R/utils.R

In calcita/ech: Downloading and Processing Microdata from ECH-INE (Uruguay)

# #' This function allows you to get the IPC data
# #' @family dwnld_read
# #' @param folder ruta temporal para descargar el archivo
# #' @importFrom readxl read_xls
# #' @importFrom dplyr slice mutate select everything %>%
# #' @importFrom janitor clean_names excel_numeric_to_date
# #' @importFrom fs path
# #' @importFrom rlang .data
# #' @details
# #' Disclaimer: This script is not an official INE product.
# #' Aviso: El script no es un producto oficial de INE.

# get_ipc <- function(folder = tempdir()){
#
#   assertthat::assert_that(is.character(folder), msg = "Sorry... :( \n \t folder parameter must be character")
#   assertthat::assert_that(.x = curl::has_internet(), msg = "No internet access was detected. Please check your connection.")
#
#   u <- "https://www.ine.gub.uy/c/document_library/get_file?uuid=2e92084a-94ec-4fec-b5ca-42b40d5d2826&groupId=10181"
#   f <- fs::path(folder, "IPC gral var M_B10.xls")
#   if (identical(.Platform$OS.type, "unix")) {
#     try(utils::download.file(u, f, mode = 'wb', method = 'wget'))
#   } else {
#     try(utils::download.file(u, f, mode = 'wb', method = 'libcurl'))
#   }
#   suppressMessages({
#      df <- readxl::read_xls(f)
#      df <- df %>%
#        dplyr::slice(7, 10:length(df[[1]])-3)
#      names(df) <- df[1,]
#      df <- df[-c(1:4),]
#      df <- janitor::clean_names(df) %>%
#       dplyr::mutate(fecha = janitor::excel_numeric_to_date(as.numeric(as.character(.data$mes_y_ano)), date_system = "modern")) %>%
#       dplyr::select(fecha, dplyr::everything(), -mes_y_ano)
#     ipc_base2010 <- df
#   })
# }

#' This function allows you to organize dates
#' @family utils
#' @param data data frame with an 'yy' variable for the year, and a 'mm' variable for the month
#' @importFrom dplyr mutate case_when
#' @return data.frame
#' @export
# @examples
# df <- dates_ech()

dates_ech <- function(data) {
  data %>% dplyr::mutate(
    mm = dplyr::case_when(mm == "enero" ~ "01",
                          mm == "febrero" ~ "02",
                          mm == "marzo" ~ "03",
                          mm == "abril" ~ "04",
                          mm == "mayo" ~ "05",
                          mm == "junio" ~ "06",
                          mm == "julio" ~ "07",
                          mm == "agosto" ~ "08",
                          mm == "setiembre" ~ "09",
                          mm == "octubre" ~ "10",
                          mm == "noviembre" ~ "11",
                          TRUE ~ "12"),
    dd = "01",
    fecha = as.Date(paste(yy, mm, dd, sep = "-")))
}


# #' This function allows you to get the IPC data
# #' @family dwnld_read
# #' @param folder temporal folder
# #' @param region Montevideo ("M") or Interior ("I")
# #' @param sheet sheet number. Default 1.
# #' @importFrom readxl read_xls
# #' @importFrom dplyr slice mutate select everything filter_all slice any_vars bind_rows %>%
# #' @importFrom tidyr gather separate
# #' @importFrom janitor clean_names excel_numeric_to_date
# #' @importFrom fs path
# #' @return data.frame
# #' @details
# #' Disclaimer: This script is not an official INE product.
# #' Aviso: El script no es un producto oficial de INE.

# get_ipc_region <- function(folder = tempdir(), region, sheet = 1){
#   assertthat::assert_that(.x = curl::has_internet(), msg = "No internet access was detected. Please check your connection.")
#   assertthat::assert_that(is.character(folder), msg = "Sorry... :( \n \t folder parameter must be character")
#   assertthat::assert_that(region %in% c("M", "I"), msg = "Sorry... :( \n \t region parameter must be 'M' for Montevideo or 'I' for Interior")
#
#   if (region == "M") {
#     u <- "https://www.ine.gub.uy/c/document_library/get_file?uuid=c7628833-9b64-44a4-ac97-d13353ee79ac&groupId=10181"
#     f <- fs::path(folder, "IPC 3.1 indvarinc_ div M_B10_Mon.xls")
#   }
#   else {
#     u <- "https://www.ine.gub.uy/c/document_library/get_file?uuid=61f9e884-781d-44be-9760-6d69f214b5b3&groupId=10181"
#     f <- fs::path(folder, "IPC 3.2 indvarinc_ div M_B10_Int.xls")
#   }
#   if (identical(.Platform$OS.type, "unix")) {
#     try(utils::download.file(u, f, mode = 'wb', method = 'wget'))
#   } else {
#     try(utils::download.file(u, f, mode = 'wb', method = 'libcurl'))
#   }
#   suppressMessages({
#     df <- readxl::read_xls(f, sheet = sheet)
#     df <- df[,-1] %>% janitor::remove_empty("rows")
#     df <- dplyr::bind_rows(dplyr::slice(df, 1), dplyr::filter_all(df, dplyr::any_vars(grepl('ndice General', .))))
#     names(df) <- df[1,]
#     df <- df[-1,]
#     df <- df %>% dplyr::select(dplyr::contains("20")) %>%
#       janitor::clean_names()
#     df <- df %>% tidyr::gather(fecha, indice, names(df)[1]:names(df)[ncol(df)], factor_key = TRUE) %>%
#       tidyr::separate(fecha, into = c("mm", "yy"), sep = "_") %>%
#       ech::dates_ech() %>%
#       dplyr::select(fecha, indice)
#
#     if (region == "M") {
#       ipc_base2010_mdeo <- df
#     }
#     else{
#       ipc_base2010_int <- df
#     }
#   })
# }

# #' This function allows you to get the CBA and CBNA data
# #' @family dwnld_read
# #' @param folder temporal folder
# #' @param region Montevideo ("M"), Interior Urbano ("I"), Interior Rural ("R")
# #' @param sheet sheet number. Default 1.
# #'
# #' @importFrom readxl read_xls
# #' @importFrom dplyr slice mutate bind_cols %>%
# #' @importFrom janitor clean_names excel_numeric_to_date remove_empty
# #' @importFrom fs path
# #' @importFrom purrr map_df
# #' @importFrom curl has_internet
# #'
# #' @return data.frame
# #' @details
# #' Disclaimer: This script is not an official INE product.
# #' Aviso: El script no es un producto oficial de INE.

# get_cba_cbna <- function(folder = tempdir(), region, sheet = 1){
#   assertthat::assert_that(.x = curl::has_internet(), msg = "No internet access was detected. Please check your connection.")
#   assertthat::assert_that(is.character(folder), msg =  "Sorry... :( \n \t folder parameter must be character")
#   assertthat::assert_that(region %in% c("M", "I", "R"), msg =  "Sorry... :( \n \t region parameter must be 'M' for Montevideo, 'I' for Interior urbano or 'R' for Interior rural")
#
#   u <- "https://www.ine.gub.uy/c/document_library/get_file?uuid=1675e7d0-6fe0-49bd-bf3f-a46bd6334c0c&groupId=10181"
#   f <- fs::path(folder, "CBA_LP_LI_M.xls")
#   if (identical(.Platform$OS.type, "unix")) {
#     try(utils::download.file(u, f, mode = 'wb', method = 'wget'))
#   } else {
#     try(utils::download.file(u, f, mode = 'wb', method = 'libcurl'))
#   }
#   suppressMessages({
#     df <- readxl::read_xls(f, sheet = sheet)
#     date <- df[9:nrow(df),1]
#     names(date) <- "fecha"
#     date <- date %>%
#       dplyr::mutate(fecha = janitor::excel_numeric_to_date(as.numeric(as.character(fecha)), date_system = "modern")) %>%
#       janitor::remove_empty("rows")
#     df <- df[,-1] %>% janitor::remove_empty("rows") %>% janitor::remove_empty("cols")
#
#     if (region == "M") {
#       cba_mdeo <- df[, 1:3]
#       names(cba_mdeo) <- df[2, 1:3]
#       cba_mdeo <- cba_mdeo %>%
#         dplyr::slice(-1:-3) %>%
#         janitor::clean_names() %>%
#         purrr::map_df(as.numeric) %>%
#         dplyr::bind_cols(date,.)
#     } else if (region == "I") {
#       cba_int_urb <- df[, 4:6]
#       names(cba_int_urb) <- df[2, 4:6]
#       cba_int_urb <- cba_int_urb %>%
#         dplyr::slice(-1:-3) %>%
#         janitor::clean_names() %>%
#         purrr::map_df(as.numeric) %>%
#         dplyr::bind_cols(date,.)
#     } else {
#       cba_int_rur <- df[, 7:9]
#       names(cba_int_rur) <- df[2, 7:9]
#       cba_int_rur <- cba_int_rur %>%
#         dplyr::slice(-1:-3) %>%
#         janitor::clean_names() %>%
#         purrr::map_df(as.numeric) %>%
#         dplyr::bind_cols(date,.)
#     }
#   })
# }
#

# # This function allows you to get the IPAB (Indice de precios de alimentos y bebidas) data
# # @family dwnld_read
# # @param folder temporal folder
# # @param sheet sheet number. Default 1
# # @importFrom readxl read_xls
# # @importFrom janitor remove_empty
# # @importFrom dplyr bind_rows slice filter_all bind_cols any_vars mutate_all
# # @importFrom tidyr fill
# # @importFrom curl has_internet
# #
# # @return data.frame
# # @details
# # Disclaimer: This script is not an official INE product.
# # Aviso: El script no es un producto oficial de INE.

# get_ipab <- function(folder = tempdir(), sheet = 1){
#   assertthat::assert_that(.x = curl::has_internet(), msg = "No internet access was detected. Please check your connection.")
#   assertthat::assert_that(is.character(folder), msg =  "Sorry... :( \n \t folder parameter must be character")
#
#   u <- "https://www.ine.gub.uy/c/document_library/get_file?uuid=c4b5efaa-cdd4-497a-ab78-e3138e4f08dc&groupId=10181"
#   f <- fs::path(folder, "IPC Div M_B10.xls")
#   if (identical(.Platform$OS.type, "unix")) {
#     try(utils::download.file(u, f, mode = 'wb', method = 'wget'))
#   } else {
#     try(utils::download.file(u, f, mode = 'wb', method = 'libcurl'))
#   }
#   suppressMessages({
#     df <- readxl::read_xls(f, sheet = sheet)
#     df <- df[,-1:-2] %>% janitor::remove_empty("rows")
#     df <- dplyr::bind_rows(dplyr::slice(df, 1), dplyr::filter_all(df, dplyr::any_vars(grepl(c('Divisiones'), .))), dplyr::filter_all(df, dplyr::any_vars(grepl(c('Alimentos y Bebidas No Alcoh'), .))))
#     df[,1] <- c("yy", "mm", "indice")
#     df <- dplyr::bind_cols(t(df[1,]), t(df[2,]), t(df[3,]))
#     names(df) <- df[1,]
#     df <- df %>% dplyr::slice(-1) %>%
#       janitor::remove_empty("rows") %>%
#       tidyr::fill(yy) %>%
#       dplyr::mutate_all(tolower) %>%
#       ech::dates_ech() %>%
#       dplyr::select(fecha, indice)
#   })
# }

# #' This function allows you to get the IPAB (Indice de precios de alimentos y bebidas) data
# #' @family dwnld_read
# #' @param folder temporal folder
# #' @param region Montevideo ("M"), Interior Urbano ("I")
# #' @param sheet sheet number. Default 1
# #' @importFrom readxl read_xls
# #' @importFrom janitor remove_empty
# #' @importFrom dplyr bind_rows slice filter_all bind_cols any_vars mutate
# #' @importFrom tidyr drop_na separate
# #' @return data.frame

# get_ipab_region <- function(folder = tempdir(), region, sheet = 1){
#   assertthat::assert_that(.x = curl::has_internet(), msg = "No internet access was detected. Please check your connection.")
#   assertthat::assert_that(is.character(folder), msg = "Sorry... :( \n \t folder parameter must be character")
#   assertthat::assert_that(region %in% c("M", "I"), msg = "Sorry... :( \n \t region parameter must be 'M' for Montevideo or 'I' for Interior")
#
#   if (region == "M") {
#     u <- "https://ine.gub.uy/c/document_library/get_file?uuid=c7628833-9b64-44a4-ac97-d13353ee79ac&groupId=10181"
#     f <- fs::path(folder, "IPC 3.1 indvarinc_ div M_B10_Mon.xls")
#   } else {
#     u <- "https://ine.gub.uy/c/document_library/get_file?uuid=61f9e884-781d-44be-9760-6d69f214b5b3&groupId=10181"
#     f <- fs::path(folder, "IPC 3.2 indvarinc_ div M_B10_Int.xls")
#   }
#   if (identical(.Platform$OS.type, "unix")) {
#     try(utils::download.file(u, f, mode = 'wb', method = 'wget'))
#   } else {
#     try(utils::download.file(u, f, mode = 'wb', method = 'libcurl'))
#   }
#   suppressMessages({
#     df <- readxl::read_xls(f, sheet = sheet)
#     df <- df[,-1] %>% janitor::remove_empty("rows")
#     df <- dplyr::bind_rows(dplyr::slice(df, 1), dplyr::filter_all(df, dplyr::any_vars(grepl(c('Alimentos y Bebidas No Alcoh'), .))))
#     names(df) <- df[1,]
#     df <- df %>% janitor::remove_empty("cols")
#     df <- df[,-1]
#     df <- t(df)
#     df <- data.frame(df) %>%
#       tidyr::drop_na() %>%
#       tidyr::separate(X1, sep = " ", into = c("mm", "yy"))
#     names(df) <- c("mm", "yy", "indice")
#     df <- df %>% dplyr::mutate_all(tolower) %>%
#       ech::dates_ech() %>%
#       dplyr::select(fecha, indice)
#
#     if (region == "M") {
#       ipab_base2010_mdeo <- df
#     }
#     else{
#       ipab_base2010_int <- df
#     }
#   })
# }

#' This function allows you to calculate a deflator coefficient
#' @family income
#' @param base_month baseline month
#' @param base_year baseline year
#' @param index IPC or IPAB
#' @param level General index ('G'), Montevideo index ('M') or Interior index ('I')
#' @param df_year ECH year
#' @return vector
#' @importFrom dplyr select slice mutate
#' @importFrom rlang .data
#' @export
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.

deflate <- function(base_month = NULL,
                    base_year = NULL,
                    index = "IPC",
                    level = "G",
                    df_year = NULL) {

  assertthat::assert_that(level %in% c("G", "M", "I"), msg = "Sorry... :( \n \t level parameter must be 'G' for General, 'M' for Montevideo or 'I' for Interior")
  assertthat::assert_that(index %in% c("IPC", "IPAB"), msg = "Sorry... :( \n \t index parameter must be 'IPC' or 'IPAB'")

  if (nchar(as.character(base_month)) == 1) {
    base_month <- paste0("0", base_month)
  }

  if (index == "IPC" & level == "G") {
    df <- ech::ipc_base2010
  }  else if (index == "IPC" & level == "M") {
    df <- ech::ipc_base2010_mdeo
  } else if (index == "IPC" & level == "I") {
    df <- ech::ipc_base2010_int
  } else if (index == "IPAB" & level == "G") {
    df <- ech::ipab_base2010
  }  else if (index == "IPAB" & level == "M") {
    df <- ech::ipab_base2010_mdeo
  } else {
    df <- ech::ipab_base2010_int
  }

  mes_base <- df %>%
    dplyr::filter(fecha == paste0(base_year, "-", base_month, "-01")) %>%
    dplyr::select(indice) %>%
    as.numeric()

  rows1 <- which(df$fecha == paste0(as.numeric(df_year) - 1, "-",12, "-01"))
  rows2 <- which(df$fecha == paste0(df_year, "-",11, "-01"))

  indice <- df %>%
    dplyr::slice(rows1:rows2) %>%
    dplyr::select(indice)

  indice <- as.numeric(indice$indice)

  deflator <- dplyr::bind_cols(deflator = mes_base/indice, mes = 1:12)

}

#' This function allows you to get the Basket goods
#' @family income
#' @param data data.frame with the price of the basket of goods from Montevideo, Interior or Rural region
#' @param year the ECH year
#' @return data.frame
#' @export
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.
#'
#' @examples
#' df <- basket_goods(data = ech::cba_cbna_mdeo, year = 2018)

basket_goods <- function(data = ech::cba_cbna_mdeo,
                         year = NULL){

  assertthat::assert_that(is.data.frame(data), msg = "Sorry... :( \n \t data parameter must be data.frame")

  #ech::cba_cbna_int, ech::cba_cbna_rur
    rows1 <- which(data$fecha == paste0(as.numeric(year) - 1, "-",12, "-01"))
    rows2 <- which(data$fecha == paste0(year, "-",11, "-01"))

    df <- data %>%
      dplyr::slice(rows1:rows2)

}

#' This function allows you to labelled variables
#' @family utils
#' @param data data frame
#' @importFrom dplyr select mutate
#' @importFrom haven is.labelled
#' @importFrom labelled to_factor
#' @return data.frame
#' @export
#' @examples
#' df <- unlabelled(data = ech::toy_ech_2018)

unlabelled <- function(data = NULL){
  assertthat::assert_that(is.data.frame(data), msg = "Sorry... :( \n \t data parameter must be data.frame")
  d <- data %>% dplyr::mutate_if(haven::is.labelled, labelled::to_factor) #%>%
    #dplyr::mutate_if(is.factor, as.character)

}

#' This function allows you to calculate age groups
#' @family demographic
#' @param data data.frame
#' @param cut breaks points to cut a numeric variable
#' @param e27 Variable name of age
#' @return data.frame
#' @importFrom dplyr mutate
#' @importFrom haven labelled
#' @importFrom labelled var_label
#' @export
#'
#' @examples
#'#' toy_ech_2018 <- age_groups(data = ech::toy_ech_2018, cut = c(0, 4, 11, 17, 24))

age_groups <- function(data = ech::toy_ech_2018,
                       cut = c(0, 4, 11, 17, 24),
                       e27 = "e27") {

  assertthat::assert_that(is.data.frame(data), msg = glue:glue("Sorry... :( \n \t data parameter must be data.frame"))
  assertthat::assert_that(is.numeric(cut), msg = glue:glue("Sorry... :( \n \t cut parameter must be a numeric vector"))
  assertthat::assert_that(e27 %in% names(data), msg =  glue:glue("Sorry... :( \n \t {e27} is not in data"))

  if (min(data %>% dplyr::pull(e27)) < min(cut)) {
    cut <- c(min(data %>% dplyr::pull(e27)), cut)
  }
  if (max(data %>% dplyr::pull(e27)) > max(cut)) {
    cut <- c(cut, max(data %>% dplyr::pull(e27)))
  }

  data <- data %>% dplyr::mutate(age_groups = cut(e27, breaks = cut, include.lowest = TRUE, ordered_result = TRUE, labels = FALSE),
                                 age_groups = haven::labelled(age_groups, label = "Grupos de edad"))

  return(data)
}

#'  This function allows you to fix ht11 from 2013 to 2015
#' @family income
#' @param data data.frame
#' @param year survey year
#' @param ht11 Variable name of ht11
#' @param numero Variable name of numero
#'
#' @return data.frame
#' @export
#'
#' @examples
#' toy_ech_2018 <- organize_ht11(data = ech::toy_ech_2018, year = 2018)

organize_ht11 <- function(data, year, ht11 = "ht11", numero = "numero") {

  assertthat::assert_that(is.data.frame(data), msg = glue:glue("Sorry... :( \n \t data parameter must be data.frame"))
  assertthat::assert_that(is.numeric(year), msg = glue:glue("Sorry... :( \n \t year parameter must be a numeric value"))
  assertthat::assert_that(ht11 %in% names(data), msg =  glue:glue("Sorry... :( \n \t {ht11} is not in data"))
  assertthat::assert_that(numero %in% names(data), msg =  glue:glue("Sorry... :( \n \t {numero} is not in data"))

  if (year %in% 2013:2015) {
    data <- data %>%
      dplyr::group_by(numero) %>%
      dplyr::mutate(ht11 = max(ht11)) %>%
      dplyr::ungroup()
  }
  return(data)
}

#' This function allows you to fix education variables from 2021
#' @family education
#' @param data data.frame
#' @param year survey year
#' @param e49 Variable name of e49
#' @param e579 Variable name of e579
#' @param numero Variable name of numero
#'
#' @return data.frame
#' @export

organize_educ <- function(data, year, e49 = "e49", e579 = "e579", numero = "numero") {

  assertthat::assert_that(is.data.frame(data), msg = glue:glue("Sorry... :( \n \t data parameter must be data.frame"))
  assertthat::assert_that(is.numeric(year), msg = glue:glue("Sorry... :( \n \t year parameter must be a numeric value"))
  assertthat::assert_that(e49 %in% names(data), msg =  glue:glue("Sorry... :( \n \t {e49} is not in data"))
  assertthat::assert_that(e579 %in% names(data), msg =  glue:glue("Sorry... :( \n \t {e579} is not in data"))
  assertthat::assert_that(numero %in% names(data), msg =  glue:glue("Sorry... :( \n \t {numero} is not in data"))

  if (year %in% 2021:2022) {
    data <- data %>%
      dplyr::mutate(e193 = ifelse(e49 == 3 & e579 == 1, 1, # Variable name of attendance preescolar
                                  ifelse(e49 == 2 & e579 == 1, 3,
                                         ifelse(e49 == 1 & e579 == 1, 2, 0))),
                    e197 = ifelse(e49 == 3 & e579 %in% c(2, 3), 1, # Variable name of attendance primary
                                  ifelse(e49 == 2 & e579 %in% c(2, 3), 3,
                                         ifelse(e49 == 1 & e579 %in% c(2, 3), 2, 0))),
                    e201 = ifelse(e49 == 3 & e579 %in% c(4, 6), 1, # Variable name of attendance secondary
                                  ifelse(e49 == 2 & e579 %in% c(4, 6), 3,
                                         ifelse(e49 == 1 & e579 %in% c(4, 6), 2, 0))),
                    e212 = ifelse(e49 == 3 & e579 %in% c(5, 7, 8), 1,# Variable name of attendance technical school (non-university)
                                  ifelse(e49 == 2 & e579 %in% c(5, 7, 8), 3,
                                         ifelse(e49 == 1 & e579 %in% c(5, 7, 8), 2, 0))),
                    e215 = ifelse(e49 == 3 & e579 == 9, 1, # Variable name of attendance magisterio
                                  ifelse(e49 == 2 & e579 == 9, 3,
                                         ifelse(e49 == 1 & e579 == 9, 2, 0))),
                    e218 = ifelse(e49 == 3 & e579 == 10, 1, # Variable name of attendance university
                                  ifelse(e49 == 2 & e579 == 10, 3,
                                         ifelse(e49 == 1 & e579 == 10, 2, 0))),
                    e221 = ifelse(e49 == 3 & e579 == 11, 1, # Variable name of attendance tertiary
                                  ifelse(e49 == 2 & e579 == 11, 3,
                                         ifelse(e49 == 1 & e579 == 11, 2, 0))),
                    e224 = ifelse(e49 == 3 & e579 == 12, 1, # Variable name of attendance postgrade
                                  ifelse(e49 == 2 & e579 == 12, 3,
                                         ifelse(e49 == 1 & e579 == 12, 2, 0))),
                    e201_1 = e201_1c, # finalizo nivel edu media
                    e212_1 = ifelse(e201_1d == 1, e201_1d, e201_1b)) # finalizo nivel edu tecnica
    if (!any(colnames(data) %in% c("e51_4", "e51_7"))) {
      data <- data %>%
        dplyr::mutate(e51_4 = e51_4_a, e51_7 = e51_4_b)
    }


  }
  return(data)
}


# #' This function allows you to get the CIIU data
# #' @family dwnld_read
# #' @param folder temp folder
# #' @param version by default the last ciiu version
# #' @importFrom utils read.csv
# #' @importFrom pdftables convert_pdf
# #' @importFrom rstudioapi askForSecret
# #' @export
# #' @details
# #' Disclaimer: This script is not an official INE product.
# #' Aviso: El script no es un producto oficial de INE.
#
# get_ciiu <- function(folder = tempdir(),
#                      version = 4){
#   assertthat::assert_that(is.character(folder), msg = "Sorry... :( \n \t folder parameter must be character")
#   assertthat::assert_that(is.numeric(version), msg = "Sorry... :( \n \t version parameter must be numeric")
#   assertthat::assert_that(.x = curl::has_internet(), msg = "No internet access was detected. Please check your connection.")
#   u <- "https://www.ine.gub.uy/documents/10181/33330/CORRESPONDENCIA+CIUU4+A+CIUU3.pdf/623c43cb-009c-4da9-b48b-45282745063b"
#   f <- fs::path(folder, "ciiu4.pdf")
#   if (identical(.Platform$OS.type, "unix")) {
#     try(utils::download.file(u, f, mode = 'wb', method = 'wget'))
#   } else {
#     try(utils::download.file(u, f, mode = 'wb', method = 'libcurl'))
#   }
#   key <- rstudioapi::askForSecret("api_key")
#   pdftables::convert_pdf(f, "ciiu4.csv",api_key = key)
#   df <- read.csv("ciiu4.csv")
#   df <- df[,-3]
#   names(df) <- c("ciiu_4","description", "ciiu_3")
#   df <- df[-1,]
#   df[] <- lapply(df, textclean::replace_non_ascii)
#   ciiu4 <- df
# }


#' Pipe operator
#' See \code{dplyr::\link[dplyr]{\%>\%}} for details.
#' @name %>%
#' @rdname pipe
#' @keywords internal
#' @export
#' @importFrom dplyr %>%
#' @usage lhs \%>\% rhs
#' @return No return value, called for side effects
NULL

#' add_geom
#' See \code{geouy::\link[geouy]{add_geom}} for details.
#' @return sf and data.frame object
#' @name add_geom
#' @rdname add_geom
#' @keywords internal
#' @export
#' @importFrom geouy add_geom
NULL

#' plot_geouy
#' See \code{geouy::\link[geouy]{plot_geouy}} for details.
#' @return ggplot object of a choropleth map with x geometries and col values.
#' @name plot_geouy
#' @rdname plot_geouy
#' @keywords internal
#' @export
#' @importFrom geouy plot_geouy
NULL