How to Get Stock Price Data with Python pandas



In this article, you will learn how to get stock price data with Python pandas.

Get Stock Price Data with Python pandas

To get stock price data with Python pandas, you can use the pandas-datareader library. This library allows you to download historical stock price data from a variety of sources, including Yahoo Finance, Google Finance, and more.

Here’s a step-by-step guide on how to use pandas-datareader to get stock price data:

Install pandas-datareader library:
!pip install pandas-datareader
Import the necessary libraries:
import pandas_datareader as pdr
import datetime
Define the stock symbol and the date range for which you want to retrieve data:
stock_symbol = 'AAPL'
start_date = datetime.datetime(2020, 1, 1)
end_date = datetime.datetime(2021, 1, 1)
Use the DataReader function from pandas-datareader to download the data:
stock_data = pdr.DataReader(stock_symbol, 'yahoo', start_date, end_date)

In this example, we are using Yahoo Finance as our data source. If you want to use a different source, you can replace ‘yahoo’ with the appropriate data source code.

The stock_data variable now contains a pandas DataFrame with the stock price data for the specified date range:

This will print the first five rows of the DataFrame:

                 High        Low       Open      Close       Volume  Adj Close
2020-01-02  75.150002  73.797501  74.059998  75.087502  135480400.0  73.840042
2020-01-03  75.144997  74.125000  74.287498  74.357498  146322800.0  73.122154
2020-01-06  74.989998  73.187500  73.447502  74.949997  118387200.0  73.704819
2020-01-07  75.224998  74.370003  74.959999  74.597504  108872000.0  73.358185
2020-01-08  76.110001  74.290001  74.290001  75.797501  132079200.0  74.537514