We may earn an affiliate commission when you visit our partners.

Using Python to Access Web Data

This course will show how one can treat the Internet as a source of data. We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML, and JSON data formats in Python. This course will cover Chapters 11-13 of the textbook “Python for Everybody”. To succeed in this course, you should be familiar with the material covered in Chapters 1-10 of the textbook and the first two courses in this specialization. These topics include variables and expressions, conditional execution (loops, branching, and try/except), functions, Python data structures (strings, lists, dictionaries, and tuples), and manipulating files. This course covers Python 3.

Enroll now

Or subscribe to Coursera Plus

And get unlimited access to Coursera

Three deals to help you save

We found three deals and offers that may be relevant to this course.

Save money when you learn. All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Valid until December 12

Annual Subscription Savings

Unlock programs from Google, Microsoft, and IBM and join 77% of learners who reported positive career outcomes.

Only $239!

Valid for a limited time only

Future-proof your career

Access O'Reilly books, live events, courses, and more. Save with an annual subscription.

Take

15%

off

What's inside

Syllabus

Getting Started

In this section you will install Python and a text editor. In previous classes in the specialization this was an optional assignment, but in this class it is the first requirement to get started. From this point forward we will stop using the browser-based Python grading environment because the browser-based Python environment (Skulpt) is not capable of running the more complex programs we will be developing in this class.

Regular Expressions (Chapter 11)

Regular expressions are a very specialized language that allow us to succinctly search strings and extract data from strings. Regular expressions are a language unto themselves. It is not essential to know how to use regular expressions, but they can be quite useful and powerful.

Networks and Sockets (Chapter 12)

In this section we learn about the protocols that web browsers use to retrieve documents and web applications use to interact with Application Program Interfaces (APIs).

Programs that Surf the Web (Chapter 12)

In this section we learn to use Python to retrieve data from web sites and APIs over the Internet.

Web Services and XML (Chapter 13)

In this section, we learn how to retrieve and parse XML (eXtensible Markup Language) data.

JSON and the REST Architecture (Chapter 13)

In this module, we work with Application Program Interfaces / Web Services using the JavaScript Object Notation (JSON) data format.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops parsing and scraping techniques for data extraction

Teaches learners about networks, sockets, and web data access

Examines and incorporates HTML, XML, and JSON data formats in Python

Assumes learners have experience with Python and familiarity with earlier course material

Embraces hands-on approach to data manipulation and analysis

Emphasizes practical applications of web data extraction

Save this course

Save Using Python to Access Web Data to your list so you can find it easily later:

Save

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Using Python to Access Web Data with these activities:

Review Python Variables and Expressions

Show steps

Refreshes your understanding of basic Python variables and expressions to prepare you for more advanced material.

Browse courses on Variables

Show steps

Review the concepts of variables and expressions in Python.
Write some simple Python code to practice using variables and expressions.
Check your understanding by completing some exercises on variables and expressions.

Find a mentor

Show steps

A mentor can provide guidance and support to help you succeed in the course.

Show steps

Reach out to people in your network.
Attend industry events and meetups.
Search for mentors on online platforms.

Attend a data science conference or meetup

Show steps

Attending a data science event can help you connect with other professionals and learn about new trends.

Show steps

Identify relevant data science conferences or meetups.
Register for and attend the event.
Meet new people and learn about their work.

Ten other activities

Expand to see all activities and additional details

Show all 13 activities

Join a Study Group for Chapter Review

Show steps

Facilitates collaborative learning and reinforces your understanding through discussions and shared insights with fellow students.

Show steps

Find classmates or online groups interested in forming a study group for this course.
Establish regular meetings to review chapter content, discuss concepts, and solve problems together.
Contribute actively to the group discussions and support your peers.

Watch tutorials on Python web scraping

Show steps

Tutorials can help you learn new techniques and tricks for web scraping in Python.

Browse courses on Web Scraping

Show steps

Search for Python web scraping tutorials.
Watch the tutorials and follow along.
Experiment with the code and try it out yourself.

Practice Regular Expression Drills

Show steps

Provides repeated practice to strengthen your understanding and proficiency in using regular expressions.

Browse courses on Regular Expressions

Show steps

Find different online platforms or resources for regular expression drills.
Set aside a specific time each day to practice solving regular expression problems.
Review your mistakes and try to understand why a particular regular expression didn't work as expected.

Create a collection of Python web scraping resources

Show steps

Creating a collection of Python web scraping resources can help you organize and access relevant materials.

Browse courses on Web Scraping

Show steps

Search for Python web scraping resources.
Compile the resources into a document or spreadsheet.
Organize the resources by category or topic.

Learn about Web Scraping Using BeautifulSoup

Show steps

Builds your skills in web scraping by using BeautifulSoup to extract data from websites.

Browse courses on Web Scraping

Show steps

Find tutorials on using BeautifulSoup for web scraping.
Follow the tutorials to build a simple web scraper that extracts specific data from a website.
Experiment with different websites and data extraction techniques to improve your skills.

Build a Python script to scrape data from a website

Show steps

Building a Python script to scrape data from a website will allow you to apply the skills you've learned in the course.

Browse courses on Web Scraping

Show steps

Identify the target website you want to scrape data from.
Write a Python script using the Beautiful Soup library to scrape the data.
Run the script and check the results.

Create a Cheat Sheet for JSON and RESTful APIs

Show steps

Reinforces your understanding of JSON and RESTful APIs by creating a concise cheat sheet for quick reference.

Browse courses on JSON

Show steps

Summarise the key concepts of JSON and RESTful APIs in your own words.
Create a cheat sheet that includes syntax, examples, and best practices for using JSON and RESTful APIs.
Share your cheat sheet with classmates or online communities for feedback and discussion.

Attend a Workshop on Python for Data Science

Show steps

Enhances your knowledge and skills in Python for data science through hands-on learning and expert guidance.

Browse courses on Python

Show steps

Research and find workshops on Python for data science offered by reputable organizations or institutions.
Register for a workshop that aligns with your learning goals and schedule.
Actively participate in the workshop, ask questions, and engage with instructors and peers.

Write a blog post on a course topic

Show steps

Explaining a course topic to others helps you understand it better and strengthen your knowledge.

Browse courses on HTML

Show steps

Choose a topic you're familiar with.
Write a blog post explaining the topic.
Publish your blog post.

Contribute to Open-Source Web Development Projects

Show steps

Provides valuable hands-on experience in web development and enhances your understanding of real-world projects.

Browse courses on Web Development

Show steps

Identify open-source web development projects that align with your interests and skills.
Join the project community and familiarize yourself with the codebase.
Start contributing to the project by fixing bugs, implementing new features, or improving documentation.

Career center

Learners who complete Using Python to Access Web Data will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts use Python to extract, clean, and analyze data from various sources, including the web. This course provides a strong foundation in Python for data analysis, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Data Analysts.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use Python to develop machine learning models and analyze data to solve complex business problems. This course provides a solid foundation in Python for data analysis, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Data Scientists.

See salaries and explore the career path for Data Scientist

Web Developer

Web Developers use Python to build and maintain websites and web applications. This course provides a comprehensive overview of web development using Python, including web scraping, data parsing, and web APIs. It also covers topics such as HTML, CSS, and JavaScript, which are essential for Web Developers.

See salaries and explore the career path for Web Developer

Software Engineer

Software Engineers use Python to develop and maintain software applications. This course provides a solid foundation in Python for software development, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are useful skills for Software Engineers.

See salaries and explore the career path for Software Engineer

Quantitative Analyst

Quantitative Analysts use Python to analyze financial data and develop trading strategies. This course provides a strong foundation in Python for financial data analysis, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Quantitative Analysts.

See salaries and explore the career path for Quantitative Analyst

Business Analyst

Business Analysts use Python to analyze business data and make recommendations for improvement. This course provides a strong foundation in Python for business data analysis, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Business Analysts.

See salaries and explore the career path for Business Analyst

Market Researcher

Market Researchers use Python to collect and analyze data about consumer behavior. This course provides a strong foundation in Python for market research, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Market Researchers.

See salaries and explore the career path for Market Researcher

Data Journalist

Data Journalists use Python to analyze data and create data-driven stories. This course provides a solid foundation in Python for data journalism, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Data Journalists.

See salaries and explore the career path for Data Journalist

Information Security Analyst

Information Security Analysts use Python to analyze security data and identify threats. This course provides a strong foundation in Python for information security, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Information Security Analysts.

See salaries and explore the career path for Information Security Analyst

UX Researcher

UX Researchers use Python to collect and analyze data about user experience. This course provides a strong foundation in Python for UX research, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for UX Researchers.

See salaries and explore the career path for UX Researcher

Product Manager

Product Managers use Python to analyze data and make decisions about product development. This course provides a solid foundation in Python for product management, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Product Managers.

See salaries and explore the career path for Product Manager

Technical Writer

Technical Writers use Python to create documentation for software and other technical products. This course provides a strong foundation in Python for technical writing, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Technical Writers.

See salaries and explore the career path for Technical Writer

Librarian

Librarians use Python to manage and organize information. This course provides a solid foundation in Python for library science, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Librarians.

See salaries and explore the career path for Librarian

Archivist

Archivists use Python to manage and preserve historical records. This course provides a solid foundation in Python for archival science, including web scraping and data parsing techniques. It also covers web APIs and data visualization techniques, which are essential skills for Archivists.

See salaries and explore the career path for Archivist

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Using Python to Access Web Data.

Python for Everybody

Save

Is recommended as the primary textbook for this course as it covers the essential Python programming concepts that will be used throughout the course.

Using Python to Access Web Data

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

Share

Similar courses