import jsm
import datetime
import numpy
import matplotlib.pyplot as plt
start=datetime.date(2015,1,1)
end=datetime.date(2016,4,21)
nis=q.get_historical_prices(7211,jsm.DAILY,start,end)
maz=q.get_historical_prices(7203,jsm.DAILY,start,end)
a=[]
b=[]
for i in range(318):
a.append(nis[i]._adj_close)
b.append(maz[i]._adj_close)

np.corrcoef(a,b)[0,1]
plt.plot(a,b,"o")
plt.show()

0.7395025