R Interface to Google Charts

R interface to Google's chart tools, allowing users to create interactive charts based on data frames. Charts are displayed locally via the R HTTP help server. A modern browser with an Internet connection is required. The data remains local and is not uploaded to Google.


googleVis

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The googleVis package provides an interface between R and the Google's charts tools. It allows users to create web pages with interactive charts based on R data frames. Charts are displayed locally via the R HTTP help server. A modern browser with Internet connection is required. The data remains local and is not uploaded to Google.

Check out the examples from the googleVis demo.

Please read Google's Terms of Use before you start using the package.

Installation

You can install the stable version from CRAN:

install.packages('googleVis')

Usage

library(googleVis)
?googleVis
demo(googleVis)

See the googleVis package vignette for more details. For a brief introduction read the five page R Journal article.

License

This package is free and open source software, licensed under GPL 2 or later.

Creative Commons Licence
googleVis documentation by Markus Gesmann & Diego de Castillo is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("googleVis")

0.7.3 by Markus Gesmann, 2 years ago


https://mages.github.io/googleVis/


Report a bug at https://github.com/mages/googleVis/issues


Browse source code at https://github.com/cran/googleVis


Authors: Markus Gesmann [aut, cre] , Diego de Castillo [aut] , Joe Cheng [ctb] , Ashley Baldry [ctb] , Durey IngenierĂ­a [ctb]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports methods, jsonlite, utils

Suggests shiny, httpuv, knitr, rmarkdown, markdown, data.table


Imported by MetaLandSim, RLumShiny, bayesPop, bea.R, eAnalytics, mplot, nser, wppExplorer.

Suggested by BayesNetBP, Lahman, PerformanceAnalytics, bayesTFR, googlePublicData, spacetime.


See at CRAN