Explanation of Web Scraping: How to collect data using API requests in Data science .
Web scraping refers to the process of automatically extracting data from websites. It involves writing code to access web pages, parse their HTML or XML content, and extract the desired information. Web scraping allows you to gather data from multiple web pages quickly and efficiently, which can be used for various purposes such as data analysis, research, or creating datasets.
Roadmap for Web Scraping:
1. Identify the target website: Determine the website from which you want to scrape data. Ensure that the website allows web scraping and check for any legal or ethical restrictions.
2. Choose a programming language and libraries: Select a programming language such as Python, which provides robust libraries and frameworks for web scraping, such as BeautifulSoup, Scrapy, or Selenium.
3. Understand the website’s structure: Inspect the website’s HTML structure to identify the elements that contain the data you want to scrape. This may include HTML tags, class names, IDs, or CSS selectors.
4. Write the scraping code: Use the chosen programming language and libraries to write code that fetches the web page, parses the HTML content, and extracts the desired data. You may need to handle pagination, form submissions, or other website-specific features.
5. Handle anti-scraping mechanisms: Some websites implement measures to prevent or restrict web scraping, such as CAPTCHAs or rate limiting. Implement strategies to handle such mechanisms, such as using proxies, rotating user agents, or introducing delays between requests.
6. Clean and process the scraped data: Once you have extracted the data, perform any necessary cleaning or preprocessing steps to make it suitable for your analysis or use case. This may involve removing duplicates, converting data types, or handling missing values.
7. Store or analyze the data: Decide whether you want to store the scraped data in a database, save it to a file, or directly analyze it using data analysis
To know this more better and see the implementation as well in Python, You can check out :
In the above code on Kaggle you can see how have I implemented a code for scraping or retreiving data from websites onto Kaggle .and also plotting them . You can drop your reviews , suggestions or if you got any doubts feel free to ask them in comments .
Thank you for reading . !!!
Regards;
Darshan D Prabhu.
Aao Code kare .