FAOSTAT (version 2.4.0)

download_faostat_bulk: Download bulk data from the faostat website https://www.fao.org/faostat/en/#data

Description

• get_faostat_bulk() loads the given data set code and returns a data frame.

• download_faostat_bulk() loads data from the given url and saves it to a compressed zip file.

• read_faostat_bulk() Reads the compressed .csv .zip file into a data frame. More precisely it unzips the archive. Reads the main csv file within the archive. The main file has the same name as the name of the archive. Note: the zip archive might also contain metadata files about Flags and Symbols.

In general you should load the data with the function get_faostat_bulk() and a dataset code. The other functions are lower level functions that you can use as an alternative. You can also explore the datasets and find their download URLs on the FAOSTAT website. Explore the website to find out the data you are interested in https://www.fao.org/faostat/en/#data Copy a "bulk download" url, for example they are located in the right menu on the "crops" page https://www.fao.org/faostat/en/#data/QC Note that faostat bulk files with names ending with "normalized" are in long format with a year column instead of one column for each year. The long format is preferable for data analysis and this is the format returned by the get_faostat_bulk() function.

Usage

download_faostat_bulk(url_bulk, data_folder = ".")
read_faostat_bulk(zip_file_name, encoding = "latin1", rename_element = TRUE)
get_faostat_bulk(code, data_folder = tempdir(), subset = "All Data Normalized")
read_bulk_metadata(dataset_code)

Value

data frame of FAOSTAT data

data frame of FAOSTAT data

data frame of FAOSTAT data

Arguments

url_bulk

character url of the faostat bulk zip file to download

data_folder

character path of the local folder where to download the data

zip_file_name

character name of the zip file to read

encoding

parameter passed to `read.csv`.

rename_element

boolean Rename the element column to snake case. To facilitate the use of elements as column names later when the data frame gets reshaped to a wider format. Replace non alphanumeric characters by underscores.

code

character. Dataset code

subset

character. Use read_bulk_metadata. Request all data, normalised data or region

dataset_code

character. Dataset code

Author

Paul Rougieux

Examples

if (FALSE) {

# Create a folder to store the data
data_folder <- "data_raw"
dir.create(data_folder)

# Load crop production data
crop_production <- get_faostat_bulk(code = "QCL", data_folder = data_folder)

# Cache the file i.e. save the data frame in the serialized RDS format for faster load time later.
saveRDS(crop_production, "data_raw/crop_production_e_all_data.rds")
# Now you can load your local version of the data from the RDS file
crop_production <- readRDS("data_raw/crop_production_e_all_data.rds")


# Use the lower level functions to download zip files, 
# then read the zip files in separate function calls.
# In this example, to avoid a warning about "examples lines wider than 100 characters"
# the url is split in two parts: a common part 'url_bulk_site' and a .zip file name part.
# In practice you can enter the full url directly as the `url_bulk`  argument.
# Notice also that I have choosen to load global data in long format (normalized).
url_bulk_site <- "https://fenixservices.fao.org/faostat/static/bulkdownloads"
url_crops <- file.path(url_bulk_site, "crop_production_E_All_Data_(Normalized).zip")
url_forestry <- file.path(url_bulk_site, "Forestry_E_All_Data_(Normalized).zip")
# Download the files
download_faostat_bulk(url_bulk = url_forestry, data_folder = data_folder)
download_faostat_bulk(url_bulk = url_crops, data_folder = data_folder)

# Read the files and assign them to data frames 
crop_production <- read_faostat_bulk("data_raw/crop_production_E_All_Data_(Normalized).zip")
forestry <- read_faostat_bulk("data_raw/Forestry_E_All_Data_(Normalized).zip")
 
# Save the data frame in the serialized RDS format for fast reuse later.
saveRDS(crop_production, "data_raw/crop_production_e_all_data.rds")
saveRDS(forestry,"data_raw/forestry_e_all_data.rds")
}