data-raw/processData.R

In nutriverse/gnr: R Companion to the Global Nutrition Report

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#
# Load libraries
#
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if(!require(readxl)) install.packages("readxl")

url <- "https://globalnutritionreport.org/documents/348/2018_Global_Nutrition_Report_Dataset_F0lDqIh.xlsx"

destFile <- tempfile()

download.file(url = url, destfile = destFile)

indicator_description <- read_xlsx(
  path = destFile, sheet = excel_sheets(destFile)[2], range = "A5:C714"
)

usethis::use_data(indicator_description, compress = "xz", overwrite = TRUE)



year <- c(2018, 2020, 2021, 2022, 2021, 2022)

code <- c("gnr2018", "gnr2020", "gnr2021", "country_profiles", "n4g", "gnr2022")

file_type <- c("xlsx", "xlsx", "xlsx", "xlsx", "xlsx", "zip")

name <- c(
  "2018 Global Nutrition Report Dataset",
  "2020 Global Nutrition Report Dataset",
  "2021 Global Nutrition Report Dataset",
  "Country Nutrition Profiles Dataset",
  "Nutrition for Growth Assessments Dataset",
  "2022 Global Nutrition Report Dataset"
)

link <- c(
  "https://globalnutritionreport.org/documents/348/2018_Global_Nutrition_Report_Dataset_F0lDqIh.xlsx",
  "https://globalnutritionreport.org/documents/573/2020_Global_Nutrition_Report_Dataset.xlsx",
  "https://globalnutritionreport.org/documents/729/2021_Global_Nutrition_Report_Dataset.xlsx",
  "https://globalnutritionreport.org/documents/718/Country-Nutrition-Profiles-data_February-2022.xlsx",
  "https://globalnutritionreport.org/documents/717/Nutrition-for-Growth-assessments-data_November-2021.xlsx",
  "https://globalnutritionreport.org/documents/891/2022_Global_Nutrition_Report_Data_jRPppzv.zip"
)

gnr_data <- tibble::tibble(year, code, file_type, name, link)

usethis::use_data(gnr_data, compress = "xz", overwrite = TRUE)