Get historical fundamental data time series in Pandas Dataframes from SEC Edgar for any company. I couldn't find this anywhere in an easy to use way. Other options were very complicated and didn't work well across companies.
Requirements:
beautifulsoup4
pandas
Usage:
Ask for historical data for a particular ticker and financial statement item, and it will return a Pandas DataFrame with all the series it was able to pull for that item. 'root' will always be the entity as a whole, but you might get back multiple series if the company has divisions geographically, or different business segments.
example:
from xbrl_parse import Company
data = Company('MSFT')
print data.get_series_from_id('Assets')['root']
2009-06-30 77888000000
2009-09-30 81612000000
2009-12-31 82096000000
2010-03-31 84910000000
2010-06-30 86113000000
2010-09-30 91540000000
2010-12-31 92306000000
2011-03-31 99727000000
2011-06-30 108704000000
2011-09-30 107415000000
2011-12-31 112243000000
2012-03-31 118010000000
2012-06-30 121271000000
2012-09-30 121876000000
2012-12-31 128683000000
2013-03-31 134105000000
2013-06-30 142431000000
2013-09-30 142348000000