data-science-stacks
This is a simple starter pack to learn about serious computer science,
or a if you got some data and you wanna make some serious inquires
pipenv / docker based data science starter stacks
getting started
#
# IMPORTANT # it will say some shit like 👇
# The Jupyter Notebook is running at:
# 👉http://34cd4227ea1a:8888/
#
docker-compose up # pay it no mind, its lying to you
open a browser and go to localhost:8888
Stack
The stack is simplest described using an example below
voting example
TheOn codecation19, a troop of programmers(17 st) ranked 8 different activities (1 for most prioritized). This is how to over engineer a simple vote
open the Adventure jupyter notebook.
First cell
import pandas as pd
import seaborn as sns
from sklearn.cluster import KMeans
from matplotlib import pyplot as plt
sns.set_style("white", rc={'figure.figsize':(18.7,9.27)})
- We use
panda
as our dataframe handler etc, etc.. - We use seaborn for reasons unknown
- KMeans is used to try to split our adventures in similar interest groups
matplotlib
orplt
is used to draw beutiful diabrams- The interested reader can find out what the last instruction does (then write it down and send in as a pull request