Web Scraping, Data Mining

Beginner’s Guide for Web Scraping   Suppose we have a website that has tons of useful data e.g.: Millions of email address or Names of Hospitals in the whole state, which needs to be downloaded, manually it would be very difficult to extract them into the computer for further process, Here comes web scraping. Web scraping makes it easier to extract data or information from websites or web pages into a personal computer in much lesser time without doing much manual work. It is done by writing code of programs that will reach the website, parse the HTML of the pages, and extract the data predefined tags of HTML. Programming languages varies but the most recommended programming language for web scraping is Python due to its processing speed, simplified syntax, mature python community and overwhelming adoption by all corporate sectors. Let’s understand by a scenario: Suppose you have a website that contains 30 thousand schools in USA, UK or say New York, and you need the names and contact numbers of these schools. Would you open 30K links and copy-paste the names and contact numbers manually? NO. So, the developer writes python code and executes it. The code will send HTTPS requests to the website and get the response back from the website in HTML. It parses this HTML, searches for names and contact numbers of schools in that HTML effectively and stores them in excel or JSON on the local computer. And this all takes much less time than doing it manually. Why Python: Easy to learn for beginners with simple syntax yet powerful programming language with collections of more than 100 thousand libraries with huge community support. Python is also known for lesser numbers of lines for large tasks as compared to other programming languages like Java or C#. What you should know before learning Web Scraping: Basic Programming in Python: Loops, if-else, try-except, list, dictionary, sets, Data Frame, typecasting etc. Built in functions like Len, type, range, break, pass, etc. Boolean operators: ‘or’, ‘and’, ‘not’. HTML: HTML (Hypertext Markup Language) is used for creating the structure of web pages and formatting its content. It is standard for creating web pages as almost all the websites on the internet have html for their structuring. It consists of elements represented by html tags, these tags contain content like text, links, images enclosed between them or sometimes enclosed in them. Applications of web scraping:  Extract Data Images Contacts Customized Data E-commerce Products Scraping Comparison of Products and/or Prices Events Betting Statistics Scraping How data is delivered: The scraped data or content can be delivered in various forms. MS Excel (.xlsx) or (.csv) files are most commonly deliverables. Although JSON, SQL Database could also be good options for data storage. Main Libraries for Beginners:  Pandas  BS4 or Beautiful Soup Requests Selenium Extras: Basics of Servers: Servers in web scraping are used to execute time taking scraping scripts that need more computational power. Linux Commands: Proficiency in basic Linux commands is necessary for effectively utilizing Linux servers for web scraping tasks. Converting (.py) to (.exe):pyinstaller is used to convert script.py into script.exe file. Future: Web scraping could be helpful in future for data analysis, market analysis and sentiment analysis to drive the results and make data oriented decisions. Further web scraping can be extended as data mining, data preparation, Data Visualization etc. If you have any question or curious to learn and don’t know where to start from or if you have a task you want done, don’t hesitate to reach Scraping Solution by email or WhatsApp live chat follow us on Facebook Linkedin Instagram

Is web scraping legal?   There has been a great talk about the legality of the scraping information from internet in past decade since the boom of IT specially the automation. Companies in marketing and other business sectors were hunting the data from all available sources but there question was always there that is scraping legal at all? This discussion was not only among the netizens but many courts in UK, Europe and USA discussed the legality of this for many years and different rulings has been passed depending upon the nature of data but none have banned them in any country. This kind of data is mostly advertised on business directories, maps or public or government databases by the companies themselves to get digital exposure. This data is legal to scrape all around the work and laws allow you to get and use this data for marketing or business purposes. Private/Personal data According to GDPR the definition of personal data is as follows “Personal data means any information relating to an identified or identifiable natural person”. Although this data is not publically available on any directories but sometimes this data comes online stolen or sold by different apps or websites. Recently, due to increasing trend of using social media, sometimes users publish their information on the websites like Facebook, Instagram or LinkedIn as well and can be easily scraped from there sources at small level. But scraping this data is not legal in most of the world, except California where you can scrape this information if published by the user itself on his/her profile from 2023. Therefore for time being is a good practice to deal with personal data and lets just focus on business-to-business data which in itself is a big field and still has unknown dimensions to explore. Ethics of Scraping Even if you are dealing with public records which is totally legit to scrape Scraping solution still uses some ethics in its process of web scraping to keep things transparent and ethical and if you are dealing with scraping you should consider these as well follow us on Facebook Linkedin Instagram