Scraping Financial Data from Web: How to Extract Yahoo Finance Page using Python
Introduction
Financial data was always one of the most valuable data in the market. If you make a proper analysis, you will have a 100% chance to solve your organization’s financial issues and grow your business. Today, Yahoo Finance is one of the most popular financial web sources with free access. Through this article, we’ll build a web crawler for scraping real-time stock data and other most active Yahoo Finance data like world indices, currencies, and cryptocurrencies. Let’s reveal what Yahoo Finance is, why to scrape financial data, and how to download data from Yahoo Finance with Python.
What is Yahoo Finance
Yahoo Finance provides various financial data like currency trends, financial reports, finance stock quotes, general news from the financial market, etc. Whether you are a business owner or investor, you’ll always get interesting and valuable insights from the Yahoo Finance page or Yahoo Finance app.
Reasons to Scrape Yahoo Finance
If you are working in finance or just interested in trading and investments, scraping Yahoo Finance page is a must. Financial data collected in real-time will enable you to have a wealth of information to make an up-to-date investment or financial analysis. Scraping data from Yahoo Finance is especially needed for stock trading organizations that can download historical stock data from Yahoo Finance into Excel and make stock market predictions based on the fetched information.
To sum up the above, we can state that by scraping financial data you can make:
- Financial market research
- Stock market prediction
- Sentiment analysis of the market
Using Python for Scraping Yahoo Finance
Before building a crawler, you need to import the following libraries: Pandas and Beautiful Soup. Pandas library is used to arrange the extracted data as tables, while the Beautiful Soup enables crawling in Python.
Cryptocurrencies
A digital currency known as cryptocurrency is a localized system founded on blockchain tech with advanced protection. It is a global phenomenon with considerable growth in recent years, attracting many investors.
Let’s build a code to extract data about cryptocurrencies. We need to input the URL for the cryptocurrencies page into the code that will iterate through all the pages containing data about the cryptocurrencies and extract the required information. For that, it is necessary to define the related HTML tags and put them in the code.
And here is the result in the table format.
Currencies
The approach to scraping the currency data is the same as in the above case. You can scrape Yahoo Finance web source for currencies; you just have to identify the tags with the needed information.
As there are no certain attributes in the HTML code of the Yahoo Finance page, we retrieved the data using a data ID.
And here is the result of scraping currencies data from Yahoo Finance
World Indices
MSCI World is a market cap-weighted indexes of 1,649 stocks from around the world. The index and its dynamics show the attitude of investing in companies of any size and field.
The below code will enable scraping world indices’ data like prices, changes in percentage, and market volume.
Most Active Stocks
The shares on the exchange with the highest volume for a certain period are the most active. Because of the value of the latest information affecting the entry of stocks into the market, stock trading volumes grow above average, which induces investors to sell or buy shares at high returns.
The code for scraping most active stocks is coming below.
And here is the most active stock data gathered after scraping Yahoo Finance.
How to Scrape Yahoo Finance without Python
If you have no coding skills, there are other options as well.
- Buy a scraping tool
- Hire a web scraping developer
- Outsource to data scraping service providers.
Except for Yahoo Finance, there are other financial data sources providing valuable insights like Bloomberg, TMXMoney, Google Finance, and much more. Anyway, keep in mind that scraping financial data has its challenges and issues and, of course, should be done in the maximum accurate way. So if you are not sure that you can handle it yourself, trust it to professionals.
Conclusion
Extracting and analyzing data from financial sources can help organizations make financial market sentiment analysis and do equity research. Anyway, the financial market is full of instability and risks. Financial data scraping can be the ideal solution to have all necessary data on hand. At DataOx we are always ready to help you with scraping financial data. Schedule a free consultation with our expert to reveal the complete list of our web scraping services and learn how DataOx can help you scrape financial data in accordance with your business goals.
Originally published at https://data-ox.com on June 9, 2021.
