R/plot_q70b_hh_income_fishing.R

In Rare-Technology/HHS_Dashboard: PKG_TITLE

prep_q70b_hh_income_fishing <- function(.data, iso3){
  
  #### inconsistent numbers  on number of respondents in 2019; is the filtering the  source
  # of this discrepancy? check the numbers w/ and w/o filters

  conversion <- convert_money(iso3)
  
  hhs_Q70 <- .data %>%
    dplyr::filter (dplyr::between(
      as.numeric(`70_hh_average_income`), 10, 1.00e+09)) %>%
    droplevels()
  
  Q70_length <-
    tapply(hhs_Q70$`70_hh_average_income`,
           hhs_Q70$maa,
           length)
  
  #Proportion of income and Average income per MA
  income_source <-
    hhs_Q70[, c(
      "maa",
      "11a_income_farming",
      "11b_income_harvesting",
      "11c_income_fishing_artisanal",
      "11d_income_fishing_industrial",
      "11e_income_buying_trading",
      "11f_income_processing",
      "11g_income_aquaculture",
      "11h_income_extraction",
      "11i_income_tourism",
      "11k_income_other"
    )]
  
  income_source[is.na(income_source)] <- 0
  income_source$`70_hh_average_income` <-
    as.numeric(as.character(hhs_Q70$`70_hh_average_income`))
  income_source <- data.frame(income_source)
  
  ## Agregate income
  income_summary <-
    aggregate(. ~ maa,
              FUN = mean,
              na.rm = TRUE,
              data = income_source)
  
  HH_avg_income <- data.frame (
    N = Q70_length,
    Total_Income_USD = round(income_summary$X70_hh_average_income, 1),
    Farming = round(income_summary$X11a_income_farming, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100,
    Harvesting = round(income_summary$X11b_income_harvesting, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100,
    Artisinal_Fishing = round(income_summary$X11c_income_fishing_artisanal, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100,
    Industrial_Fishing = round(income_summary$X11d_income_fishing_industrial, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100,
    Buying_Trading = round(income_summary$X11e_income_buying_trading, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100,
    Processing_Fish = round(income_summary$X11f_income_processing, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100,
    Aquaculture = round(income_summary$X11g_income_aquaculture, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100,
    Extraction = round(income_summary$X11h_income_extraction, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100,
    Tourism = round(income_summary$X11i_income_tourism, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100,
    Other = round(income_summary$X11k_income_other, 1) /
      rowSums(income_summary[, c(2:11)], na.rm = TRUE) * 100
  )
  
  HH_avg_income$Fishing_related <-
    HH_avg_income$Artisinal_Fishing + 
    HH_avg_income$Industrial_Fishing +
    HH_avg_income$Buying_Trading +
    HH_avg_income$Processing_Fish
  
  Q70_summary <-
    tibble::rownames_to_column(HH_avg_income[, c(1:2, 13)], "MA name")
  colnames(Q70_summary) <-
    c("MA name", "N", "Proportion (%)", "Fishing_related")
  
  Q70b <- Q70_summary[, c(1:2)]
  Q70b[["Proportion (%)"]] <- round(
    as.numeric(Q70_summary$`Proportion (%)`) * as.numeric(as.character(Q70_summary$Fishing_related)) * conversion /
      100,1)
  
  Q70b <- clean_plot_data(Q70b)
  colnames(Q70b) <- c("MA name", "N", "Average")
  Q70b
}

plot_q70b_hh_income_fishing <- function(.data, ...){

   dots <- list(...)
   .data_plot <- prep_q70b_hh_income_fishing(.data, dots$iso3)
   
   p <- plot_horiz_bar(
     .data_plot,
     title = "Average household income from fishing-related activities in USD",
     y_var = Average,
     y_title = "US Dollars ($)",
     limits = NULL,
     breaks = waiver()
   )
   
   result <- list(
     plot = p,
     data = .data_plot
   )
}