FAOSTAT (version 2.4.0)

read_fao: Access FAOSTAT API

Description

Uses the same functionality as the web interface to pull data from the FAOSTAT API. Contains most of its parameters. Currently only works for datasets that have area, item, element and year. Values for Chinese countries are not yet deduplicated.

Usage

read_fao(
  area_codes,
  element_codes,
  item_codes,
  year_codes,
  area_format = c("M49", "FAO", "ISO2", "ISO3"),
  item_format = c("CPC", "FAO"),
  dataset = "RL",
  metadata_cols = c("codes", "units", "flags", "notes"),
  clean_format = c("make.names", "unsanitised", "unsanitized", "snake_case"),
  include_na = FALSE,
  language = c("en", "fr", "es")
)
getFAO(
  area_codes,
  element_codes,
  item_codes,
  year_codes,
  area_format = c("M49", "FAO", "ISO2", "ISO3"),
  item_format = c("CPC", "FAO"),
  dataset = "RL",
  metadata_cols = c("codes", "units", "flags", "notes"),
  clean_format = c("make.names", "unsanitised", "unsanitized", "snake_case"),
  include_na = FALSE,
  language = c("en", "fr", "es")
)

Value

data.frame in long format (wide not yet supported). Contains attributes for the URL and parameters used.

Arguments

area_codes

character. FAOSTAT area codes

element_codes

character. FAOSTAT element codes

item_codes

character. FAOSTAT item codes

year_codes

character. Vector of desired years

area_format

character. Desired area code type in output (input still needs to use FAOSTAT codes)

item_format

character. Item code

dataset

character. FAO dataset desired, e.g. RL, FBS

metadata_cols

character. Metadata columns to include in output

clean_format

character/function. Whether to clean columns. Either one of the formats described in [change_case] or a formatting function

include_na

logical. Whether to include NAs for combinations of dimensions with no data

language

character. 2 letter language code for output labels

Examples

if (FALSE) {

# Get data for Cropland (6620) Area (5110) in Antigua and Barbuda (8) in 2017
df = read_fao(area_codes = "8", element_codes = "5110", item_codes = "6620", 
year_codes = "2017")
# Load cropland area for a range of year
df = read_fao(area_codes = "106", element_codes = "5110", item_codes = "6620", 
year_codes = 2010:2020)

# Find which country codes are available
metadata_area <- read_dimension_metadata("RL", "area")
# Find which items are available
metadata_item <- read_dimension_metadata("RL", "item")
# Find which elements are available
metadata_element <- read_dimension_metadata("RL", "element")

}