Yahoo Finance API for Python

In this article we want to talk about Yahoo Finance API for Python, Yahoo Finance is popular platform that provides financial data and news to investors and traders. it offers different financial tools and information that can be accessed through its APIs. in this article we want to explore how to use the Yahoo Finance API for Python to retrieve financial data.

Yahoo Finance API for Python

First of all we need to install yahoo finance

pip install yfinance

1	pip install yfinance

You can use the API to retrieve historical stock data for a particular company. this is an example of how to retrieve the data for Apple Inc. (AAPL).

import yfinance as yf

aapl = yf.Ticker("AAPL")

# get historical market data
data = aapl.history(period="max")

import yfinance as yf

aapl = yf.Ticker("AAPL")

# get historical market data

data = aapl.history(period="max")

This will retrieve the historical stock data for Apple Inc. from its inception to the present day.

You can also use the API to retrieve live stock data for a particular company. this is an example of how to retrieve the data for Apple Inc, this code will retrieve the live stock data for Apple Inc, including the current price, volume and other information.

import yfinance as yf

aapl = yf.Ticker("AAPL")

# get live market data
data = aapl.info

import yfinance as yf

aapl = yf.Ticker("AAPL")

# get live market data

data = aapl.info

You can use the API to retrieve financial statements for a particular company. this is an example of how to retrieve the income statement for Apple Inc.

import yfinance as yf

aapl = yf.Ticker("AAPL")

# get income statement
income_statement = aapl.financials

import yfinance as yf

aapl = yf.Ticker("AAPL")

# get income statement

income_statement = aapl.financials

This is practical example code that retrieves the historical stock data for Apple Inc. (AAPL) using the Yahoo Finance API for Python:

import yfinance as yf

# Define  ticker symbol
tickerSymbol = 'AAPL'

# Get  data for the stock
tickerData = yf.Ticker(tickerSymbol)

# Get the historical prices for this stock
tickerDf = tickerData.history(period='1d', start='2010-1-1', end='2023-3-31')

# Print the data
print(tickerDf)

import yfinance as yf

# Define ticker symbol

tickerSymbol = 'AAPL'

# Get data for the stock

tickerData = yf.Ticker(tickerSymbol)

# Get the historical prices for this stock

tickerDf = tickerData.history(period='1d', start='2010-1-1', end='2023-3-31')

# Print the data

print(tickerDf)

This code imports yfinance package, after we have defined the ticker symbol for the stock (in this case, AAPL for Apple Inc.), and retrieves the historical prices for the stock from January 1, 2010 to March 31, 2023. resulting data will be printed in the terminal or command prompt, and will include information such as the opening and closing prices, high and low prices, volume and many more.

You can modify the code to retrieve different types of financial data such as live stock data or financial statements by using different functions from the yfinance package. but this example should give you a good starting point for using the Yahoo Finance API for Python.

Run the code and this will be the result

Also you can use Matplotlib to visualize the data

import yfinance as yf
import matplotlib.pyplot as plt

# Define  ticker symbol
tickerSymbol = 'AAPL'

# Get  data for the stock
tickerData = yf.Ticker(tickerSymbol)

# Get  historical prices for this stock
tickerDf = tickerData.history(period='1d', start='2010-1-1', end='2023-3-31')

# Calculate  moving average of the closing price
movingAvg = tickerDf['Close'].rolling(window=50).mean()

# Plot the closing prices and moving average
plt.plot(tickerDf['Close'], label='Closing Price')
plt.plot(movingAvg, label='Moving Average')
plt.title('Historical Stock Prices for ' + tickerSymbol)
plt.xlabel('Date')
plt.ylabel('Price')
plt.legend()
plt.show()

import yfinance as yf

import matplotlib.pyplot as plt

# Define ticker symbol

tickerSymbol = 'AAPL'

# Get data for the stock

tickerData = yf.Ticker(tickerSymbol)

# Get historical prices for this stock

tickerDf = tickerData.history(period='1d', start='2010-1-1', end='2023-3-31')

# Calculate moving average of the closing price

movingAvg = tickerDf['Close'].rolling(window=50).mean()

# Plot the closing prices and moving average

plt.plot(tickerDf['Close'], label='Closing Price')

plt.plot(movingAvg, label='Moving Average')

plt.title('Historical Stock Prices for ' + tickerSymbol)

plt.xlabel('Date')

plt.ylabel('Price')

plt.legend()

plt.show()

This code first calculates moving average of the closing price of AAPL using window size of 50, and then plots both the closing prices and the moving average on the same graph using the plt.plot() function.

Run the code and this will be the result