The article “Stock Market Data: Obtaining Data, Visualization & Analysis in Python” first appeared on QuantInsti blog.
Are you looking to get stock market data and analyse the historical data in Python? You have come to right place.
After reading this, you will be able to:
- Get historical data for stocks
- Plot the stock market data and analyse the performance
- Get the fundamental, futures and options data
Yahoo Finance
One of the first sources from which you can get historical daily price-volume stock market data is Yahoo finance. You can use pandas_datareader
or yfinance
module to get the data and then can download or store in a csv file by using pandas.to_csv method.
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 package import yfinance as yf # Set the start and end date start_date = '1990-01-01' end_date = '2021-07-12' # Set the ticker ticker = 'AMZN' # Get the data data = yf.download(ticker, start_date, end_date) # Print 5 rows data.tail()
amazon_data.py hosted with ❤ by GitHub
To visualize the adjusted close price data, you can use the matplotlib library and plot method as shown below.
# Import matplotlib for plotting import matplotlib.pyplot as plt %matplotlib inline # Plot adjusted close price data data['Adj Close'].plot() plt.show()
plot_amazn_data.py hosted with ❤ by GitHub
Data Source: Yahoo Finance
Let us improve the plot by resizing, giving appropriate labels and adding grid lines for better readability.
# Plot the adjusted close price data['Adj Close'].plot(figsize=(10, 7)) # Define the label for the title of the figure plt.title("Adjusted Close Price of %s" % ticker, fontsize=16) # Define the labels for x-axis and y-axis plt.ylabel('Price', fontsize=14) plt.xlabel('Year', fontsize=14) # Plot the grid lines plt.grid(which="major", color='k', linestyle='-.', linewidth=0.5) # Show the plot plt.show()
plot_amzn_data_with_grids.py hosted with ❤ by GitHub
Data Source: Yahoo Finance
Advantages
- Adjusted close price stock market data is available
- Most recent stock market data is available
- Doesn’t require API key to fetch the stock market data
How to get Stock Market Data for different geographies?
To get stock market data for different geographies, search the ticker symbol on Yahoo finance and use that as the ticker.
Get stock market data for multiple tickers
To get the stock market data of multiple stock tickers, you can create a list of tickers and call the yfinance download method for each stock ticker.
For simplicity, I have created a dataframe data
to store the adjusted close price of the stocks.
# Import packages import yfinance as yf import pandas as pd # Set the start and end date start_date = '1990-01-01' end_date = '2021-07-12' # Define the ticker list tickers_list = ['AAPL', 'IBM', 'MSFT', 'WMT'] # Create placeholder for data data = pd.DataFrame(columns=tickers_list) # Fetch the data for ticker in tickers_list: data[ticker] = yf.download(ticker, start_date, end_date)['Adj Close'] # Print first 5 rows of the data data.head()
multiple_tickers_data.py hosted with ❤ by GitHub
# Plot all the close prices data.plot(figsize=(10, 7)) # Show the legend plt.legend() # Define the label for the title of the figure plt.title("Adjusted Close Price", fontsize=16) # Define the labels for x-axis and y-axis plt.ylabel('Price', fontsize=14) plt.xlabel('Year', fontsize=14) # Plot the grid lines plt.grid(which="major", color='k', linestyle='-.', linewidth=0.5) plt.show()
plot_multiple_tickers_data.py hosted with ❤ by GitHub
Data Source: Yahoo Finance
Visit QuantInsti blog to learn how to retrieve data for S&P 500 stock tickers.
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Great post! I really appreciate these step-by-step tutorials. Thank you!
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Go to the Analyst Rating tab.
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