ericmjl

UPDATE: I have baked the ideas in this file inside a Python CLI tool called pyds-cli. Please find it here: https://github.com/ericmjl/pyds-cli

How to organize your Python data science project

Having done a number of data projects over the years, and having seen a number of them up on GitHub, I've come to see that there's a wide range in terms of how "readable" a project is. I'd like to share some practices that I have come to adopt in my projects, which I hope will bring some organization to your projects.

Disclaimer: I'm hoping nobody takes this to be "the definitive guide" to organizing a data project; rather, I hope you, the reader, find useful tips that you can adapt to your own projects.

Disclaimer 2: What I’m writing below is primarily geared towards Python language users. Some ideas may be transferable to other languages; others may not be so. Please feel free to remix whatever you see here!

resilar

% Output: http://i.imgur.com/88G3s9V.png
\begin{equation}
  \begin{split}
                 & \text{\large Primal} \\
    \text{min }  & \sum_{j=1}^s x_j + Bz \\
    \text{s.t. } &
    \begin{aligned}[t]
      x_j + z &\ge 1 & \forall j = 1,2,\dots,s \\
          x_j &\ge 0 & \forall j = 1,2,\dots,s \\
            z &\ge 0

stephenhardy

-- Remove the history from 
rm -rf .git

-- recreate the repos from the current content only
git init
git add .
git commit -m "Initial commit"

-- push to the github remote repos ensuring you overwrite history
git remote add origin git@github.com:<YOUR ACCOUNT>/<YOUR REPOS>.git