R/plt_timeserie.R

In THartl1/EntrancesDataPackage: Package containing functions to extract data from the ENTRANCES Dataset

#' @title Plot time series data for a variable from the Entrance Data set.
#'
#' @description Plot time series data for a variable from the Entrance Data set. The observations for different regional units are displayed in different colors. The plot can be saved as png and printed in the R Studio plot window.
#'
#' @param VarName character string o with the name of the variable which shall be plotted.
#' @param data data_frame containing the data you want to use. It must contain a column called year containing the years of the observation, a column called value containing the variable values and a column called NUTS_ID with regional IDs. Default is the EntrancesData dataset.
#' @param years integer vector containing all years for which the data should be plotted. Default is all years contained in the dataset
#' @param nuts_ids, sting vector with NUTS IDs which should be plotted. Default is "all", selecting all NUTS IDs in the dataset for plotting.
#' @param print_plot logical, if TRUE, the plot is displayed in the Plot window
#' @param save_png logical, if TRUE, a png of the plot is saved.
#' @param legend_labels, vector with legend labels, if set to "default", NUTS_IDs are used. Default is "default", If you have more than 11 legend labels, you must use default. Must have the same number of elements as nuts_ids.
#' @param folder_for_png string, name of the folder in the working directory where a picture of the plots should be saved. folder="wd" saves plots directly in the working directory. Default is the folder Plots in the working directory. If the folder doesn't exist, the function creates a new folder in the working directory.
#' @param NUTS_level string, plots data only for a specific NUTS level. default is "all", so all data is plotted. Other possible inputs: "NUTS3", "NUTS2","NUTS1","NUTS country"
#' @export
#' @examples
#' plt_timeserie(VarName="pop", data=EntrancesData, years=c(2000:2020), nuts_ids=c("IT", "PL", "RO"), print_plot=TRUE, save_png=FALSE, legend_labels=c("Italy","Poland","Romania"), folder_for_png="Plots", NUTS_level="all")
plt_timeserie <- function(VarName,data=EntrancesData, years="all", nuts_ids="all", print_plot=TRUE, save_png=TRUE, legend_labels="default", folder_for_png="Plots", NUTS_level="all") {
  library(ggplot2)
  #extract data for variables if VarName is not the default
  data<-get_data_for_variable(data=data, VarName=VarName)
  if(suppressWarnings(nuts_ids!="all")[1]) data<-get_data_for_regions(RegionIDs=nuts_ids, data=data)
  #extract data for NUTS level
  if(suppressWarnings(NUTS_level!="all")){
    if (NUTS_level=="NUTS3") data<-get_data_NUTS3(data)
    if (NUTS_level=="NUTS2") data<-get_data_NUTS2(data)
    if (NUTS_level=="NUTS1") data<-get_data_NUTS1(data)
    if (NUTS_level=="NUTS country") data<-get_data_NUTS_country(data)
  }
  #extract data for years, if years is not set to default
  if (class(years)=="integer") {
    check_fun<-try(data<-data[which(data$year %in% years),])
    if (class(check_fun)=="try-error") stop ("years is not correctly defined. See ?plt_timeseries")
  } else {
    if (years[1]!="all") stop("Variable years not correctly defined. years should be a vector containing years as integer or be set to default")
  }
  # Create plot object with different plots for each variable

  if (legend_labels[1]=="default") {
    plt<-ggplot2::ggplot(data, aes(x=year, y=value, col=NUTS_ID)) + geom_point() + labs(title=VarName)
  } else {
    if (length(legend_labels)<9) {
      plt<-ggplot2::ggplot(data, aes(x=year, y=value, col=NUTS_ID)) + geom_point() + labs(title=VarName) + scale_color_manual(labels = legend_labels, values = RColorBrewer::brewer.pal(length(legend_labels), "Dark2"))
    } else {
       if (length(legend_labels)<12) {
         plt<-ggplot2::ggplot(data, aes(x=year, y=value, col=NUTS_ID)) + geom_point() + labs(title=VarName) + scale_color_manual(labels = legend_labels, values = RColorBrewer::brewer.pal(length(legend_labels), "Paired"))
       } else {
         plt<-ggplot2::ggplot(data, aes(x=year, y=value, col=NUTS_ID)) + geom_point() + labs(title=VarName)
         print("Too many legend labels for color palette. Legend_labels were set to 'default'")
         }
    }
  }
  # defining directory for saving plots. If folder_for_png="wd", plots are saved in working directory.
  #folder_for_plot can be defined as a path or as a folder name for a folder in the working directory.
  #If the folder doesn't exist in the working directory, the folder is created.
  #Default is a subfolder Plots in the working directory
  if (save_png==TRUE) {
    current_wd<-getwd()
    if (folder_for_png=="wd") {
      directory<-current_wd
    } else {
      directory<-paste(current_wd,"/", folder_for_png,"/", sep="")
      if(!dir.exists(file.path(current_wd, folder_for_png))) {
        dir.create(file.path(current_wd, folder_for_png))
        print(paste("The folder ", folder_for_png, " was created in the directory", sep=""))
      }
    }
    suppressMessages(errormsg <- try(ggplot2::ggsave(paste(directory, VarName, ".png", sep=""), plot = plt), silent = FALSE))
    if (class(errormsg)=="try-error") print("Error: saving plot as png not successfully. Check variable name for special characters. Check if the plot can be displayed in RStudio if print_plot is set to FALSE.")
  }

  if (print_plot==TRUE) plt
}