**Revolutions**, and kindly contributed to R-bloggers)

by Matt Sundquist

co-founder of Plotly

Domino's new R Notebook and Plotly's R API let you code, make interactive R and ggplot2 graphs, and collaborate entirely online. Here is the Notebook in action:

To execute this Notebook, or to build your own, head to Domino's Plotly Project. The GIF below shows how to get started: choose an R session, press "Open Notebook", and choose the "R Notebook" file. For sensitive data, see Domino On-Premise and Plotly Enterprise.

## Overlaid Histogram

This plot, like the rest in this post, was made in the R Notebook with ggplot2, then converted to an interactive plot with one line of code. The plot is drawn with D3.js. You can hover your mouse to see text, click and drag to zoom, and toggle traces on and off by clicking them in the legend. check out our GitHub page to see our ggplot2 support.

## Anscombe's Quartet

Next up, let's visualize Anscombe's Quartet. Head to the R Notebook to see the R code for this.

## Bar Charts

Interactive bar charts let you hover and filter. Press the legend items to filter the plot. Head to the R Notebook to see the code.

## 3D Plots

Plotly and Domino let you transition ggplot2 plots into interactive 3D plots. Head to the R Notebook to see the code.

## Error Bars

If you use error bars, you can see the values when you hover your mouse. Head to the R Notebook to see the code.

## Dendrograms

We can also make dendrograms; this example uses ggdendro and ggplot2. Head to the R Notebook to see the example.

## Box plots

You can make interactive box plots from ggplot2 and share them.

## Usage

Domino Notebooks can run Python, R, Julia, and Scala. Each Notebook can be shared in the Domino Cloud or exported as an IPython Notebook, HTML or reST file. Notebooks support LaTeX, and allow you to use Markdown, headers, import images, and display iframes.

Plotly graphs can be embedded in Notebooks, dashboards, HTML, knitr, or Shiny. Every Plotly graph can be exported in varied programming languages and image types. For example, for the boxplot above:

- https://plot.ly/~r_user_guide/1079.png
- https://plot.ly/~r_user_guide/1079.svg
- https://plot.ly/~r_user_guide/1079.pdf
- https://plot.ly/~r_user_guide/1079.eps
- https://plot.ly/~r_user_guide/1079.py
- https://plot.ly/~r_user_guide/1079.m
- https://plot.ly/~r_user_guide/1079.jl
- https://plot.ly/~r_user_guide/1079.json
- https://plot.ly/~r_user_guide/1079.embed

This is our first pass at showing how you can use Domino and Plotly for coding and plotting in R. Have ideas? Suggestions? Other collaboration or Notebook projects you'd like to see? We're at @DominoDataLab and @DominoDataLab and welcome your suggestions.

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**Revolutions**.

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