Ashish Patel ashishpatel26

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!

Disclaimer 3: I found the Cookiecutter Data Science page after finishing this blog post. Many ideas overlap here, though some directories are irrelevant in my work -- which is to

	;What does this script do?
	;It's a workaround for broken G910 Logitech keyboards (possibly other keyboards too) whereby some keys occasionally register multiple keystrokes for one kkkkkeypress.
	;The key bug appears because keyboard registers multiple keystrokes in a very short timespan even though you pressed the key only once.
	;This script makes it so the subsequent keystrokes registered in a very short timespan are ignored thus outputing the key only for the first stroke.

	;List all your broken keys between quotes below. I.e. if your broken keys are g and f then the line below shoud be
	;brokenKeys := "gf"
	brokenKeys := "gf"

	/*
	* Academy Engraved LET *
	AcademyEngravedLetPlain
	---------------------
	* Al Nile *
	AlNile
	AlNile-Bold
	---------------------
	* American Typewriter *
	AmericanTypewriter

	import pandas as pd
	import numpy as np
	import matplotlib
	import matplotlib.pyplot as plt
	import seaborn as sns
	import missingno
	import warnings
	warnings.filterwarnings("ignore")
	%matplotlib inline

	from sklearn.cluster import KMeans
	import pandas as pd

	data = {'one': [1., 2., 3., 4., 3., 2., 1.], 'two': [4., 3., 2., 1., 2., 3., 4.]}
	data = pd.DataFrame(data)

	n_clusters = 2

	for col in data.columns:
	kmeans = KMeans(n_clusters=n_clusters)