Cookiecutter instructions

README.Rmd

@@ -141,6 +141,16 @@ As noted above, to keep the image size down, I've only provided a Jupyter notebo
 3. Enter `source activate jupyter`.
 4. Use `conda search` to find packages in the Conda ecosystem, then install them with `conda install`. You can also install packages with `pip` if they're not in the Conda repositories.
 
+### Creating a Cookiecutter data science project
+Reference: <https://drivendata.github.io/cookiecutter-data-science/>
+
+1. Open a new terminal using the `New -> Terminal` dropdown at the upper right of the `Home` tab.
+2. Enter `./make-cookiecutter-project`.
+
+The script will install `cookiecutter` in the `jupyter` environment if necessary. Then it will launch the Cookiecutter data science interactive setup to create a new project in `/home/jupyter/Projects`.
+
+Follow the instructions to set up the project.
+
 ## RStudio
 This service is based on the `rocker/rstudio` image from Docker Hub: <https://hub.docker.com/r/rocker/rstudio/>. I've added header files so that the R packages `RPostgres`, `odbc`, `sf` and `devtools` will install from source, but there are no R packages on the image besides those that ship with `rocker/rstudio`.
 

README.md

@@ -12,6 +12,8 @@
     -   [Miniconda](#miniconda)
         -   [Setting up `git`](#setting-up-git-1)
         -   [Installing packages](#installing-packages)
+        -   [Creating a Cookiecutter data science
+            project](#creating-a-cookiecutter-data-science-project)
     -   [RStudio](#rstudio)
         -   [Setting up `git`](#setting-up-git-2)
         -   [Installing R packages](#installing-r-packages)
@@ -239,6 +241,20 @@ Jupyter notebook server. To install packages:
     install them with `conda install`. You can also install packages
     with `pip` if they’re not in the Conda repositories.
 
+### Creating a Cookiecutter data science project
+
+Reference: <https://drivendata.github.io/cookiecutter-data-science/>
+
+1.  Open a new terminal using the `New -> Terminal` dropdown at the
+    upper right of the `Home` tab.
+2.  Enter `./make-cookiecutter-project`.
+
+The script will install `cookiecutter` in the `jupyter` environment if
+necessary. Then it will launch the Cookiecutter data science interactive
+setup to create a new project in `/home/jupyter/Projects`.
+
+Follow the instructions to set up the project.
+
 RStudio
 -------