Jyoti Nigania

Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree. ...

Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree.

RPA is Meant to Automate the Routine Task
yesterday

How AI is going to change the lives of Visually Challenged People?
yesterday

How Organizations can get Best Out of Data Scientists?
yesterday

Understanding the Present Scenario and Future Outlook of Artificial Intelligence
2 days ago

Understanding the Past or History of AI
4 days ago

Scope of AI and Machine learning in India
26679 views

Skills Required To Become Data Scientists
14028 views

How to Learn Mathematics for Machine Learning?
12096 views

Difference between Artificial Intelligence, Machine Learning and Deep Learning
10140 views

Differentiating between Data Science, Big Data and Data Analytics
8769 views

Understanding the Concept of Web Scraping or Data Extraction

Jul 9, 2018 | 1443 Views

What is Web Scraping?
Web scraping is also known as web harvesting or data extraction. It is used for extracting data from the website. Web scraping a web page included fetching and extracting.  Fetching is something what we are downloading. So we can say that web crawling is a most important component of web scraping, to fetch pages for later processing. Once fetched, then the extraction takes place. It is also used for contact scrapping, and as a component of applications used for web indexing, web mining, and data mining.
Data can be extracted from the web source using a numerous methods, popular websites like Google, Facebook, and Twitter to extract the available data in a structured manner. This prevents the use of other methods that may not be preferred by the API provider. 

Basic steps involved in Web Scraping:
  • Document Load: Here we have to load the entire document which is a HTML page.
  • Parsing: Here we interpret the document to make the searching possible. 
  • Extraction: Here we can extract anything like the name, price or any specifications of the product.
  • Transformation: It converts the data into useful formats. 

Need of Web Scraping:
So scraping is basically extracting data from various websites. There are various ways to collect data online but for example if want data for comparison we have taken mysmartprice, which is known for best price comparison.  What they do, they directly collect data from merchants. We need to fetch some information from the website. To do so, copy and paste the data displayed by the website which is a very tedious job that make many hours or sometime days to complete. Apart from these there are many use cases and examples where people do scraping so for example we can take E-Commerce portals, here we can build our own website and then scraping product from the retailer or from the manufacturing units. So basically here you can scrap pricing, ratings, images or any other specifications as well. After that market research will come, here scraping help you in providing important information's to identify and to analyze the market and needs and analyze the completion of the market as well. It can be any kind of industry whether travel industry where we can scarp the reviews, products or nay places, hotels, restaurants or it can be anything. Lastly we have social websites here people scrap business profiles from social networks and track their online presence and reputations and hence the list goes on. 

So people generally use web scraping to build the best marketing strategies, monitor them and hence upgrade them. So, web scraping is the only alternative to get data out of them. 
Web scraping is legal, yes may be like scraping is fine till you are not causing any considerable damage to the target website. Web scraping is a technique employed to extract large amount of data from websites whereby the data is extracted and saver to a local file in your computer or to a database. 

Different Libraries used for Web Scraping:
1. Pattern
2. Scrapy
3. Mechanize
4. Beautiful Soup
5. Requests

Hence, in the Big Data world, Web Scraping or Data Extraction services are the main requisites for Big Data Analytics. Extracting data from the web has become very necessary for companies to survive in business. To carry out web scraping using Python, the very first step is to install the Python Environment, which enables to run code written in the python language. It understands the website and how the things are laid out and Python we are using because it is ridiculous fast as well as easy to this kind of web-scraping.

Source: HOB
Jyoti Nigania

Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree. ...

Full Bio 

Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree.

RPA is Meant to Automate the Routine Task
yesterday

How AI is going to change the lives of Visually Challenged People?
yesterday

How Organizations can get Best Out of Data Scientists?
yesterday

Understanding the Present Scenario and Future Outlook of Artificial Intelligence
2 days ago

Understanding the Past or History of AI
4 days ago

Scope of AI and Machine learning in India
26679 views

Skills Required To Become Data Scientists
14028 views

How to Learn Mathematics for Machine Learning?
12096 views

Difference between Artificial Intelligence, Machine Learning and Deep Learning
10140 views

Differentiating between Data Science, Big Data and Data Analytics
8769 views