Quandl also offers free commodity price data for almost 100 commodities ( See API for commodity data) so I decided to create a Jupyter notebook comparing SIPEF's stock price with the price of palm oil. Take a look at the full notebook I shared on github if you want to learn why - https://github.com/jorisp/tradingnotebooks/blob/master/Quandl_API_Euronext_SIPEFPalmOil.ipynb
Remarks:
- Be careful when embedding images in a Jupyter notebook that you want to publish on Github (see Images in Markdown not showing when uploaded to Git for a discussion on this) - filenames are case sensitive - I got it working using the url syntax
- To store the quandl key I used the approach outlined on how to use secrets in Jupyter Notebooks with python-dotenv
- I really like Matplotlib and its versatility in rendering capabilities in this notebook I used the ability to visualize multiple time series (see code preview below) with different axes. (see code below)
sipcolor = 'tab:red' fig,ax1 = plt.subplots() ax1.plot(data['SIP'],color=sipcolor) ax1.set_ylabel('SIPEF',color=sipcolor) #Instantiate a second axes that shares the same x-axis ax2 = ax1.twinx() ax2.plot(data['PPOIL']) ax2.set_ylabel('PALM OIL USD') plt.gcf().set_size_inches(15,8) plt.show()
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