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Reproducible Project Workflow in R (with ProjectTemplate)

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ProjectTemplate is an R package that makes it easy to create and run projects so that you can spend less time thinking about organization and more time analyzing data.

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Reproducible Project Workflow in R (with ProjectTemplate)

  1. 1. Reproducible Project Workflow in R (with ProjectTemplate) Caitlin Hudon, Sr. Data Analyst @
  2. 2. Why reproducible workflow matters
  3. 3. Things I care about (in structuring projects) + Easy to find things (reports, data, etc.) + Easy to share + Ability to update with new data + Reproducibility + Being able to quickly verify results + The sanity of my future self
  4. 4. Enter:
  5. 5. Technical Benefits of ProjectTemplate + Easy to create new projects + Organizes and standardizes your projects + Automatically loads data and R packages needed + Automatically runs data munging scripts
  6. 6. Non-technical benefits + Automates the thoughtless parts of your project (so you can use your energy on the important stuff) + Easier for someone new to your project to understand steps / data / preparation involved to execute it
  7. 7. Create a project library(‘ProjectTemplate’) create.project(‘new_project’)
  8. 8. New ProjectTemplate Project Munge Folder Data Folder Config Folder → global.dcf file
  9. 9. Load a project library(‘ProjectTemplate’) setwd(‘~/projects/new_project’) load.project()
  10. 10. Advice + Number files in the munge folder so they run in order + Avoid manually updating raw data files (do this in code!) + Edit the global.dcf file (in config folder) to add libraries you use, load libraries automatically, and adjust “strings as factors” settings + Lots of other ways to make analysis reproducible; ProjectTemplate is one part of larger ecosystem
  11. 11. Cheat Sheet ProjectTemplate home page + Don’t miss the tutorial! Great discussion on best practices for managing analysis projects The talk that got me interested in ProjectTemplate (thanks, Hilary Parker!)
  12. 12. Questions? Ideas? @beeonaposy