text_html_output_1.png
from subprocess import check_output

, # This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load in 
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory
from subprocess import check_output
print(check_output(["ls", "../input"]).decode("utf8"))
# Any results you write to the current directory are saved as output.
# ^^^ DEFAULT SETUP ABOVE HERE. EVERYTHING BELOW MUST BE ADDED
import seaborn as sns # plotting
from sklearn import tree # classification tree, see http://scikit-learn.org/stable/modules/tree.html