Data Scrapping
Data Scrapping / Web Scrapping involves automatically extracting information from various sources, such as websites, databases, documents, and more.
Identify the Data Source
Determine where the data you need is located. This could be a website, a database, a document, or any other structured or unstructured data repository.
Fetch the Data
Use a tool or script to access the data source. For web scraping, this often involves sending HTTP requests to the website’s server to retrieve the HTML content of web pages.
Parse the Data
Once the data is fetched, it needs to be parsed to extract the relevant information. In Python to navigate and extract data from HTML or XML documents.
Store the Data
After extracting the necessary information, store it in a structured format, such as a CSV file, a database, or a spreadsheet, for further analysis or use.
Automate the Process
To make data scraping efficient, automate the process using scripts or tools that can run at scheduled intervals or in response to specific triggers.