knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" ) library(magrittr)
unclass(desc::desc_get_authors(here::here("DESCRIPTION"))) %>% purrr::keep(~"aut" %in% .$role) %>% purrr::map_chr(~paste(.$given, .$family)) %>% paste(collapse = ", ") %>% paste0("Authors: _", ., "_") %>% cat()
The cites package provides a complete extract of the CITES wildlife trade database.
Install the cites package with this command:
source("https://install-github.me/ecohealthalliance/cites")
The main function in cites is cites_data()
. This returns the main
CITES database as a dplyr tibble.
cites makes use of datastorr to manage data download.
The first time you run cites_data()
the package will download the most recent version of the database (~32MB). Subsequent calls will load the database from storage on your computer.
The CITES database is stored as an efficiently compressed .fst
file, and loading it loads it a
a remote dplyr source. This means
that it does not load fully into memory on load, but some limited operations
(column selection) can be performed on-disk. If you wish to manipulate it as a data frame, simply call dplyr::collect()
to load it fully into memory, like so:
all_cites <- cites_data() %>% collect()
Note that the full database will be approximately 270 MB in memory.
cites_codes()
returns a data frame with descriptions of the codes in the
various columns of cites_data()
. This is useful for lookup
or joining with the main data for more descriptive outputs. The ?cites_code
help file also has a searchable table of these codes. cites_metadata()
provides field descriptions and cites_parties()
lists the CITES party countries
and the date they joined the treaty.
See the developer README for more on the data-cleaning process.
Please give us feedback or ask questions by filing issues
cites is developed at EcoHealth Alliance. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
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