Become Familiar with Web Scraping using Python
The need and importance of extracting data from the web is becoming increasingly loud and clear. There is an unprecedented volume of data on the internet right now - and data science projects often need this data to build predictive models.
That’s a key reason why data scientists are expected to be familiar with web scraping.
We have found web scraping to be a very helpful technique for gathering data from multiple websites. Some websites these days also provide APIs for many different types of data you might want to use, such as Tweets or LinkedIn posts.
But there might be occasions when you need to collect data from a website that does not provide a specific API. This is where having the ability to perform web scraping comes in handy. As a data scientist, you can code a simple Python script and extract the data you’re looking for.
So knowing how to perform web scraping using Python will help you go a long way towards becoming a resourceful data scientist. Are you ready to take the next step and dive in?
A note of caution here – web scraping is subject to a lot of guidelines and rules. Not every website allows the user to scrape content so there are certain legal restrictions at play. Always ensure you read the website’s terms and conditions on web scraping before you attempt to do it.
In this course, we will dive into the basics of web scraping using Python. We will understand what web scraping is, the different Python libraries for performing web scraping, and finally we’ll implement web scraping using Python in a real-world project. There’s a lot to unpack here so enroll today and start learning!
Questions Beginners have about Web Scraping using Python
We’re sure you’ve asked these questions before. Even if you haven’t, you should start learning how these web scraping questions should be answered:
- What is web scraping?
- Why should you learn web scraping?
- Why Python for web scraping?
- What are the different Python libraries for performing web scraping?
- Can I use R for web scraping?
- What kind of projects can I take up after learning web scraping?
- Are web scraping concepts asked in data science/machine learning interviews?
You’ll learn about these concepts inside the course and we have even provided a high-level overview of these questions after the course curriculum below.
Who is the Introduction to Web Scraping using Python Course for?
This course is for anyone who:
- Wants to learn the art of web scraping using Python
- Is looking to collect or gather more data for their data science or machine learning project
- Wants to add a new and crucial skill to their existing data science portfolio
- Is curious about Python programming
What do you need to get started with the Introduction to Web Scraping using Python course?
Here’s what you’ll need:
- A working laptop/desktop with 4 GB RAM
- A working Internet connection
- Basic knowledge of Python. You can take this free Python course if you need a refresher
That’s it! You’re all set to perform web scraping on your machine!
Call to action
This is where you seal the deal. Sprinkle this section throughout your page to push prospects to purchase!
Course curriculum
-
1
Introduction to Web Scraping
- What is Web Scraping?
- Caution
- Popular Libraries for Web Scraping
- Components of Web Scraping
- AI&ML Blackbelt Plus Program (Sponsored)
-
2
Web Scraping: Procedure
- Problem Setup
- Step 1: Crawl
- Step 2: Parse and Transform
- Step 3: Store the Data
-
3
Scraping URLs and Email IDs from a Web Page
- Single Webpage Scraping
- Multiple Webpage Scraping(BeautifulSoup and Regex)
-
4
Scrape Images in Python
- Scrape Images in Python
-
5
Scrape Data on Page Load
- Scarpe Data on Page Load
Instructor(s)
-
Analytics Vidhya
Analytics Vidhya provides a community based knowledge portal for Analytics and Data Science professionals. The aim of the platform is to become a complete portal serving all knowledge and career needs of Data Science Professionals.
Common Questions Beginners Ask about Web Scraping
Here, we break down the common questions beginners often have on web scraping
What is web scraping?
Web scraping is a computer software technique of extracting information from websites. This technique mostly focuses on the transformation of unstructured data (HTML format) on the web into structured data (database or spreadsheet).
You can perform web scraping in various ways, including use of Google Docs to almost every programming language.
Why should you learn web scraping?
Web scraping is incredibly useful when you don’t have enough data with you to train a machine learning model. Web scraping helps us to collect this data from websites (if permitted) and we can then use that to train our model. You can imagine why web scraping is such a prized tool in a data scientist’s arsenal!
Why Python for web scraping?
Python is the most popular tool out there in the world for Web Scraping. Its 2 prominent libraries - BeautifulSoup and Scrapy makes web scraping easy and efficient. Python’s syntax makes understanding of the codes easy. Also python provides many other libraries for web scraping which can be used as per our needs. Eg- lxml, requests etc
What are the different Python libraries for performing web scraping?
There are many libraries in Python that help us to scrape the web. The 3 most prominent libraries include:
- BeautifulSoup
- Scrapy
- Selenium
Can I use R for web scraping?
You sure can! You can perform web scraping in both Python and R. We are teaching you how to do this using Python in the course but feel free to use R if that’s your language of choice. You can go through this tutorial that walks you through how to master web scraping using an R package called rvest.
Are web scraping concepts asked in data science/machine learning interviews?
This depends a lot on the data science role and the organization you’re interviewing for. Not all organizations require you to know or apply web scraping. But here’s why you should learn it anyway - it will help you expand your skillset and also help you work on your personal projects for data science. There’s a lot to learn and nothing to lose!
FAQ
-
Who should take the Introduction to Web Scraping using Python course?
This course is designed for anyone who wants to learn everything about getting started with web scraping using Python. Web scraping is an incredibly useful tool to have in your data scientist’s armoury and this course will get you started on the right footing.
-
I have decent programming experience but no background in machine learning. Is this course right for me?
Absolutely! This course covers a topic that is not reliant on machine learning knowledge. All you need are basic Python programming skills - everything else will fall into place as you go through the contents of the course.
-
What is the fee for the course?
This course is free of cost! All you need to do is sign up and get started.
-
How long would I have access to the “Introduction to Web Scraping using Python” course?
Once you register, you will have 6 months to complete the course. If you visit the course 6 months after your initial registration, you will need to enroll in the course again. Your past progress will be lost.
-
How much effort do I need to put in for this course?
You can complete the “Introduction to Web Scraping using Python” course in a few hours.
-
I’ve completed this course and have a good grasp on linear programming. What should I learn next?
The next step in your journey is to build on what you’ve learned so far. We recommend taking the popular “Applied Machine Learning” course.
-
Can I download the videos in this course?
We regularly update the “Introduction to Web Scraping using Python” course and hence do not allow videos to be downloaded. You can visit the free course anytime to refer to these videos.