Initial commit

.github/workflows/binder-badge.yml

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+name: binder-badge
+on:
+  pull_request_target:
+
+jobs:
+  badge:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: manics/action-binderbadge@main
+        with:
+          githubToken: ${{ secrets.GITHUB_TOKEN }}

README.md

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+# r-conda
+
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/betatim/r-conda/master?urlpath=rstudio)
+
+> R and RStudio in repo2docker without waiting for packages to compile!
+
+Jupyter+R: [![Binder](http://mybinder.org/badge_logo.svg)](http://mybinder.org/v2/gh/binder-examples/r-conda/master?filepath=index.ipynb)
+
+RStudio: [![Binder](http://mybinder.org/badge_logo.svg)](http://mybinder.org/v2/gh/binder-examples/r-conda/master?urlpath=rstudio)
+
+Binder supports using R and RStudio, with libraries pinned to a specific versions.
+
+Install R itself and your required R packages via conda packages. Installing conda packages is faster than
+installing CRAN packages. This is because CRAN packages need compiling during the install process and conda
+packages do not.
+
+For some R packages there is no corresponding conda-forge package yet, in that case take a look at https://github.com/binder-examples/r. Note that these two approaches cannot be combined, so you cannot install R packages via Conda and via an `install.R` file at the same time. You can check if a required R package is available on the Conda Forge website at https://conda-forge.org/feedstock-outputs/ by searching for `r-PACKAGENAME`. You can install R packges from other sources using a `postBuild` script.
+
+Both [RStudio](https://www.rstudio.com/) and [IRKernel](https://irkernel.github.io/)
+are installed by default, so you can use either the Jupyter notebook interface or
+the RStudio interface.

environment.yml

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+channels:
+  - conda-forge
+dependencies:
+  - r-base=3.6
+  - r-tidyverse
+