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.
Note
It only supports Japanese company for now.
Dependencies
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 1479.188532If 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
