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A Full Guide on Scraping Yahoo Finance

Thursday, September 29, 2022

In the world of business, the financial health of a company is crucial. This information is provided to the public through various platforms and forums. Yahoo Finance is one of the most popularly used web media to view and extract financial details of companies around the world. In this article, we'll introduce the best Yahoo Finance scraper to scrape Yahoo Finance easily and quickly.

 

 

Does Yahoo Finance Allow Scraping

In short, yes. Most of the data available on the Yahoo Finance website is open-source and public information. This information consists of the following main parts.

  • News updates on stock markets
  • Current Stock prices of companies
  • The trend of rising or falling of a company's stock prices.
  • Mutual Funds and ETFs
  • Value of currencies and even cryptocurrencies

 

Scraping the above information can be of paramount usage to businesses. In the business market, analyzing this data can produce information required to improve business strategies.

 

How to Scrape Yahoo Finance Data Without Coding

There are multiple ways that you can scrape Yahoo Finance. Some of them require no coding knowledge. Tools and software are available online for web scraping. Here we'll introduce Octoparse, which is a user-friendly web crawler tool. It is one of the most widely-used, open-source software and is free. It extracts bulk data from multiple websites, and supports up to 10,000 links in one go.

 

Octoparse can auto-detect data from Yahoo Finance site, it also has preset templates for you to scrape data within only a few clicks. It allows you to export the extracted data in multiple formats, including Excel, CVS, and database. You can use the scheduled scraping for your tasks hourly, daily, or weekly.

 

Steps to scrape data from Yahoo Finance

You can follow the steps below to scrape data from Yahoo Finance after you have downloaded and installed Octoparse. Or, you can watch the video guide here.

 

 

Step 1: Enter the URL copied from Yahoo Finance

Open the Yahoo Finance page you need to scrape data, and copy the page link. Enter the URL into Octoparse search bar, and click on the Search button. It will start auto-detecting.

 

Step 2: Make changes on your workflow

Waiting for the auto-detecting process, and create a workflow after it finished. You can see the extracted data in the preview section, and Octoparse lets you change the data fields you want to extract.

 

Step 3: Run the workflow to extract Yahoo Finance data

After all the changes have been saved, click on the Run button to scrape data. You can download the results to your local devices or save them to a database.

 

If you still have any question about the details, you can move to Scrape cryptocurrencies information from Yahoo Finance tutorial to read more.

 

Scrape Yahoo Finance Data Using Python

To web scrape Yahoo Finance using python we can make use of multiple python modules and methods available open-source. One of the simplest and beginner-friendly methods to scrape financial data is to use the BeautifulSoup library. Let us look at this method step by step.

 

Step 1: Install the dependencies on the device you are using.

  • pip install bs4
  • pip install requests
  • pip install pandas

 

Step 2: Import the modules

#import modules

import requests

from bs4 import BeautifulSoup

import pandas as pd

 

Step 3: Get the webpage URL and check for errors.

#get the URL using response variable

my_url = "https://finance.yahoo.com/news"

response = requests.get(my_url)

#Catching Exceptions

print("response.ok : {} , response.status_code : {}".format(response.ok , response.status_code))

print("Preview of response.text : ", response.text[:500])

 

Step 4: Create a function to retrieve HTML data of the webpage as a Beautiful Soup object.

#utility function to download a webpage and return a beautiful soup doc

def get_page(url):

response = requests.get(url)

if not response.ok:

print('Status code:', response.status_code)

raise Exception('Failed to load page {}'.format(url))

page_content = response.text

doc = BeautifulSoup(page_content, 'html.parser')

return doc

#function call

doc = get_page(my_url)

 

Step 5: Extract and store the information.

#appropritae tags common to news-headlines to filter out the necessary information.

a_tags = doc.find_all('a', {'class': "js-content-viewer"})

print(len(a_tags))

#print(a_tags[1])

news_list = []

#print top 10 Headlines

for i in range(1,len(a_tags)+1):

news = a_tags[i-1].text

news_list.append(news)

print("Headline "+str(i)+ ":" + news)

news_df = pd.DataFrame(news_list)

news_df.to_csv('Market_News')

 

Scraping financial information has given you a competitive edge over the business world. Now, you have learned the basics of scraping Yahoo Finance, try extracting data from multiple sources and compiling them into a useful set of information. Apply the inferences from this information in different forms and how the extracted data can be put to maximum use. I hope this article inspires you to dive into the world of financial web scraping. Best wishes for your future coding endeavors.

 

Related Resources

How to Extract and Monitor Stock Prices from Yahoo Finance

3 Ways to Scrape Financial Data WITHOUT Python

Stock Market Analysis using Web Scraping

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