Stock Market Data – How to Scrape It?

Web scraping has become such an important job nowadays that if you don't use it, you are already behind almost everyone in the market. Like web scraping, data scraping is an essential thing; however, many people don't know where to start or what tool to use. Even though there are tools present everywhere for beginners, they won't give you the flexibility and results you want. So, the best option is always Python. People use Yahoo Finance for the website for data scraping or for specifically scrape stock market data.

Data scraping is carried out for obtaining the data from multiple sites on the internet. Data scrapers extract this information through algorithms or scripts set to extract such info at a large scale. This data is worth a lot and can be used in data analysis, which why companies a lot to data scrapers to do their work professionally.

But how exactly can you do it? And what tools you need to extract it? We will discuss those questions in this article and provide you with the answers.

Stock Market Data Scraping

The data procedure involves specific steps, including downloading target data, its extraction, and storing it. The final steps include finalizing and analyzing the data, which is done in CSV format or on an excel spreadsheet. The procedure to scrape stock market data is very much similar to other types of data scraping.

The first step is downloading the stock data from the target site or database where the data is kept. Then you use the data scraper tool or Python to scrape the data from the raw unstructured form and make it a structured format. After that, you need to store the data, mostly in CSV format or on an excel spreadsheet, as we said above. Lastly, you need to analyze the data you have scraped, which reveals the stock market's current condition and sometimes specific stocks. This data is crucial for business people who want to invest or know about the condition to strategize and make decisions, which grants their business a higher rank. Hence, the better the data is the more its worth.

The Best Tool for Data Scraping

The most used tool by many data scrapers is Python because it offers flexibility and can do any task you may want during this process. Its efficiency also depends on the user, but if used correctly, it can work so well. Not only that, but people also use Python for data mining, cybersecurity, and even penetration testing. But you may ask, is it as useful to scrape stock market data as it is in data scraping? Well, stock market data is taken like any other data and can be scraped similarly, so Python's efficiency does not depend on those things.

It’s also open-source software and can be used for free, which makes it excellent for every programmer or a data scraper. However, it does require you to have some knowledge before you use it because its language can differ from others. If you are a beginner in data scraping and don't know how to use Python, we recommend asking other data scrapers and their experience with different tools. There are many current online, but each can offer different services, so the answer depends on your needs. But the point is that you can use any other tool if you don't know how to use Python.

Stock Data Scraping with Python

The first step of scraping stock market data with Python is to specify the URL of the site you want to scrape the data from the execution code. This URL sends the requested info in the form of an HTML or XML page so that you can gather the information from there. The scraper detects the required data displayed on the URL and then identifies it for scraping before running the code for execution. This data can then be stored in any desired format.

The process of stock data scraping on Python is simple and easy if you know how to use it, but due to the complexity of using the tool itself, people avoid it initially. However, as you slowly progress as a data scraper, you realize how vital Python is for this job, and you need it.

Stock Market Data Scraping from Yahoo Finance

Yahoo finance is the most widely used site to scrape stock market data, and the steps to scrape the data are following.

• First, you need to construct the URL of the Yahoo Finance search page; the example of one for Apple is "http://finance.yahoo.com/quote/AAPL?p=AAPL."
• Use Python to download the HTML of the search result page.
• The third step is to parse the page with LXML – LXML, which allows you to navigate the HTML structure by Xpaths. The Xpaths is predefined for the details in the code.
• Lastly, you can save the data in a JSON file.

To complete this procedure, you will need to download other things for Python, also known as packages. These packages include PIP, Python Requests, and Python LXML.

PIP is for installing the packages, while Python Requests is for making the requests and downloading the HTML content from pages. Python LXML is for parsing the HTML tree structure with the help of Xpaths. 

Be Cautious

Although all the above steps are right and can do your job correctly, there are some known limitations that you should avoid. You can of almost all the companies. But, if you want to scrape thousands of pages with multiple per hour, then you should know how to do such things without getting blacklisted or banned. You need to be cautious and perform things anonymously because most sites don't like data scraping on their site.

Role of Proxies in Scraping Data

A dedicated proxy is a third party host which lets you track your request through their servers and utilize their IP address at the procedure. When using a proxy, then the site you're making the request to no more visits your IP address but also the IP address of the proxy, providing you the capacity to scrape the net with higher security. There are plenty of providers available on the internet. But ProxyAqua is the best among them with respect to their prices and services.

Conclusion

Stock market data scraping is an integral part of gathering information desired by many businesses. The pure and relevant your information is, the more they will want it. The procedure for gathering this information is also lengthy and requires professional hands. It would be best if you had experience in Python and Yahoo Finance to scrape stock market data better.