R/create_lagged.R

In canhakan/canhakan1: Helper Package for Spatio-temporal Time-Series Data

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# install_github('canhakan/canhakan1')

#' @description Creates a new data frame(?) with Lag/Lead values. Also one may exclude the features(columns) from "lag process" but have them with the new data frame
#' @export
#' @title Creates Lagged Data
#' @param data input data
#' @param lags list of wanted lags. Negative values correspond to lags while positives correspond to leads.
#' @param exclude_head the columns of data that is not subject to lagging process (e.g. date/hour). Will be merged to left-side of the lagged data.
#' @param exclude_tail the columns of data that is not subject to lagging process (e.g. production). Will be merged to right-side
#' @return Data with more columns as lagged versions of existing columns
create_lagged <- function(data,
                          lags,
                          exclude_head = NULL,
                          exclude_tail = NULL){
  # data.table -> data.frame
  data = data.frame(data)
  # get min/max for removing first/last rows from data for lag/lead
  min_lag = min(0,lags)
  max_lag = max(0,lags)
  startN = 1 - min_lag # for cutting the head
  endN = nrow(data) - max_lag # for cutting the tail
  # seperating excludes
  exclude = c(exclude_head, exclude_tail)
  tobe.head = data[(startN:endN),exclude_head]
  tobe.tail = data[(startN:endN),exclude_tail]
  # creating an empty data.table for
  dat = data.table::data.table() # empty data table
  # adding lagged values one by one (column by column)
  for(i in lags){
    lagdat = data[((startN+i):(endN+i)),-exclude]
    if(i<0){
      lagname = paste('lag',-i,sep='')
      colnames(lagdat) = paste(colnames(lagdat),lagname,sep='_')
    } else if(i>0){
      lagname = paste('lead',i,sep='')
      colnames(lagdat) = paste(colnames(lagdat),lagname,sep='_')
    }
    dat = cbind(dat,lagdat)
  }
  dat = cbind(tobe.head,dat,tobe.tail)
  return(dat)
}