andrewkittredge/financial_fundamentals

Find XBRL filings on the SEC's Edgar and extract accounting metrics.

financial_fundamentals

Find XBRL filings on the SEC's edgar and extract accounting metrics. See the blog @ http://andrewonfinance.blogspot.com/. Caching is provided by my vector_cache package, https://github.com/andrewkittredge/vector_cache.

import pandas as pd
import financial_fundamentals as ff

date_range = pd.date_range('2012-1-1', '2013-12-31')
required_data = pd.DataFrame(columns=['MSFT', 'GOOG', 'YHOO', 'IBM'], index=date_range)

eps = ff.accounting_metrics.earnings_per_share(required_data)
print eps

Follow up:

I (Andrew) am working for Calcbench the leading commercial XBRL shop. I have written an API client for Calcbench that achieves the goals of financial_fundamentals, check it out at https://github.com/calcbench/python_api_client.

The SEC's XBRL database is a wonderful, huge, source of fundamentals data; but making sense of it and correcting the errors is a massive project. Calcbench is further towards XBRL mastery than anybody else, if you have legitimate need for the data in XBRL I would encourage you to consider Calcbench before embarking on a parsing adventure of your own.

financial_fundamentals's Issues

fundamentals inserted twice.

2009-11-18 00:00:00|2010-02-17 00:00:00|CSCO|quarterly_eps|0.37
2009-11-18 00:00:00|2010-02-17 00:00:00|CSCO|quarterly_eps|0.37

Calling sqlite driver with default args causing too many variables error on windows machine.

Calling sqlite driver with default args causing too many variables error.

Out of the box AttributeError

eps = ff.accounting_metrics.earnings_per_share(required_data)

AttributeError: 'module' object has no attribute 'accounting_metrics'

Should i see that when i just launched it w/o touch code?
I've loaded the modules from another point and it worked.... idk what is wrong with those paths.

import pandas as pd
from financial_fundamentals import accounting_metrics as am #this one

date_range = pd.date_range('2016-1-1', '2016-12-31')
required_data = pd.DataFrame(columns=['MSFT', 'GOOG', 'YHOO', 'IBM'], index=date_range)

eps = am.earnings_per_share(required_data)
print eps

how to use vector-cache module

could not run/compile as could not found module 'vector_cache' that is being used.would you please suggest how to use it.

Thanks in advance

sqlite cache first get returns all values between dates rather that dates requested.