R interface to the Data Retriever.
The Data Retriever automates the tasks of finding, downloading, and cleaning up publicly available data, and then stores them in a local database or csv files. This lets data analysts spend less time cleaning up and managing data, and more time analyzing it.
This package lets you access the Retriever using R, so that the Retriever's data handling can easily be integrated into R workflows.
To use the R package rdataretriever you first need to install the Retriever.
Installers are available for all major operating systems from the Install page
or it can be installed from source.
The R package takes advantage of the Data Retriever's command line interface which must be enabled by adding it to the path on Mac platforms. On a Windows platform the Retriever should be added automatically to the path.
To install the development version of the R package rdataretriever, use the devtools package:
# install.packages("devtools")
library(devtools)
install_github("ropensci/rdataretriever")library(rdataretriever)
# List the datasets available via the Retriever
rdataretriever::datasets()
# Install the portal into csv files in your working directory
rdataretriever::install('portal', 'csv')
# Download the raw portal dataset files without any processing to the
# subdirectory named data
rdataretriever::download('portal', './data/')
# Install and load a dataset as a list
portal = rdataretriever::fetch('portal')
names(portal)
head(portal$species)To get citation information for the rdataretriever in R use citation(package = 'rdataretriever')
A big thanks to Ben Morris for helping to develop the Data Retriever. Thanks to the rOpenSci team with special thanks to Gavin Simpson, Scott Chamberlain, and Karthik Ram who gave helpful advice and fostered the development of this R package. Development of this software was funded by the National Science Foundation as part of a CAREER award to Ethan White.
