I am looking for a Python code that scraps a website to download historical firm data such as market capitalization, dividend-yield, and so on. I have a code that downloads the current firm data from Yahoo but I am looking for historical data. Any suggestions?
You don't have to scrape that data to get it via Python if you work with Intrinio's API. Here is a Python SDKs that will make it easy for you:
Historical financial statements and dividend yield, marketcap, etc: https://github.com/nhedlund/intrinio
Specifically, you can make a curl request for historical marketcap like this:
curl "https://api.intrinio.com/historical_data?identifier=AAPL&item=marketcap&start_date=2014-01-01&end_date=2015-01-01" -u "USERNAME:PASSWORD"
That would give you the marketcap for Apple over the specified dates. You can just swap out the marketcap tag for dividendyield and get the data you want. Here is a full tutorial:
You can get stock price data using the following packages. Generally, scraping is not legal and using the API is the best and faster way to get the data.
I have shown below three ways to get the stock price data:
- Yahoo finance
import matplotlib.pyplot as plt import fix_yahoo_finance as yf data = yf.download('AAPL','2016-01-01','2019-08-01') data.Close.plot() plt.show()
import matplotlib.pyplot as plt import quandl data = quandl.get("WIKI/KO", start_date="2016-01-01", end_date="2018-01-01", api_key=<Your_API_Key>) data.Close.plot() plt.show()
Note: To get your API key, sign up for a free Quandl account. Then, you can find your API key on Quandl account settings page.
If you are looking to get minute level data or fundamental data such as earnings or cash flow statement then this page should be helpful.