You’ll learn about regular expressions (regex), a powerful tool that allows you to match and manipulate text data with precision. You’ll also learn to work with JSON data, a common format you’ll encounter when pulling data from web APIs. Then you’ll dive into map and anonymous functions, two intermediate-to-advanced concepts in R that can speed up your data cleaning.
You’ll also learn how to resolve missing values in your data, a critical part of almost every data analysis project. Rather than dropping rows or columns, which reduces the amount of data you have to work with, you’ll learn statistical techniques to impute missing data, and you’ll also learn how to insert data from outside sources.
Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser.
- Cleaning and manipulating text data using regex
- Using map and anonymous functions
- Resolving missing data
- Advanced techniques for data cleaning
Advanced Data Cleaning in R [4 lessons]
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