Welcome to financialdatapy’s documentation!¶
financialdatapy is a package for getting a fundamental financial data of a company. Currently it supports financial data of companies listed in United States (NASDAQ, NYSE) and South Korea (KOSPI, KOSDAQ).
User can see the company’s latest financial statement reported, standard financials, and historical stock price. financialdatapy will be a good choice for research purposes, and managing an investment portfolio.
Installation¶
To use financialdatapy, first install it using pip:
Note
Python version above 3.10 is required to use financialdatapy.
pip install financialdatapy
Quick Start¶
financialdatapy supports three major financial statements of a company. Income statement, balance sheet, and cash flow. Also the user can select between annual and quarter financial statements.
Checkout the usage in Usage page, and notebook
API Key¶
❗️When getting financial statements of a company listed in Korea stock exchange, API Key from DART should be provided in the system to successfully retrieve its data.
After receiving API key, store it on a .env file in the root directory of your project.
Inside .env file, provide api key as shown below.
DART_API_KEY=xxxxxxxxxxxxxxxx
Initialization¶
from financialdatapy.stock import Stock
# Apple
us_comp = Stock('aapl')
# Samsung Electronics
kor_comp = Stock('005930', country_code='kor') # should specify 'country_code' for stock exchange other than USA
Values passed for financial statements and periods should follow the format below. If no argument is passed, it automatically retrieves income statement from annual report.
income_statement = us_comp.financials('income_statement')
balance_sheet = us_comp.financials('balance_sheet')
cash_flow = us_comp.financials('cash_flow')
# Annual Report
income_statement = kor_comp.financials('income_statement', 'annual')
# Quarterly Report
income_statement = kor_comp.financials('income_statement', 'quarter')
Financial Statement as reported¶
Financial statements reported by the company to a financial regulator.
The elements in the financial statements are different from others, depending on the comapany and stock exchange.
United States Stock Exchange
us_comp = Stock('aapl')
ic_as_reported = us_comp.financials('income_statement', 'annual')
Korea Stock Exchange
kor_comp = Stock('005930', country_code='kor') # should specify 'country_code' for stock exchange other than USA
ic_as_reported = kor_comp.financials('income_statement', 'annual')
To see the full financial report from a browser, pass True in web. Supports both US exchange and KOR exchange.
us_comp.financials(web=True)
kor_comp.financials(web=True)
Standard Financial Statement¶
Summarized financial statements of a company.
us_comp = Stock('aapl')
std_ic = us_comp.financials('income_statement', 'annual', is_standard=True)
Historical Stock Data¶
Historical stock price of the company.
us_comp = Stock('aapl')
price = us_comp.price('2021-1-1', '2021-1-5')
All of the above will return in pandas.DataFrame.
Note
Data source of stock price data differ from US stock exchange to KOR stock exchange.
Exchange |
Source |
|---|---|
USA |
|
KOR |
Contribute¶
It will be a great help if you contribute to the package. You can open issues here!
Code style¶
The project basically follows PEP-8, Google Python Style Guide.
Git commit messages¶
The project basically follows Conventional Commits. Click on the badge to see the details.
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Documentation¶
The documentation is built with Sphinx and deployed with Read the Docs.
License¶
Licensed under the MIT License
Disclaimer¶
financialdatapy is not meant to be used in any kind of trading. The data might not be accurate, and timely.
financialdatapy is aimed for people who use stock data in their portfolio management and researchers who need stock
market data in their research. So if you are willing to use data for trading, there are lot more better options.