yahoo_ff

Package to obtain financial fundamental data as well as price history for stocks. Creates database (using pickle) to be quickly used later. Loads/Saves data as Pandas DataFrame.

Requirements

pip install python-dateutil Quandl pandas pickle

Installation

$ pip install yahoo_ff

Using

A single stock

>>> from yahoo_ff.yahoo_ff import yahoo_ff
>>> aapl = yahoo_ff('aapl')

will create an object from which several Pandas DataFrames of interest can be extracted

>>> aapl.incomestatement_annual
>>> aapl.incomestatement_quarterly
>>> aapl.balancesheet_annual
>>> aapl.balancesheet_quarterly
>>> aapl.cashflow_annual
>>> aapl.cashflow_quarterly
>>> aapl.pricehistory
>>> aapl.infos

Note: pricehistory includes Open, High, Low, Close, Volume, Ex-Divident, Split Ratio, Adj.Open, Adj.High, Adj.Low, Ajd.Close, Adj.Volume.

To simplify a bit further,

>>> aapl.package_sec_annually()

will return all annual data from the three SEC filings (incomestatement, balancesheet, cashflow) in one single DataFrame.

Create a database for a list of stocks

You can use it later quickly, or get it updated. If you have a list of stocks such as a file dbtest .csv

>>> from yahoo_ff.stocks_database import stocks_database
>>> dbtest = stocks_database('dbtest')

will create a folder named dbtest_db in the root directory with all the data stored as a pickle file. The object dbtest will now be available for you to access stocks stored in the database using the take('aapl') function as follows:

>>> dbtest.take('aapl').pricehistory

and all other data as described in section above. Note: take('aapl') returns None if stock does not exist in the database object.

Next updates:

• Create an automatic updating flow of a database.