January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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We already showed how to download the factor-related data directly from prof. French's website. As an alternative, we can use the functionalities of pandas_datareader and avoid some manual preprocessing steps:
- Import the libraries:
from pandas_datareader.famafrench import get_available_datasetsimport pandas_datareader.data as web
- Print the available datasets (only the first five):
get_available_datasets()[:5]
The preceding code results in the following output:
['F-F_Research_Data_Factors', 'F-F_Research_Data_Factors_weekly', 'F-F_Research_Data_Factors_daily', 'F-F_Research_Data_5_Factors_2x3', 'F-F_Research_Data_5_Factors_2x3_daily']
- Download the selected dataset:
ff_dict = web.DataReader('F-F_Research_Data_Factors', ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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