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