rdataretriever

R Interface to the Data Retriever


Keywords
data, data-science, database, datasets, r, r-package, rstats, science
License
MIT

Documentation

ecoretriever Build Status

R interface to the EcoData Retriever.

The EcoData Retriever automates the tasks of finding, downloading, and cleaning up publicly available ecological data, and then stores them in a local database or csv files. This lets ecologists spend less time cleaning up and managing data, and more time doing science.

This package lets you access the Retriever using R, so that the Retriever's data handling can easily be integrated into R workflows.

Installation

To use the R package ecoretriever you first need to install the Retriever. Installers are available for all major operating systems from the Download page or it can be installed from source.

Add Retriever to the path

The R package takes advantage of the EcoData 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.

Install R package

To install the development version of the R package ecoretriever, use the devtools package:

# install.packages("devtools")
library(devtools)
install_github("ropensci/ecoretriever")

Examples

library(ecoretriever)

# List the datasets available via the Retriever
ecoretriever::datasets()

# Install the Gentry dataset into csv files in your working directory
ecoretriever::install('Gentry', 'csv')

# Download the raw Gentry dataset files without any processing to the 
# subdirectory named data
ecoretriever::download('Gentry', './data/')

# Install and load a dataset as a list
Gentry = ecoretriever::fetch('Gentry')
names(Gentry)
head(Gentry$counts)

To get citation information for the ecoretriever in R use citation(package = 'ecoretriever')

Acknowledgements

A big thanks to Ben Morris for helping to develop the EcoData 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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