is not provided. The default is \code{k = 5}.
#' @return the value returned from \code{split} is a list containing the data frames for each sub-period.
#'
#'
#'
#' @examples
#'
#' data(scientometrics, package = "bibliometrixData")
#'
#' list_df <- timeslice(scientometrics, breaks = c(1995, 2005))
#'
#' names(list_df)
#'
#' @seealso \code{\link{convert2df}} to import and convert an ISI or SCOPUS Export file in a bibliographic data frame.
#' @seealso \code{\link{biblioAnalysis}} function for bibliometric analysis.
#' @seealso \code{\link{summary}} to obtain a summary of the results.
#' @seealso \code{\link{plot}} to draw some useful plots of the results.
#'
#' @export
timeslice <- function(M, breaks = NA, k = 5) {
  M$PY <- as.numeric(M$PY)
  period <- list()
  if (is.na(breaks[1]) & is.numeric(k)) {
    breaks <- (floor(seq(min(M$PY, na.rm = TRUE) - 1, max(M$PY, na.rm = TRUE), length.out = k + 1)))
  } else {
    breaks <- c(min(M$PY, na.rm = TRUE) - 1, breaks, max(M$PY, na.rm = TRUE))
  }
  df <- cut(M$PY, breaks)
  N <- levels(df)
  ind <- as.numeric(df)
  df <- split(M, ind)
  names(df) <- N
  return(df)
}