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A clean environment to organise code, reports, data sets and documentation is crucial in large analytical projects.

The create_project function automatically creates a clean template environment, along with an R project file–anchoring working directories to enable simultaneously working across multiple projects. It works across all platforms–Windows, Mac, and Linux.

This vignette walks though what to expect in this project.

library(WAACHShelp) # Let's load the WAACHShelp package

Function specifics

The create_project has a small set of arguments:

  • Project name
    • project_name
  • Folders – should the following folders be created for the project? The default for these is TRUE.
    • data
    • reports
    • output
    • docs
  • Other folders
    • Should any other folders (not contained in the above) be created?

Running the function

Suppose we have just created an empty folder for a project wherever we like (could be local, in a network drive, etc.).

Step 1:

Create a folder for our project contents to sit.

For the sake of this example, I have created a folder called “test_project” in Documents.

Empty folder called test_project in My Documents
Empty folder called test_project in My Documents

Step 2:

Now we can run our function in R. This can be done from a null project, or from terminal.

I have left all of the data, reports, output, arguments as default (TRUE). This means they will all be created.

create_project(project_name = "test_project")

This opens the following window:

Navigate to the test_project folder we created earlier.

Step 3:

Done!

All of the folders have been created, in addition to an R project that takes the name given by the project_name argument.