A wrapper for download and cleaning of IOC bird Master Lists

IOCmasteR.R

# A wrapper for download and cleaning of IOC bird lists
# This function downloads a given list, defined by the URL,
# completes rows with relevant information, and outputs a data frame.
# Further functions may be added and a small package developed, in time.
# 
# There's almost certainly a more elegant way of doing this.
#
# earl = URL of IOC master List (see https://www.worldbirdnames.org/new/ioc-lists/master-list-2); currently defaults to v13.1
#
# E.g. 
# df <- IOCmasteR()
IOCmasteR <- function(earl = "https://worldbirdnames.org/master_ioc_list_v13.1.xlsx"){ 

require(tidyverse)
require(janitor)
require(readxl)
# Download Master List
temp = tempfile(fileext = ".xlsx")
dataURL <- earl
download.file(dataURL, destfile=temp, mode='wb')
birds<- read_excel(temp, 
           col_names = T,
           skip = 3)
# Clean column names
birds <- clean_names(birds)
# Fill relevant columns and thin to single-row records, only
# Note that certain fields need to be excluded to prevent erroneous duplication
# of discrete data.
birds2 <- birds %>%
  select(-c(parvclass, 
            authority,
            breeding_range_subregion_s, 
            nonbreeding_range,
            code,
            comment)) %>%
  fill(infraclass) %>%
  group_by(infraclass) %>%
  fill(order:species_scientific, .direction = 'downup') %>%
  group_by(across(infraclass:species_scientific)) %>%
  reframe(across(everything(), ~if(all(is.na(.x)))NA else na.omit(.x)))
# Create comparative df for merge, containing reference columns and those]
# previously excluded
birds3 <- birds %>% fill(c("infraclass", 
                           "order", 
                           "family_scientific",
                           "family_english",
                           "genus",
                           "species_scientific",
                           "species_english"), .direction = "down") %>%
  mutate(name = paste(family_scientific, genus, 
                      " ", species_scientific, subspecies))
# Create the same reference column in the filled data frame
birds2 <- birds2 %>%
  mutate(name = paste(family_scientific, genus, 
                      " ", species_scientific, subspecies))
# Merge data frames
b <- merge(birds2, birds3[c("name", 
                            "comment", 
                            "code", 
                            "breeding_range_subregion_s", 
                            "authority", 
                            "nonbreeding_range")], 
           by="name",
           all.x = F)
# Re-order columns to something more logical
b <- b[, c(2:7, 9, 8, 14, 10, 13, 15, 12, 11)]
# Sort data
b <- b[order(b$infraclass, 
             b$order,
             b$family_scientific,
             b$genus,
             b$species_scientific, 
             b$subspecies),]

return(b)
}