import quandl
import pandas as pd
import datetime
import pandas.io.data as web
import matplotlib.pyplot as plt
from matplotlib import style

start = datetime.datetime(2008, 1, 1)
end = datetime.datetime(2016, 8, 21)

df = web.DataReader("SPY", "yahoo", start, end)
df['Close'].plot()

plt.legend()

api_key = open('quandlapikey.txt','r').read()
df = quandl.get('LLOYDS/BDI', authtoken=api_key)

df.plot()

plt.legend()
plt.show()



					
				

If you want to plot them on the same axis using that specific method, then you'd need to merge the two dataframes into one dataframe, then plot both columns at the same time.

Harrison,

I was able to plot both of these but I need to adjust the Y scale as value and X scale as years.   Any advice would be appreciated.  Thank you!

[CODE]
import quandl
import pandas as pd
import datetime
import pandas.io.data as web
import matplotlib.pyplot as plt
from matplotlib import style

df1 = pd.read_csv('SPY.csv')
df1['Adj Close'].to_csv('newSPY.csv')
df2 = pd.read_csv('baltic.csv')
df2['Index'].to_csv('newBaltic.csv')

df3 = pd.merge(df1,df2)

df3.plot()
plt.xlabel('Date')
plt.ylabel('Value')
plt.title('Baltic Dry Index vs. SPX')
plt.legend()

plt.show()
[CODE]