Install

Install the package

You can install the latest development version of floraR package from GitHub as follows:

if (!requireNamespace("BiocManager", quietly = TRUE)) 
install.packages("BiocManager") 

# Install the development version of floraR from GitHub, 
# together with its required dependencies 
BiocManager::install("DBOSlab/floraR", dependencies = TRUE)

Caution

floraR requires R (>= 4.1.0). If you already have a recent R installation, you can skip straight to the install step above.

library(floraR)

Optional packages for the curation tools

flora_species_gap() reads Plants of the World Online data fastest from a local copy of the World Checklist of Vascular Plants, provided by the rWCVPdata package (not on CRAN):

install.packages("rWCVPdata",
                 repos = c("https://matildabrown.github.io/drat",
                           "https://cloud.r-project.org"))

flora_distribution_gap() can also use REFLORA herbarium specimens through the refloraR package, and speciesLink records with a free speciesLink API key. None of these are needed for the rest of the package.

Quick Start

Once installed, a good first step is to check which Flora e Funga do Brasil dataset versions are currently published:

flora_version()

Most functions — including flora_records(), flora_search(), flora_get_children_taxa(), flora_species_gap(), and flora_distribution_gap() — download and parse the FFB dataset automatically the first time you call them, and reuse the same local cache on subsequent calls, so you rarely need to call flora_download()/flora_parse() yourself unless you want to inspect the raw data directly.

From there, browse the How-To Articles to learn how to download and parse checklist data, filter records by taxonomic or geographic criteria, resolve your own species names against the checklist, explore the taxonomic hierarchy, find species and state records missing from FFB to help expand its monographs, and curate new records. The workflow diagram on the Articles page shows how the functions fit together.

--- title: "Install" format: html: toc: true --- <style> body { background-image: url('/figures/ffb-background.png'); background-repeat: repeat-y; background-size: cover; background-attachment: fixed; background-position: top center; position: relative; z-index: 0; } .background-overlay { position: fixed; top: 0; left: 0; width: 100%; height: 100%; background-color: rgba(255, 255, 255, 0.85); z-index: -1; } </style> ## Install the package You can install the latest development version of `floraR` package from [GitHub](https://github.com/DBOSlab/floraR) as follows: ```{r} #| eval: false if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") # Install the development version of floraR from GitHub, # together with its required dependencies BiocManager::install("DBOSlab/floraR", dependencies = TRUE) ``` :::{.callout-caution} `floraR` requires R (>= 4.1.0). If you already have a recent R installation, you can skip straight to the install step above. ::: ```{r} #| eval: false library(floraR) ``` :::{.callout-note} ## Optional packages for the curation tools `flora_species_gap()` reads Plants of the World Online data fastest from a local copy of the World Checklist of Vascular Plants, provided by the [rWCVPdata](https://github.com/matildabrown/rWCVPdata) package (not on CRAN): ```r install.packages("rWCVPdata", repos = c("https://matildabrown.github.io/drat", "https://cloud.r-project.org")) ``` `flora_distribution_gap()` can also use REFLORA herbarium specimens through the [refloraR](https://github.com/DBOSlab/refloraR) package, and speciesLink records with a free [speciesLink](https://specieslink.net) API key. None of these are needed for the rest of the package. ::: ## Quick Start Once installed, a good first step is to check which Flora e Funga do Brasil dataset versions are currently published: ```{r} #| eval: false flora_version() ``` Most functions — including `flora_records()`, `flora_search()`, `flora_get_children_taxa()`, `flora_species_gap()`, and `flora_distribution_gap()` — download and parse the FFB dataset automatically the first time you call them, and reuse the same local cache on subsequent calls, so you rarely need to call `flora_download()`/`flora_parse()` yourself unless you want to inspect the raw data directly. From there, browse the [How-To Articles](/articles/index.qmd) to learn how to download and parse checklist data, filter records by taxonomic or geographic criteria, resolve your own species names against the checklist, explore the taxonomic hierarchy, find species and state records missing from FFB to help expand its monographs, and curate new records. The [workflow diagram](/articles/index.qmd) on the Articles page shows how the functions fit together.