In scholaempirica/reschola: The Schola Empirica Package

This document is just for you, to help you find out how to work with such a project. You can delete it afterwards.

You have just created a {reschola} project.

It comes with some files and directories as suggested ways of organising your work:

• shared.R for variables and perhaps functions shared by more scripts. By default contains GDrive URL and project title, if provided during setup.
• data/01_retrieve.R helps you download files from your GDrive folder, if set. You can also use it to store code for retrieving other data. This should only hold things which you expect to only run once, or refresh rarely -- particularly things that take time or put a load on other servers.
• data/02_read.R should hold the code that reads the data and does any transformations immediately tied to data reading, e.g. setting data types or basic filtering. Again, this is code that you don't expect to change as you work on the actual analysis. You may want to save the result into .rds files in data/intermediate (or data/input if it is simply an .rds mirror of the input data saved for quick access).
• data/03_check-and-process.R should process data in data/input and save its outputs in data/processed. You may turn it into an .Rmd file if that is more convenient for you or split it into smaller pieces.
• [NN]_*.Rmd where NN is 01-98 is the actual analysis - may be an exploratory script, a partial analysis, or a report. Expected to be run in the order of their numbering, but ideally key components should work off data saved in data-input or data-intermediate.
• data/input should contain only unaltered input data as downloaded.
• data/processed should contain processed data files
• data/output should contain data that you expect to share externally that are the output of your project
• charts-output and reports-output for the obvious
• 99_reproducibility.R by default contains a description of the system and environment used to run the analysis. Use it to store any other information useful for reproducing the analysis (but not passwords etc.)

The data/input and data/processed have .gitignore files in to stop you form committing sensitive data to GitHub. Commit these .gitignore files to git. But only alter them if you are sure you know what you are doing.

You should feel free to move code between the analysis and the 00*_* scripts as you discover data transformations that should be made earlier on in the workflow.

Use build_all.R to tie these together - when run, it should rebuild the whole project from scratch, except perhaps downloading data. You may want to build different build_*.R as helpers for running different parts of the workflow while you work.

You can find guidelines for building Schola Empirica projects by running the following chunk:

vignette("workflow", package = "reschola")

(If R cannot find the vignette, make sure you add build_vignettes = TRUE in install_github("scholaempirica/reschola)).

If you are having trouble setting up your system, see

vignette("setup", package = "reschola")

For tips on using R and RStudio efficiently, run

vignette("tips", package = "reschola")

And if you would like to make changes to the reschola package, see

vignette("meta", package = "reschola")

The whole documentation for the package is online, run the following chunk to go there:

browseURL("https://scholaempirica.github.io/reschola")

scholaempirica/reschola documentation built on Feb. 1, 2024, 12:26 a.m.