Skip to main content

Regular Expressions in Python

Learn about string manipulation and become a master at using regular expressions.

Start Course for Free
4 Hours15 Videos54 Exercises25,511 Learners4650 XPPython Programmer TrackPython Toolbox Track

Create Your Free Account



By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA. You confirm you are at least 16 years old (13 if you are an authorized Classrooms user).

Loved by learners at thousands of companies

Course Description

As a data scientist, you will encounter many situations where you will need to extract key information from huge corpora of text, clean messy data containing strings, or detect and match patterns to find useful words. All of these situations are part of text mining and are an important step before applying machine learning algorithms. This course will take you through understanding compelling concepts about string manipulation and regular expressions. You will learn how to split strings, join them back together, interpolate them, as well as detect, extract, replace, and match strings using regular expressions. On the journey to master these skills, you will work with datasets containing movie reviews or streamed tweets that can be used to determine opinion, as well as with raw text scraped from the web.

  1. 1

    Basic Concepts of String Manipulation


    Start your journey into the regular expression world! From slicing and concatenating, adjusting the case, removing spaces, to finding and replacing strings. You will learn how to master basic operation for string manipulation using a movie review dataset.

    Play Chapter Now
    Introduction to string manipulation
    50 xp
    First day!
    100 xp
    Artificial reviews
    100 xp
    100 xp
    String operations
    50 xp
    Normalizing reviews
    100 xp
    Time to join!
    100 xp
    Split lines or split the line?
    100 xp
    Finding and replacing
    50 xp
    Finding a substring
    100 xp
    Where's the word?
    100 xp
    Replacing negations
    100 xp
  2. 2

    Formatting Strings

    Following your journey, you will learn the main approaches that can be used to format or interpolate strings in python using a dataset containing information scraped from the web. You will explore the advantages and disadvantages of using positional formatting, embedding expressing inside string constants, and using the Template class.

    Play Chapter Now
  3. 3

    Regular Expressions for Pattern Matching

    Time to discover the fundamental concepts of regular expressions! In this key chapter, you will learn to understand the basic concepts of regular expression syntax. Using a real dataset with tweets meant for sentiment analysis, you will learn how to apply pattern matching using normal and special characters, and greedy and lazy quantifiers.

    Play Chapter Now
  4. 4

    Advanced Regular Expression Concepts

    In the last step of your journey, you will learn more complex methods of pattern matching using parentheses to group strings together or to match the same text as matched previously. Also, you will get an idea of how you can look around expressions.

    Play Chapter Now

In the following tracks

Python ProgrammerPython Toolbox


sara-billenSara Billenhillary-green-lermanHillary Green-Lerman


Intermediate Python
Maria Eugenia Inzaugarat Headshot

Maria Eugenia Inzaugarat

Data Scientist and Artificial Intelligence Consultant

Eugenia is a passionate, dedicated, and proactive data scientist and Artificial Intelligence Consultant that enjoys not only doing machine learning projects but also telling stories with data. She obtained a Ph.D. from the University of Buenos Aires. She has taught university courses in mathematics and biology as well as online courses on Data Science. Having transitioned from an academic background into data science, Eugenia loves teaching concepts related to python programming, data science, and machine learning to help others also gain knowledge about these fields.
See More

What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA