Dimitri dimi-tree

	import pandas as pd
	df = pd.read_csv(
	'http://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data',
	names = ['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)', 'class']
	)

	# store feature matrix in "X"
	X = df.drop('class', axis=1).values

	levels = {'Iris-setosa': 0, 'Iris-versicolor': 1, 'Iris-virginica':2}

	# Working with multiple stocks

	"""
	SPY is used for reference - it's the market
	Normalize by the first day's price to plot on "equal footing"
	"""

	import os
	import pandas as pd
	import matplotlib.pyplot as plt

	// Use Gists to store code you would like to remember later on
	console.log(window); // log the "window" object to the console