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String Manipulation with stringr in R

中級スキルレベル

更新日 2022/11

Learn how to pull character strings apart, put them back together and use the stringr package.

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RProgramming

4時間

17 ビデオ

60 演習

5,150 XP

33,000

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コース説明

Character strings can turn up in all stages of a data science project. You might have to clean messy string input before analysis, extract data that is embedded in text or automatically turn numeric results into a sentence to include in a report. Perhaps the strings themselves are the data of interest, and you need to detect and match patterns within them. This course will help you master these tasks by teaching you how to pull strings apart, put them back together and use stringr to detect, extract, match and split strings using regular expressions, a powerful way to express patterns.

前提条件

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.

What you see isn't always what you have

Escape sequences

Turning numbers into strings

Using format() with numbers

Controlling other aspects of the string

Putting strings together

Annotation of numbers

A very simple table

Let's order pizza!

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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.

Introducing stringr

Putting strings together with stringr

String length

Extracting substrings

Hunting for matches

Detecting matches

Subsetting strings based on match

Counting matches

Splitting strings

Parsing strings into variables

Some simple text statistics

Replacing matches in strings

Replacing to tidy strings

Final challenges

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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.

Regular expressions

Matching the start or end of the string

Matching any character

Combining with stringr functions

More regular expressions

Alternation

Character classes

Hunting for phone numbers

Extracting age and gender from accident narratives

Parsing age and gender into pieces

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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).

Capturing parts of a pattern

Pulling out parts of a phone number

Extracting age and gender again

Backreferences

Using backreferences in patterns

Replacing with regular expressions

Replacing with backreferences

Unicode and pattern matching

Matching a specific code point or code groups

Matching a single grapheme

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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).

Getting the play into R

Identifying the lines, take 1

Identifying the lines, take 2

A case study on case

Changing case to ease matching

Ignoring case when matching

Fixing case problems

Wrapping up

An interview with Hadley Wickham

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String Manipulation with stringr in R

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