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CommunityData:Build papers
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== Style notes and more details (add as needed) == * The typical directory structure that I use is something like: /code 01_script.py 02_script.py 03_analysis.R README /data /raw_data raw_data_file.csv measures.csv analyzed_data.RData /paper /data analyzed_data.RData (symlinked) /figures (any figures not created with knitr) paper.Rtex The code all lives in one place, with a README that explains what the pieces do. Don't underestimate the importance of a README and well-commented code. Your future self will thank you. The data lives in another place, with raw_data which is read-only (and may or may not be stored in git, depending on the size). This raw data is used to create measures (and possibly some intermediate files). Analysis is done on the measures file, and stored in an RData file. It is tempting to put as much of the analysis workflow as possible into the .Rtex file but these files can quickly become difficult to compile and unwieldy. It's often better to do the heavy lifting in a separate script, import an .RData file in the paper, and do things like creating plots and running simple statistical tests in the paper itself. * You may need to use [https://tex.stackexchange.com/questions/25701/bibtex-vs-biber-and-biblatex-vs-natbib natbib] for some journal submission styles. The stackexchange page linked above helps to explain how to do that (but if anyone wants to give more detailed instructions, please do!).
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