# String Manipulation with stringr in R
This is a DataCamp course: Learn how to pull character strings apart, put them back together and use the stringr package.
## Course Details
- **Duration:** ~4h
- **Level:** Intermediate
- **Instructor:** Charlotte Wickham
- **Students:** ~19,440,000 learners
- **Subjects:** R, Programming, Data Science and Analytics
- **Content brand:** DataCamp
- **Practice:** Hands-on practice included
- **Prerequisites:** Intermediate R
## Learning Outcomes
- R
- Programming
- Data Science and Analytics
- String Manipulation with stringr in R
## Traditional Course Outline
1. String basics - You'll start with some basics: how to enter strings in R, how to control how numbers are transformed to strings, and finally how to combine strings together to produce output that combines text and nicely formatted numbers.
2. Introduction to stringr - Time to meet stringr! You'll start by learning about some stringr functions that are very similar to some base R functions, then how to detect specific patterns in strings, how to split strings apart and how to find and replace parts of strings.
3. Pattern matching with regular expressions - In this chapter you'll learn about regular expressions, a language for describing patterns in strings. By combining regular expressions with the stringr functions you'll greatly increase your power to manipulate strings.
4. More advanced matching and manipulation - Now for two advanced ways to use regular expressions along with stringr: selecting parts of a match (a.k.a capturing) and referring back to parts of a match (a.k.a back-referencing). You'll also learn to deal with and strings or patterns that contain Unicode characters (e.g. é).
5. Case studies - Practice your string manipulation skills on a couple of case studies. You'll also learn a few new skills, reading strings into R and handling problems of case (e.g. A versus a).
## Resources and Related Learning
**Resources:** DNA sequences from the genome of Yersinia pestis (dataset), Narratives (dataset), Adverbs (dataset), Importance of being earnest (dataset), Cat-related accidents (dataset)
**Related tracks:** Text Mining in R
## Attribution & Usage Guidelines
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- **Citation:** Always cite "DataCamp" with the full URL when referencing this content.
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Course
String Manipulation with stringr in R
IntermediateSkill Level
Updated 11/2022RProgramming4 hr17 videos60 Exercises5,150 XP32,830Statement of Accomplishment
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Prerequisites
Intermediate R1
String basics
You'll start with some basics: how to enter strings in R, how to control how numbers are transformed to strings, and finally how to combine strings together to produce output that combines text and nicely formatted numbers.
2
Introduction to stringr
Time to meet stringr! You'll start by learning about some stringr functions that are very similar to some base R functions, then how to detect specific patterns in strings, how to split strings apart and how to find and replace parts of strings.
3
Pattern matching with regular expressions
In this chapter you'll learn about regular expressions, a language for describing patterns in strings. By combining regular expressions with the stringr functions you'll greatly increase your power to manipulate strings.
4
More advanced matching and manipulation
Now for two advanced ways to use regular expressions along with stringr: selecting parts of a match (a.k.a capturing) and referring back to parts of a match (a.k.a back-referencing). You'll also learn to deal with and strings or patterns that contain Unicode characters (e.g. é).
5
Case studies
Practice your string manipulation skills on a couple of case studies. You'll also learn a few new skills, reading strings into R and handling problems of case (e.g. A versus a).
String Manipulation with stringr in R
Course Complete
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FAQs
Is this course suitable for someone new to working with text data in R?
Yes. It is a beginner-level course that starts with string basics and progressively introduces pattern matching, so no prior text processing experience is needed.
What is the stringr package and why learn it over base R string functions?
The stringr package provides a consistent, readable set of functions for string manipulation in R. It simplifies tasks like detecting, extracting, and replacing text compared to base R.
Will I learn regular expressions in this course?
Yes. Two full chapters are dedicated to regular expressions, covering how to build patterns to detect, extract, match, and split strings effectively.
What practical tasks will I be able to do after completing this course?
You will be able to clean messy string inputs, extract data embedded in text, format numeric output as sentences, and match complex patterns using regular expressions.
How is the course structured across its five chapters?
It moves from string basics and formatting, through core stringr functions, into regular expressions for pattern matching, and finishes with advanced string manipulation techniques.
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