Omaha

Omaha aims to provide a unified view of financial metrics of the company.

• Designed to provide comprehensive data set for the financial analysis.
• Combining multiple type of financial data consistently.
• Data is provided in Pandas DataFrame format for the usability.

Please visit the official documentation for more detail. This is also an blog article useful to see how omaha can be used for financial data analysis.

• Omaha: Unified view of financial metrics of public companies

Note

It only supports Japanese company for now.

Dependencies

• Buffett Code
• Quandl

Install

$ pip install omaha

Usage

from omaha import Omaha
factory = Omaha(bc_apikey='XXXXXXX', quandl_apikey='YYYYYYY')

# Financial indicators for the ticker symbol 1376
company = factory.company('1376', '2018Q1', '2019Q4')

# Daily stock prices for the ticker symbol 1376
stockprice = factory.stockprice('1376', '2018-01-01', '2018-12-31')

# Joining multiple indicators

view = company.join(stockprice)
view.df().head()

#                             company_name     ceo_name                  headquarters_address        ...   Low         Close
#2018-11-30 00:00:00+00:00    カネコ種苗株式会社  代表取締役社長　　金子　昌彦   群馬県前橋市古市町一丁目50番地12 ...  1389.568777  1408.187823
#2018-08-31 00:00:00+00:00    カネコ種苗株式会社  代表取締役社長　　金子　昌彦   群馬県前橋市古市町一丁目50番地12 ...  1479.188532  1479.188532

If you are unsure the ticker symbol of the company, search feature is available. You can get the list of companies matching the given keyword.

factory.search("不動産", "2019Q1", "2019Q4")
# [Company(8881, 2019Q1, 2019Q4), Company(8802, 2019Q1, 2019Q4), Company(3465, 2019Q1, 2019Q4),...]

Development

You can develop the package as editable dependencies with Pipenv.

$ pipenv install --dev -e .

To build the package, run make package.

$ make package