How does the evolution from EDA -> analysis package work?

[mara]

Here's one post by @rmflight that might be of interest: "Creating an analysis as a package and vignette". There have also been a few threads here that could also help fill in the mysterious middle.

• @ehagen's response on Best Practice for good documented reproducible analysis

Best Practice for good documented reproducible analysis

My first step is to create a data package: http://r-pkgs.had.co.nz/data.html I put my raw data and processing scripts in a "data-raw" directory, and I treat the raw data files like master negatives: I try to never alter them, instead making all changes via r code. I also try to "normalize" my data: instead of creating one gigantic data frame, I divide the data into separate data frames, such as demographics, biomarkers, and survey items, each with the participant ID number, which I then join together as needed. Rationale for creating a data package I find that I often want to reanalyze my data a few years later, or hand it off to a grad student for further analysis, but that this is r…

• Data Science Project Template for R
• Containers and R

There are probably a few more, but those might get you rolling!