After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
课程介绍
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.
先修要求
课程大纲
课程大纲
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.
- Welcome!50 经验值
- Quotes100 经验值
- What you see isn't always what you have100 经验值
- Escape sequences100 经验值
- Turning numbers into strings50 经验值
- Using format() with numbers100 经验值
- Controlling other aspects of the string100 经验值
- formatC()100 经验值
- Putting strings together50 经验值
- Annotation of numbers100 经验值
- A very simple table100 经验值
- Let's order pizza!100 经验值
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).
R
String Manipulation with stringr in R
课程完成
