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.
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
# 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.
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