Code and data

Rules copied from https://web.stanford.edu/~gentzkow/research/CodeAndData.pdf

• Automation

  • Automate everything that can be automated
  • Write a single script that executes all code from beginning to end

• Directories

  • Separate directories by function
  • Separate files into inputs and outputs
  • Make directories portable

• Keys

  • Store cleaned data in tables with unique, non-missing keys
  • Keep data normalized as far into your code pipeline as you can

• Abstraction

  • Abstract to eliminate redundancy
  • Abstract to improve clarity
  • Otherwise, don’t abstract

• Documentation

  • Don’t write documentation you will not maintain
  • Code should be self-documenting

• Management

  • Manage tasks with a task management system
  • E-mail is not a task management system

• Code Style

  • Make your functions shy
  • Order your functions for linear reading
  • Use descriptive names
  • Pay special attention to coding algebra
  • Make logical switches intuitive
  • Be consistent
  • Check for errors

Source: Code and Data for the Social Sciences: A Practitioner's Guide