R/gdpplotterr.R

In UBC-MDS/gdphelperR: Summarize GDP Data and Make Plots

#' gpdplotterr
#' Author: Aldo Saltao Barros
#' Plot a line chart of periods and the selected feature.
#' @param cleaned_Dataframe This is the name of the dataset that you want to draw a chart. It is an output from the function gdpcleanerr
#'
#' @return line chart of GDP by the Region VS periods.
#' @export
#'
#' @examples
#' data <- tibble::tribble(~REF_DATE,~GEO,~DGUID,
#' ~`North.American.Industry.Classification.System.(NAICS)`,
#' ~UOM, ~UOM_ID,~SCALAR_FACTOR,~SCALAR_ID,~VECTOR, ~COORDINATE,
#' ~VALUE,~STATUS,~SYMBOL,~TERMINATED,~DECIMALS,1997L,"Canada",
#' "2016A000011124","Total industries", "Dollars",81L,"millions",
#' 6L, "v41894235",1.477, 816756.1, NA,NA, NA,1L,1997L,"Canada",
#' "2016A000011124", "Crop and animal production",
#' "Dollars",81L,"millions",6L,"v41700857", 1.1,12755.9,NA,NA, NA,1L)
#' cleaned_df <- gdpcleanerr(data)
#' gdpplotterr(cleaned_df)
gdpplotterr <- function(cleaned_Dataframe){

  #Check that the argument is correct
  if (is.null(cleaned_Dataframe)) {
    stop("No argument. Please use gdpcleanerr to get the right arguments for gdpplotter")
  }
  if (!is.data.frame(cleaned_Dataframe)) {
    stop("No DataFrame.Please use gdpcleanerr to get the right arguments for gdpplotter")
  }

  #Check that the argument is correct
  #if(!(typeof(cleaned_Dataframe$Value) == "double")){
  #  stop("Variable Value is not numeric. Please use gdpcleanerr to get the right arguments for gdpplotter")
  #}

  #if(!(typeof(cleaned_Dataframe$Location) == "character")){
  #  stop("Variable Location is not categorical. Please use gdpcleanerr to get the right arguments for gdpplotter")
  #}


  # calling dataFrame
  clened_df <- cleaned_Dataframe

  #listing units in Scale
  units_type <- unique(clened_df$Scale)

  #filtering the right type in Scale
  if ("millions" %in% units_type) {
    #print("check point 1: unity = millions")
    df_filtered <- dplyr::filter(clened_df, Scale == "millions")
  } else if ( "units" %in% units_type) {
    #print("check point 1: unity = units")
    df_filtered <- dplyr::filter(clened_df, Scale == "units")
  } else if ( "units " %in% units_type) {
    #print("check point 1: unity = units-sapce")
    df_filtered <- dplyr::filter(clened_df, Scale == "units ")
  } else {
    stop("This dataframe don't have the GDP's units 'millions' or 'units ' or 'units' which are allowed for this analysis. Please check your DataFrame")
  }

  #checking the variables
  filtered_unids <- unique(df_filtered$Scale)
  #sprintf("Checking filter 01: %s", filtered_unids)
  all_years <- unique(df_filtered$Date)
  #sprintf("year: %s", all_years)
  provinces <- unique(df_filtered$Location)
  #sprintf("%s", provinces)
  total_year <- length(all_years)


  # selecting the charts
  if ( "Canada" %in% provinces && total_year > 1) {
    #print("barchart for Canada")
    df_filtered_2 <- dplyr::filter(df_filtered, Location == "Canada")
    plot_location <- ggplot2::ggplot(df_filtered_2, ggplot2::aes(x = Date, y = Value, color=Location)) +
      ggplot2::geom_bar(stat = 'summary', fun = sum)+
      ggplot2::facet_wrap(~Location, ncol = 5)
    plot_location

  } else if ( "Canada" %in% provinces && total_year == 1) {
    #print("bar chart here!!")
    plot_location <- ggplot2::ggplot(df_filtered, ggplot2::aes(x = Date, y = Value, color=Location)) +
      ggplot2::geom_bar(stat = 'summary', fun = sum)+
      ggplot2::facet_wrap(~Location, ncol = 5)
    plot_location

  } else if ( total_year > 1) {
    #print("chart with multlines goes here")
    plot_location <- ggplot2::ggplot(df_filtered, ggplot2::aes(x = Date, y = Value, color = Location)) +
      ggplot2::geom_line(stat = 'summary', fun = sum)
    plot_location

  } else {
    #print("bar chart for provincies goes here")
    plot_location <- ggplot2::ggplot(df_filtered, ggplot2::aes(x = Date, y = Value, color=Location)) +
      ggplot2::geom_bar(stat = 'summary', fun = sum)+
      ggplot2::facet_wrap(~Location, ncol = 5)
    plot_location

  }


}