See Part I for instructions on how to get
yfinance module to retrieve the data, and Part II to learn how to get stock market data for different geographies. In Part III and Part IV, review the tutorial on how to analyse the stock market data for all the stocks which make up the S&P 500. Part V explains how to use Quandl to get stock market data.
We have used yfinance to get the fundamental data.
The first step is to set the ticker and then call the appropriate properties to get the right stock market data.
If yfinance is not installed on your computer, then run the below line of code from your Jupyter Notebook to install yfinance.
!pip install yfinance
install yfinance.py hosted with ❤ by GitHub
# Import yfinance import yfinance as yf # Set the ticker as MSFT msft = yf.Ticker("MSFT")
Import yfinance and set the ticker.py hosted with ❤ by GitHub
You can fetch the latest price to book ratio and price to earnings ratio as shown below.
# get price to book pb = msft.info['priceToBook'] pe = msft.info['regularMarketPrice']/msft.info['epsTrailingTwelveMonths'] print('Price to Book Ratio is: %.2f' % pb) print('Price to Earnings Ratio is: %.2f' % pe)
Get price to book.py hosted with ❤ by GitHub
# show revenues revenue = msft.financials.loc['Total Revenue'] plt.bar(revenue.index, revenue.values) plt.ylabel("Total Revenues") plt.show()
Revenue.py hosted with ❤ by GitHub
Earnings Before Interest and Taxes (EBIT)
EBIT = msft.financials.loc['Earnings Before Interest and Taxes'] plt.bar(EBIT.index, EBIT.values) plt.ylabel("EBIT") plt.show()
Balance sheet, cash flows and other information
# show income statement msft.financials # show balance heet msft.balance_sheet # show cashflow msft.cashflow # show other info msft.info
Show information.py hosted with ❤ by GitHub
Stay tuned for next installment in which Ishan Shah will share a tutorial on Stock Market Data Visualization and Analysis.
See https://blog.quantinsti.com/stock-market-data-analysis-python/ for additional insight on this topic.
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