- Blog Categories
- Software Development Projects and Ideas
- 12 Computer Science Project Ideas
- 28 Beginner Software Projects
- Top 10 Engineering Project Ideas
- Top 10 Easy Final Year Projects
- Top 10 Mini Projects for Engineers
- 25 Best Django Project Ideas
- Top 20 MERN Stack Project Ideas
- Top 12 Real Time Projects
- Top 6 Major CSE Projects
- 12 Robotics Projects for All Levels
- Java Programming Concepts
- Abstract Class in Java and Methods
- Constructor Overloading in Java
- StringBuffer vs StringBuilder
- Java Identifiers: Syntax & Examples
- Types of Variables in Java Explained
- Composition in Java: Examples
- Append in Java: Implementation
- Loose Coupling vs Tight Coupling
- Integrity Constraints in DBMS
- Different Types of Operators Explained
- Career and Interview Preparation in IT
- Top 14 IT Courses for Jobs
- Top 20 Highest Paying Languages
- 23 Top CS Interview Q&A
- Best IT Jobs without Coding
- Software Engineer Salary in India
- 44 Agile Methodology Interview Q&A
- 10 Software Engineering Challenges
- Top 15 Tech's Daily Life Impact
- 10 Best Backends for React
- Cloud Computing Reference Models
- Web Development and Security
- Find Installed NPM Version
- Install Specific NPM Package Version
- Make API Calls in Angular
- Install Bootstrap in Angular
- Use Axios in React: Guide
- StrictMode in React: Usage
- 75 Cyber Security Research Topics
- Top 7 Languages for Ethical Hacking
- Top 20 Docker Commands
- Advantages of OOP
- Data Science Projects and Applications
- 42 Python Project Ideas for Beginners
- 13 Data Science Project Ideas
- 13 Data Structure Project Ideas
- 12 Real-World Python Applications
- Python Banking Project
- Data Science Course Eligibility
- Association Rule Mining Overview
- Cluster Analysis in Data Mining
- Classification in Data Mining
- KDD Process in Data Mining
- Data Structures and Algorithms
- Binary Tree Types Explained
- Binary Search Algorithm
- Sorting in Data Structure
- Binary Tree in Data Structure
- Binary Tree vs Binary Search Tree
- Recursion in Data Structure
- Data Structure Search Methods: Explained
- Binary Tree Interview Q&A
- Linear vs Binary Search
- Priority Queue Overview
- Python Programming and Tools
- Top 30 Python Pattern Programs
- List vs Tuple
- Python Free Online Course
- Method Overriding in Python
- Top 21 Python Developer Skills
- Reverse a Number in Python
- Switch Case Functions in Python
- Info Retrieval System Overview
- Reverse a Number in Python
- Real-World Python Applications
- Data Science Careers and Comparisons
- Data Analyst Salary in India
- Data Scientist Salary in India
- Free Excel Certification Course
- Actuary Salary in India
- Data Analyst Interview Guide
- Pandas Interview Guide
- Tableau Filters Explained
- Data Mining Techniques Overview
- Data Analytics Lifecycle Phases
- Data Science Vs Analytics Comparison
- Artificial Intelligence and Machine Learning Projects
- Exciting IoT Project Ideas
- 16 Exciting AI Project Ideas
- 45+ Interesting ML Project Ideas
- Exciting Deep Learning Projects
- 12 Intriguing Linear Regression Projects
- 13 Neural Network Projects
- 5 Exciting Image Processing Projects
- Top 8 Thrilling AWS Projects
- 12 Engaging AI Projects in Python
- NLP Projects for Beginners
- Concepts and Algorithms in AIML
- Basic CNN Architecture Explained
- 6 Types of Regression Models
- Data Preprocessing Steps
- Bagging vs Boosting in ML
- Multinomial Naive Bayes Overview
- Gini Index for Decision Trees
- Bayesian Network Example
- Bayes Theorem Guide
- Top 10 Dimensionality Reduction Techniques
- Neural Network Step-by-Step Guide
- Technical Guides and Comparisons
- Make a Chatbot in Python
- Compute Square Roots in Python
- Permutation vs Combination
- Image Segmentation Techniques
- Generative AI vs Traditional AI
- AI vs Human Intelligence
- Random Forest vs Decision Tree
- Neural Network Overview
- Perceptron Learning Algorithm
- Selection Sort Algorithm
- Career and Practical Applications in AIML
- AI Salary in India Overview
- Biological Neural Network Basics
- Top 10 AI Challenges
- Production System in AI
- Top 8 Raspberry Pi Alternatives
- Top 8 Open Source Projects
- 14 Raspberry Pi Project Ideas
- 15 MATLAB Project Ideas
- Top 10 Python NLP Libraries
- Naive Bayes Explained
- Digital Marketing Projects and Strategies
- 10 Best Digital Marketing Projects
- 17 Fun Social Media Projects
- Top 6 SEO Project Ideas
- Digital Marketing Case Studies
- Coca-Cola Marketing Strategy
- Nestle Marketing Strategy Analysis
- Zomato Marketing Strategy
- Monetize Instagram Guide
- Become a Successful Instagram Influencer
- 8 Best Lead Generation Techniques
- Digital Marketing Careers and Salaries
- Digital Marketing Salary in India
- Top 10 Highest Paying Marketing Jobs
- Highest Paying Digital Marketing Jobs
- SEO Salary in India
- Brand Manager Salary in India
- Content Writer Salary Guide
- Digital Marketing Executive Roles
- Career in Digital Marketing Guide
- Future of Digital Marketing
- MBA in Digital Marketing Overview
- Digital Marketing Techniques and Channels
- 9 Types of Digital Marketing Channels
- Top 10 Benefits of Marketing Branding
- 100 Best YouTube Channel Ideas
- YouTube Earnings in India
- 7 Reasons to Study Digital Marketing
- Top 10 Digital Marketing Objectives
- 10 Best Digital Marketing Blogs
- Top 5 Industries Using Digital Marketing
- Growth of Digital Marketing in India
- Top Career Options in Marketing
- Interview Preparation and Skills
- 73 Google Analytics Interview Q&A
- 56 Social Media Marketing Q&A
- 78 Google AdWords Interview Q&A
- Top 133 SEO Interview Q&A
- 27+ Digital Marketing Q&A
- Digital Marketing Free Course
- Top 9 Skills for PPC Analysts
- Movies with Successful Social Media Campaigns
- Marketing Communication Steps
- Top 10 Reasons to Be an Affiliate Marketer
- Career Options and Paths
- Top 25 Highest Paying Jobs India
- Top 25 Highest Paying Jobs World
- Top 10 Highest Paid Commerce Job
- Career Options After 12th Arts
- Top 7 Commerce Courses Without Maths
- Top 7 Career Options After PCB
- Best Career Options for Commerce
- Career Options After 12th CS
- Top 10 Career Options After 10th
- 8 Best Career Options After BA
- Projects and Academic Pursuits
- 17 Exciting Final Year Projects
- Top 12 Commerce Project Topics
- Top 13 BCA Project Ideas
- Career Options After 12th Science
- Top 15 CS Jobs in India
- 12 Best Career Options After M.Com
- 9 Best Career Options After B.Sc
- 7 Best Career Options After BCA
- 22 Best Career Options After MCA
- 16 Top Career Options After CE
- Courses and Certifications
- 10 Best Job-Oriented Courses
- Best Online Computer Courses
- Top 15 Trending Online Courses
- Top 19 High Salary Certificate Courses
- 21 Best Programming Courses for Jobs
- What is SGPA? Convert to CGPA
- GPA to Percentage Calculator
- Highest Salary Engineering Stream
- 15 Top Career Options After Engineering
- 6 Top Career Options After BBA
- Job Market and Interview Preparation
- Why Should You Be Hired: 5 Answers
- Top 10 Future Career Options
- Top 15 Highest Paid IT Jobs India
- 5 Common Guesstimate Interview Q&A
- Average CEO Salary: Top Paid CEOs
- Career Options in Political Science
- Top 15 Highest Paying Non-IT Jobs
- Cover Letter Examples for Jobs
- Top 5 Highest Paying Freelance Jobs
- Top 10 Highest Paying Companies India
- Career Options and Paths After MBA
- 20 Best Careers After B.Com
- Career Options After MBA Marketing
- Top 14 Careers After MBA In HR
- Top 10 Highest Paying HR Jobs India
- How to Become an Investment Banker
- Career Options After MBA - High Paying
- Scope of MBA in Operations Management
- Best MBA for Working Professionals India
- MBA After BA - Is It Right For You?
- Best Online MBA Courses India
- MBA Project Ideas and Topics
- 11 Exciting MBA HR Project Ideas
- Top 15 MBA Project Ideas
- 18 Exciting MBA Marketing Projects
- MBA Project Ideas: Consumer Behavior
- What is Brand Management?
- What is Holistic Marketing?
- What is Green Marketing?
- Intro to Organizational Behavior Model
- Tech Skills Every MBA Should Learn
- Most Demanding Short Term Courses MBA
- MBA Salary, Resume, and Skills
- MBA Salary in India
- HR Salary in India
- Investment Banker Salary India
- MBA Resume Samples
- Sample SOP for MBA
- Sample SOP for Internship
- 7 Ways MBA Helps Your Career
- Must-have Skills in Sales Career
- 8 Skills MBA Helps You Improve
- Top 20+ SAP FICO Interview Q&A
- MBA Specializations and Comparative Guides
- Why MBA After B.Tech? 5 Reasons
- How to Answer 'Why MBA After Engineering?'
- Why MBA in Finance
- MBA After BSc: 10 Reasons
- Which MBA Specialization to choose?
- Top 10 MBA Specializations
- MBA vs Masters: Which to Choose?
- Benefits of MBA After CA
- 5 Steps to Management Consultant
- 37 Must-Read HR Interview Q&A
- Fundamentals and Theories of Management
- What is Management? Objectives & Functions
- Nature and Scope of Management
- Decision Making in Management
- Management Process: Definition & Functions
- Importance of Management
- What are Motivation Theories?
- Tools of Financial Statement Analysis
- Negotiation Skills: Definition & Benefits
- Career Development in HRM
- Top 20 Must-Have HRM Policies
- Project and Supply Chain Management
- Top 20 Project Management Case Studies
- 10 Innovative Supply Chain Projects
- Latest Management Project Topics
- 10 Project Management Project Ideas
- 6 Types of Supply Chain Models
- Top 10 Advantages of SCM
- Top 10 Supply Chain Books
- What is Project Description?
- Top 10 Project Management Companies
- Best Project Management Courses Online
- Salaries and Career Paths in Management
- Project Manager Salary in India
- Average Product Manager Salary India
- Supply Chain Management Salary India
- Salary After BBA in India
- PGDM Salary in India
- Top 7 Career Options in Management
- CSPO Certification Cost
- Why Choose Product Management?
- Product Management in Pharma
- Product Design in Operations Management
- Industry-Specific Management and Case Studies
- Amazon Business Case Study
- Service Delivery Manager Job
- Product Management Examples
- Product Management in Automobiles
- Product Management in Banking
- Sample SOP for Business Management
- Video Game Design Components
- Top 5 Business Courses India
- Free Management Online Course
- SCM Interview Q&A
- Fundamentals and Types of Law
- Acceptance in Contract Law
- Offer in Contract Law
- 9 Types of Evidence
- Types of Law in India
- Introduction to Contract Law
- Negotiable Instrument Act
- Corporate Tax Basics
- Intellectual Property Law
- Workmen Compensation Explained
- Lawyer vs Advocate Difference
- Law Education and Courses
- LLM Subjects & Syllabus
- Corporate Law Subjects
- LLM Course Duration
- Top 10 Online LLM Courses
- Online LLM Degree
- Step-by-Step Guide to Studying Law
- Top 5 Law Books to Read
- Why Legal Studies?
- Pursuing a Career in Law
- How to Become Lawyer in India
- Career Options and Salaries in Law
- Career Options in Law India
- Corporate Lawyer Salary India
- How To Become a Corporate Lawyer
- Career in Law: Starting, Salary
- Career Opportunities: Corporate Law
- Business Lawyer: Role & Salary Info
- Average Lawyer Salary India
- Top Career Options for Lawyers
- Types of Lawyers in India
- Steps to Become SC Lawyer in India
- Tutorials
- C Tutorials
- Recursion in C: Fibonacci Series
- Checking String Palindromes in C
- Prime Number Program in C
- Implementing Square Root in C
- Matrix Multiplication in C
- Understanding Double Data Type
- Factorial of a Number in C
- Structure of a C Program
- Building a Calculator Program in C
- Compiling C Programs on Linux
- Java Tutorials
- Handling String Input in Java
- Determining Even and Odd Numbers
- Prime Number Checker
- Sorting a String
- User-Defined Exceptions
- Understanding the Thread Life Cycle
- Swapping Two Numbers
- Using Final Classes
- Area of a Triangle
- Skills
- Software Engineering
- JavaScript
- Data Structure
- React.js
- Core Java
- Node.js
- Blockchain
- SQL
- Full stack development
- Devops
- NFT
- BigData
- Cyber Security
- Cloud Computing
- Database Design with MySQL
- Cryptocurrency
- Python
- Digital Marketings
- Advertising
- Influencer Marketing
- Search Engine Optimization
- Performance Marketing
- Search Engine Marketing
- Email Marketing
- Content Marketing
- Social Media Marketing
- Display Advertising
- Marketing Analytics
- Web Analytics
- Affiliate Marketing
- MBA
- MBA in Finance
- MBA in HR
- MBA in Marketing
- MBA in Business Analytics
- MBA in Operations Management
- MBA in International Business
- MBA in Information Technology
- MBA in Healthcare Management
- MBA In General Management
- MBA in Agriculture
- MBA in Supply Chain Management
- MBA in Entrepreneurship
- MBA in Project Management
- Management Program
- Consumer Behaviour
- Supply Chain Management
- Financial Analytics
- Introduction to Fintech
- Introduction to HR Analytics
- Fundamentals of Communication
- Art of Effective Communication
- Introduction to Research Methodology
- Mastering Sales Technique
- Business Communication
- Fundamentals of Journalism
- Economics Masterclass
- Free Courses
Web Scraping Projects & Topics For Beginners [2024]
Updated on 04 March, 2024
52.16K+ views
• 21 min read
Table of Contents
In today’s digital age, mastering web scraping is crucial for professionals aiming to automate structured data extraction from websites, especially when an API is unavailable or offers limited data access. The concept might seem daunting initially, but I’ve found that the best way to grasp web scraping is through hands-on experience with Python projects.
In this guide, I’ll share insights into various web scraping project topics for beginners, tailored to suit a range of industries and skill levels. Whether you’re just starting or looking to deepen your expertise, you’ll discover a project that matches your interests and professional aspirations.
Web scraping, also known as Web Harvesting or Screen Scraping, involves extracting large quantities of data from websites and storing it locally, either in a file on your computer or in a database. This technique is invaluable for professionals like me, aiming to leverage web data for analysis, insights, or decision-making in our respective fields.
What is Web Scraping?
Whenever you want any information, you Google it and go to the webpage, which offers the most relevant answer to your query. You can view the data you needed, but what if you need to save it locally? What if you want to see the data of a hundred more pages?
Most of the webpages present on the internet don’t offer the option to save the data present there locally. To keep it that way, you’ll have to copy and paste everything manually, which is very tedious. Moreover, when you have to save the data of hundreds (sometimes, thousands) of webpages, this task can seem strenuous. You might end up spending days just copy-pasting bits from different websites. Check out our website if you want to learn data science.
This is where web scraping comes in. It automates this process and helps you store all the required data with ease and in a small amount of time. For this purpose, many professionals use web scraping software or web scraping techniques.
Read more: Top 7 Data Extraction Tools in the Market
Why Perform Web Scraping?
In data science, to do anything, you need to have data at hand. To get that data, you’ll need to research the required sources, and web scraping helps you. Web scraping collects and categorizes all the required data in one accessible location. Researching with a single, convenient location is much more feasible and more comfortable than searching for everything one-by-one.
Just as data science is prevalent in many industries, web scraping is widespread too. When you take a look at the web scraping project ideas we’ve discussed here, you will notice how various industries use this technique for their benefit.
What programming languages are used for web scrapping, and which one is the best?
A bunch of programming languages can be used for web scrapping, and the list includes languages like Python, Ruby, Java, PHP and Perl. along with these, one can also use HTML or HTML markup or Javascript as their preferred programming language for web scrapping.
On that note, the language that is preferred the most to perform web scrapping is Python. The main reason is its ease of use. If someone is a beginner in web scrapping, they should definitely choose web scraping python projects as it utilises an object-oriented programming language. The classes and objects in web scraping projects using Python are comparatively easier to use than any other language, making it beginner friendly.
How to scrape data from a website by using Python?
In case you are an absolute beginner at web scrapping, before jumping into web scraping python projects, here is a brief overview of how web scrapping on python web scraping projects is done and what are the prerequisites to do that.
Step 1: Load the web pages with ‘request’. For this, the ‘requests’ module is used which sends HTTP requests using Python. This request will bring back a Response Object which will contain all the response data.
Step 2: Extract the title. This is done by taking the help of Python libraries like Selenium, BeautifulSoup or Pandas. All of these libraries have different purposes and as we are trying to extract data, the library that we need will be BeautifulSoup.
Step 3: Extract the body content. Similar to extract the title, BeautifulSoup is used here to easily extract some of the sections of the body content.
Step 4: Select DOM elements with BeautifulSoup methods like “.select” under the CSS selector inside the library.
Step 5: Scrape the top items and store them in a list called “top_items”. Use the “strip” method in this step to remove extra whitespaces that are present in the output.
Step 6: Extract the links. To be more precise, extract the “herf” attributes and link them with their “texts”. By doing this you will create a list named “all_links”.
Step 7: Store the data in the required format.
Now that you’re familiar with the basics of web scraping, we should start discussing web scraping projects too. Also, you can easily perform these web scraping projects using Python.
Explore our Popular Data Science Courses
Web Scraping Projects
The following are our web scraping project ideas. They are of different industries so that you can choose one according to your interests and expertise.
1. Scrape a Subreddit
Reddit is one of the most popular social media platforms out there. It has communities called subreddits, for nearly every topic you can imagine. From programming to World of Warcraft, there is a community for everything on Reddit. All of these communities are quite active, and their members (on a side note: Reddit’s users are called Redditors)share a lot of valuable information, opinions, and content.
Learn more: 17 Fun Social Media Project Ideas & Topics For Beginners
How to work on this project
Reddit’s thriving communities are a great place to try out your web scraping abilities. You can scrape its subreddits for particular topics and figure out what its users say about it (and how often they discuss it). For example, you can scrape the subreddit r/webdev, where web development professionals and enthusiasts discuss the various aspects of this field. You can scrap this subreddit for a particular topic (such as finding jobs).
This was just an example, and you can choose any subreddit and use it as your target.
This project is suitable for beginners. So, if you don’t have much experience using web scraping techniques, you should start with this one. You can modify the difficulty level of this project by selecting a smaller (or bigger) subreddit. Here is the source code to the project.
upGrad’s Exclusive Data Science Webinar for you –
How to Build Digital & Data Mindset
2. Perform Consumer Research
Consumer research is a vital aspect of marketing and product development. It helps a company understand what their targeted consumers want, whether their customers liked their product or not, and how the general public perceives their product or services. If you’d use your data science expertise in marketing, you’d have to perform consumer research many times.
Researching potential buyers helps a company in many ways. They get to know:
- What are the likings of their prospective clients
- What are the things their prospective customers hate
- What products they use
- What products they avoid
This is just the tip of the iceberg; consumer research (also known as consumer analysis) can cover many other areas.
How to work on this project
To perform consumer research, you can gather data from customer review websites and social media sites. They are a great place to start with.
Here are some popular review sites where you can start to get the necessary data:
These are just a few names. Apart from these review sites, you can head to Facebook to gather links as well. If you find any blogs that cover your company’s products, then you can include them in your web scraping efforts as well. They are an excellent source for getting valuable insight.
Doing this project will help you in performing many other tasks in data science, particularly sentiment analysis. So, pick a brand (or a product) and start researching its reviews online. Here is the link to the source code.
Learn more: Data Analytics Is Disrupting These 4 Martech Roles
Top Data Science Skills to Learn to upskill
SL. No | Top Data Science Skills to Learn | |
1 |
Data Analysis Online Courses | Inferential Statistics Online Courses |
2 |
Hypothesis Testing Online Courses | Logistic Regression Online Courses |
3 |
Linear Regression Courses | Linear Algebra for Analysis Online Courses |
3. Analyse Competitors
Competitive analysis is one of the many aspects of digital marketing. It also requires data scientists and analysts’ expertise because they have to gather data and find what their competition is doing.
You can perform web scraping for competitive analysis too. Completing this project will help you considerably in understanding how this skill can help brands in digital marketing, one of the most crucial aspects in today’s world.
How to Work on This Project
First, you should choose an industry of your liking. You can start with car companies, teaching companies (such as upGrad), or any other. After that, you have to pick a brand for which you’ll analyze the competitors. We recommend starting with a small brand if you are a beginner because they have fewer competitors than major ones.
Must read: Learn excel online free!
Once you’ve picked the brand, you should search for its competitors. You’ll have to scrape the web for their competitors, find what they sell, and how they target their audience. If you’ve picked a tiny brand and don’t know its competitors, you should search for its product categories. For example, if you picked Tata Motors as your brand, you’d search for a phrase similar to ‘buy cars in India.’ The search result will show you many cars of different brands, all of which are competitors of Tata Motors.
You can build a scraping tool that analyses your selected brand’s competitors and shows the following data:
- What are their products?
- What are the prices of their products?
- What are the offers on their products (or services)?
- Are they offering something which your brand isn’t?
You can add more sections, depending on your level of expertise and skill. This list is just to give you an idea of what you should look for in your selected brand’s competitors.
Such web scraping is particularly beneficial for new and growing companies. If you aspire to work with startups in the future, this is the perfect project idea. To make this project more challenging, you can increase the number of competitors you want to analyze. If you’re a beginner, you can start with one or two competitors, whereas if you’re a little advanced, you can start with three or four competitors.
Our learners also read: Free Python Course with Certification
4. Use Web Scraping for SEO
Search Engine Optimization (also known as SEO) is the task of modifying a website, matching the preferences of search engines’ algorithms. As the number of internet users is steadily rising, the demand for effective SEO is also increasing. SEO impacts the rank of a website when a person searches for a particular keyword.
It is a humongous topic and requires a complete guide. All you need to know for SEO is that it requires specific criteria that a website has to fulfill. You can read more on SEO and what it is in our article on how to build an SEO strategy from scratch.
You can use web scraping for SEO and help websites ranking higher for keywords.
How to work on this project
You can build a data scraping tool that scrapes your selected websites’ rankings for different keywords. The tool can extract the words these companies use to describe themselves too. You can use this technique for specific keywords and assort a list of websites. A marketing team can use this list to use the best keywords out of that list and help their website rank higher.
While this is a simple application of web scraping in SEO, you can make it more advanced. For example, you can create a similar tool but add the function of getting the metadata of those web pages. This would include the title of the web page (the text you see on the tab) and other relevant pieces of information.
On the other hand, you can build a web scraper that checks the word count of the different pages ranking for a keyword. This way you can understand the impact word count has on the ranking of a webpage
There are many ways to make a web scraper for SEO. You can take inspiration from Moz or Ahrefs and build an advanced web scraper yourself. There’s a lot of demand for useful web scraping tools in the SEO industry.
If you are interested in using your tech skills in digital marketing, this is an excellent project. It will make you familiar with the applications of data science in online marketing as well. Apart from that, you’ll also learn about the multiple methods of using web scraping for search engine optimization. You can find the source code for the project here.
Our learners also read: Free Python Course with Certification
5. Scrape Data of Sports Teams
Are you a sports fan? If so, then this is the perfect project idea for you. You can use your knowledge of web scraping to scrape data from your favorite sports team and find some interesting insights. You can choose any team you like of any popular sports.
How to work on this project
You can choose your favorite team and scrape the websites of their official website, the organization that handles their sports, and relevant archives. For example, if you’re a cricket fan, you can use ESPN’s cricket statistics database.
After you’ve scraped this data, you’d have all the required information on your favorite team. You can expand this project and add more teams in your collection to make this project a little more challenging.
However, this is among the most suitable web scraping projects for beginners. You can learn a lot about web scraping and its applications in a fun and exciting manner. Link to the source code is mentioned here.
6. Get Financial Data
The finance sector uses a lot of data. Financial data is useful in many ways as it helps investors analyze a company’s performance and reliability. Similarly, it helps a company in analyzing its position and where it stands in terms of finances. If you want to use your knowledge of data and web scraping in the finance sector, then you should work on this project.
How to work on this project
There are multiple ways to go about this project. You can start by scraping the web for the performance of a company’s stock in a set period and the news articles related to the company of that period. This data can help an investor figure out how different things affected that particular company’s stock price. Apart from that, this data will also help the investor understand what factors affect the company’s stock price, which factors don’t.
Financial statistics are crucial for any company’s health. They help the stakeholders of a company understand how well (or how badly) their business is performing. Financial data is always helpful, and this project will allow you to use your skills in this regard.
You can start with a single company initially and make the project more challenging by adding the data from more companies. However, if you want to focus on one particular company, you can increase the timeline and look at the data of a year or more. Here is the link to the source code.
7.Scrape a Job Portal
It is among the most popular web scraping project ideas. There are many job portals on the web, and if you’ve ever thought of using your expertise in data science in human resources, this is the right project for you.
There are many job portals online, and you can pick anyone for this project. Here are some places to get you started:
- Naukri.com
- Indeed.co.in
- Timesjobs.com
How to work on this project
In this project, you can build a tool that scrapes a job portal (or multiple job portals) and checks the requirements of a particular job. For example, you can look at all the ‘data analyst’ jobs present in a job portal and analyze its job requirements to see the most popular criteria for hiring one such professional.
You can add more jobs or portals in your search to add more difficulty to this project. It’s a fantastic project for anyone who wants to apply data science in management and relevant streams.
Also Read: Data Science Project Ideas & Topics
Read our popular Data Science Articles
8.Creating a job search platform utilizing web scraping
We must apply for employment roles through many websites while applying for a job. This is a tiresome process at times. We might think about developing a platform to scrape job postings from many websites, such as Glassdoor, LinkedIn, and others. Using web scraping to create a job search engine involves collecting job listings from multiple websites and combining them into a single database. We will be able to view the jobs in one location, which will save us time and effort. This is one of the popular web scraping project topics for beginners.
How to work on this project
- Identify which job search portals to target for scraping, such as Indeed, Glassdoor, LinkedIn, Monster, etc.
- Take note of the layout of these websites, including the HTML structure, pagination techniques, and the presentation of job listings.
- Data such as the company name, industry, skills, degree of education, career stage, pay information, and job type can all be extracted.
- Consider the features you want your job search engine to have, like filters, user accounts, alerts, and search capabilities.
- Create and implement the job search engine’s user interface, including components such as a search bar, filters, job listing display, and pagination.
- Create a database schema to store the job listings that are being scraped.
- To handle frontend requests, create backend APIs (application programming interfaces). Integrate your web scraping code with the backend to add scraped job listings to the database.
This GitHub Repository contains the source code that will help us use Python programming to scrape the job listing data from job portals like Glassdoor and Monster.
9.Analyzing customer reviews and feedback
Developing a web scraping project to evaluate customer reviews involves gathering reviews from different internet sites, evaluating their sentiment, identifying significant topics or themes, and providing organizations with insights. Businesses can improve products and services, acquire insightful information about customer opinions, and make well-informed decisions to increase customer happiness and loyalty by scraping data for individual products available on Amazon or Flipkart and analyzing customer reviews.
How to work on this project
- Choose a product to scrape reviews from by identifying target websites that provide consumer reviews, including Amazon, Flipkart, Myntra, etc.
- Pull out the necessary information, such as review content, rating, product specifications, reviewer details, etc., using the web scraping tool.
- Determine the sentiment (positive, negative, or neutral) of each review by applying sentiment analysis techniques using pre-trained sentiment analysis models. Based on the findings of the analysis, give each review a sentiment score. Additionally, we can use free versions of several APIs to determine the sentiment score.
- Analyze the sentiment distribution across different products on the portal. Provide visualizations and summaries using a data visualization tool to present the analysis results effectively.
This GitHub Repository contains the source code to extract customer reviews from Home Depot, Walmart, Amazon, and Lowe’s and to classify negative with a star rating of less than 3 for certain issues.
10.Implementing alerts for price drops on E-commerce products
Using web scraping to develop a Price Drop Alert system for E-commerce items involves tracking price changes across several online merchants and alerting customers when prices drop below a certain value. Everyone desires to purchase their preferred items at the greatest discount possible. However, there’s a chance of missing out on optimal deals. Alternatively, by monitoring price shifts of items in our wish list, we can capitalize on the most opportune moment to make a purchase.
How to work on this project
- Find popular marketplaces like Amazon, eBay, Walmart, and others. Select the products you wish to watch for price drops on these sites.
- Use online scraping tools such as Scrapy to retrieve product details from the target websites, such as the name, price, URL, and availability status.
- Create a database schema to hold the product data that has been scraped and set up a system to update the database with the most recent information regularly.
- Provide an intuitive online interface that enables consumers to enter their selected products and create alerts for price drops.
This GitHub Repository contains the source code that provides a user interface to interact with an automated price-tracking web scraper.
11.Scraping news websites and aggregating their content
It’s getting more and harder to stay up to date with all the news that highlights noteworthy events happening across the world, with so many new channels appearing all the time. The goal of this project is to gather news stories from multiple internet sources, compile them into a single platform, and give consumers an easy method to view and browse the most recent information on a variety of subjects and categories. We will extract news articles from a variety of news websites by using web scraping techniques and obtaining data such as article names, authors, publishing dates, content, and URLs. The project offers users a centralized platform to access and explore news articles from various sources.
How to work on this project
- Pick the preferred news websites from where we need to scrape data to gather news.
- Create a database structure to effectively store the news articles that have been scrapped.
- Create algorithms to classify and arrange news items according to sources, keywords, or subjects. Give people the option to browse news by category so they can explore and navigate with ease.
- Provide an intuitive user experience for the news aggregation platform that will consist of design features such as showcasing top news stories, category pages for browsing news by topic, and individual article pages for reading detailed content.
This GitHub Link contains source code for different news scrappers that are built to crawl the web and extract information about news articles that we want.
12.Scraping data of companies from the web
The project’s goal is to use web scraping techniques to gather and compile company-related data from several online sources. The objective is to build an extensive collection of business data that may be utilized for lead generation, market research, competitive analysis, etc. This offers a strong tool for gathering, combining, and evaluating data about businesses from several web sources. Utilizing online scraping techniques will make it easier to access and examine corporate data for a range of uses. Analyzing a company’s financial statements, for instance, is essential if you intend to invest in them.
How to work on this project
- Identify relevant websites and online platforms such as Glassdoor, Ambitionbox, Crunchbase, or LinkedIn that contain information about companies.
- Create web scraping scripts to retrieve business information from the identified sources.
- This covers details about the organization, including its name, location, revenue, industry, stock price, and size.
- It also includes contact information, website URLs, social media profiles, and any other relevant information.
- Create an effective data storage schema and select a suitable database management system to store and arrange the company’s data that has been scrapped.
You can head over to this YouTube link, which demonstrates how to use BeautifulSoup, Request, and Pandas to web-scrape a website to get a list of companies’ data in an Excel spreadsheet.
13.Analyse IT Salaries to Suggest Optimal Job Change Times
This project is last on the list of our web scraping projects with source code. The goal of this web scraping project is to track and assess pay trends within the IT sector to suggest the best times for professionals to think about changing jobs. The project aims to provide useful insights to people looking for prospects for career progression or pay rise by utilizing data on IT salaries. This will assist IT professionals in knowing when to negotiate a raise or look for a new position.
How to work on this project
- Locate multiple sites, such as AmbitionBox, PayScale, and Glassdoor, to obtain information on salaries.
- Use web scraping methods or APIs to gather current pay data for various IT positions and regions.
- Build a scraper that systematically extracts relevant information from selected websites, such as job titles, pay ranges, and locations (ideally in Python using libraries like BeautifulSoup or Scrapy).
- Compute the average and the median salary for your role and experience and compare it with your current salary.
This GitHub link contains the source code that scrapes salary data from Glassdoor.
Conclusion
We hope you found this list of web scraping project ideas useful and exciting. If you have any thoughts or suggestions on this article or topic, feel free to let us know. On the other hand, if you want to learn more, you should head to our blog to find many relevant and valuable resources.
You can enroll in a data science course as well to get a more individualized learning experience. A course can help you learn all the important topics and concepts in a personalized approach so you can be job-ready in very little time.
If you are curious to learn about data science, check out IIIT-B & upGrad’s Executive PG Programm in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.
What do you think of these project ideas? Which one of these ideas did you like the most? Let us know in the comments.
Frequently Asked Questions (FAQs)
1. What is the difference between web crawling and web scraping?
Many people get confused between web crawling and web scraping and end up considering them as equivalent. Well, they are two separate terms with totally different meanings. The web crawler is artificial intelligence, also known as “the spider” that surfs the internet and searches the required content by following the links. Web scraping is the next step after web crawling. In web scraping, data is extracted automatically using artificial intelligence known as “scrapers”. This extracted data can be used for various processes like comparison, analysis, and verification based upon the client’s needs. It also allows you to store a large amount of data within a small amount of time.
2. What are the essentials that must be kept in mind while creating a consumer research project?
Consumer research is crucial for every product-based company and there are certain things that one must keep in mind while working on a project on consumer research. There is a lot more to research and analyze while working on a consumer research project. There are various websites that provide the necessary data on consumer preferences like Trustpilot, Yelp, GripeO, and BBB. Apart from these review sites, you can also visit Facebook to get the links.
3. How can web scraping be used for SEO purposes?
Search Engine Optimization or SEO is a process that improves the visibility of your site whenever someone’s search meets your website domain. For example, you have an e-commerce website and some search for a product that is available on your website as well as on your competitors’ websites. Now, whose website or webpage among you and your competitor will occur first will depend on the SEO. Web scraping can be used for SEO and help websites ranking higher for keywords. You can build a web scraper that checks the word count of the different pages ranking for a keyword. You can even add the functionality in your web scraper to get the meta description or metadata of those web pages.