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Copy file name to clipboardExpand all lines: CONTRIBUTING.md
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@@ -3,7 +3,7 @@ We welcome contributions to the **ggvis** package. To submit a contribution:
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1.[Fork](https://github.com/rstudio/ggvis/fork) the repository and make your changes.
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2. Ensure that you have signed the [individual](http://www.rstudio.com/wp-content/uploads/2014/06/RStudioIndividualContributorAgreement.pdf) or [corporate](http://www.rstudio.com/wp-content/uploads/2014/06/RStudioCorporateContributorAgreement.pdf) contributor agreement as appropriate. You can send the signed copy to jj@rstudio.com.
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2. Ensure that you have signed the [individual](https://www.rstudio.com/wp-content/uploads/2014/06/RStudioIndividualContributorAgreement.pdf) or [corporate](https://www.rstudio.com/wp-content/uploads/2014/06/RStudioCorporateContributorAgreement.pdf) contributor agreement as appropriate. You can send the signed copy to jj@rstudio.com.
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3. Submit a [pull request](https://help.github.com/articles/using-pull-requests).
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ggvis is currently dormant. We fundamentally believe in the ideas that underlie ggvis: reactive programming is the right foundation for interactive visualisation. However, we are not currently working on ggvis because we do not see it as the most pressing issue for the R community as you can only use interactive graphics once you've successfuly tackled the rest of the data analysis process.
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We hope to come back to ggvis in the future; in the meantime you might want to try out [plotly](https://plot.ly/ggplot2/getting-started/) or creating inteactive graphics [with shiny](https://blog.rstudio.com/2015/06/16/shiny-0-12-interactive-plots-with-ggplot2/).
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We hope to come back to ggvis in the future; in the meantime you might want to try out [plotly](https://plotly.com/ggplot2/getting-started/) or creating inteactive graphics [with shiny](https://blog.rstudio.com/2015/06/16/shiny-0-12-interactive-plots-with-ggplot2/).
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## Introduction
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The goal of ggvis is to make it easy to describe interactive web graphics in
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R. It combines:
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* a grammar of graphics from [ggplot2](http://github.com/hadley/ggplot2),
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* a grammar of graphics from [ggplot2](https://github.com/tidyverse/ggplot2),
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* reactive programming from [shiny](http://github.com/rstudio/shiny), and
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* reactive programming from [shiny](https://github.com/rstudio/shiny), and
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* data transformation pipelines from [dplyr](http://github.com/hadley/dplyr).
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* data transformation pipelines from [dplyr](https://github.com/tidyverse/dplyr).
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ggvis graphics are rendered with [vega](https://github.com/trifacta/vega), so you can generate both raster graphics with [HTML5 canvas](http://diveintohtml5.info/canvas.html) and vector graphics with
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[svg](http://en.wikipedia.org/wiki/Scalable_Vector_Graphics). ggvis is less flexible than raw [d3](http://d3js.org/) or vega, but is much more succinct and is tailored to the needs of exploratory data analysis.
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ggvis graphics are rendered with [vega](https://github.com/trifacta/vega), so you can generate both raster graphics with [HTML5 canvas](https://diveintohtml5.info/canvas.html) and vector graphics with
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[svg](https://en.wikipedia.org/wiki/Scalable_Vector_Graphics). ggvis is less flexible than raw [d3](https://d3js.org/) or vega, but is much more succinct and is tailored to the needs of exploratory data analysis.
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If you find a bug, please file a minimal reproducible example at http://github.com/rstudio/ggvis/issues. If you're not sure if something is a bug, you'd like to discuss new features or have any other questions about ggvis, please join us on the mailing list: https://groups.google.com/group/ggvis.
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If you find a bug, please file a minimal reproducible example at https://github.com/rstudio/ggvis/issues. If you're not sure if something is a bug, you'd like to discuss new features or have any other questions about ggvis, please join us on the mailing list: https://groups.google.com/group/ggvis.
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## Installation
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mtcars %>% ggvis(~mpg, ~wt) %>% layer_points()
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```
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The vignettes, available from http://ggvis.rstudio.com/, provide many more details. Start with the introduction, then work your way through the more advanced topics. Also check out the
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The vignettes, available from https://ggvis.rstudio.com/, provide many more details. Start with the introduction, then work your way through the more advanced topics. Also check out the
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various demos in the `demo/` directory. See the basics in `demo/scatterplot.r`
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then check out the the coolest demos, `demo/interactive.r` and `demo/tourr.r`.
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