Why open data growth At rOpenSci we try to make it easier for people to use open data and contribute open data to the community. The question often arises: How much open data do we have? Another angle on this topic is: How much is open data growing? We provide access to dozens of data respositories through our various packages.

Editor’s note: This is a guest post by Matt Sundquist from Plot.ly. Ggplotly and Plotly’s R API let you make ggplot2 plots, add py$ggplotly(), and make your plots interactive, online, and drawn with D3. Let’s make some.1. Getting Started and Examples Here is Fisher’s iris data.library("ggplot2")ggiris <- qplot(Petal.Width, Sepal.Length, data = iris, color = Species)print(ggiris) Let’s make it in Plotly.

Reproducible research involves the careful, annotated preservation of data, analysis code, and associated files, such that statistical procedures, output, and published results can be directly and fully replicated. As the push for reproducible research has grown, the R community has responded with an increasingly large set of tools for engaging in reproducible research practices (see, for example, the ReproducibleResearch Task View on CRAN).