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Mastering Python for Finance - Second Edition
book

Mastering Python for Finance - Second Edition

by James Ma Weiming
April 2019
Intermediate to advanced
426 pages
11h 13m
English
Packt Publishing
Content preview from Mastering Python for Finance - Second Edition

Retrieving datasets from Quandl

Fetching data from Quandl into Python is fairly straightforward. Suppose we are interested in ABN Amro Group from the Euronext Stock Exchange. The ticker symbol in Quandl is EURONEXT/ABN. In a Jupyter notebook cell, run the following command:

In [ ]:    import quandl    # Replace with your own Quandl API key    QUANDL_API_KEY = 'BCzkk3NDWt7H9yjzx-DY'     quandl.ApiConfig.api_key = QUANDL_API_KEY    df = quandl.get('EURONEXT/ABN')
It is a good practice to store your Quandl API key in a constant variable. This way, should your API key change, you only need to update it in one place!

After importing the quandl package, we store our Quandl API key in the constant variable, QUANDL_API_KEY, which will be reused in the rest of this ...

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Publisher Resources

ISBN: 9781789346466Supplemental Content