Quick Tips
•Keep file paths short and sensible.
•Don't use funky characters and spaces in your file names, these cause trouble because of differences in Mac/Windows systems.
•Always pull before you push in case someone has done any work since the last time you pulled - you wouldn't want anyone's work to get lost or to have to resolve many coding conflicts.
Comment your code to make it readable and understandable for others and ensures reproducibility.
Clean Code Guidelines
• How to organize clean code:
o Code should only be relevant to the tables/graphs presented in research paper
o Code should be divided into sections; descriptive, bivariate, stratified (if applicable), multivariate
o Have section headers for each section that are in the form of comments. Have a brief summary of the steps for each section
o Include any external materials that need to be downloaded in order to run code
o Include name of dataset when data analyst originally sent it to you so that data analyst is aware of which dataset to retrieve when he/she reruns the code
• More details:
o Divide ‘clean code’ document itself into segments in which you designate how you want each section/subsection of clean code to appear
o Give example of the information you want supplied in the first comments of the clean code (eg. Name of original dataset, title of research topic, list of external materials that need to be downloaded before running code, etc.)
o Divide the ‘clean code’ document into sections such as descriptive, bivariate, stratified, and multivariate and give a brief example of clean code for each section
o You can include extra sections such as illustrations of how to divide code into subsections for scenarios in which a multiple analysis were done within the same section