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Introduction

This tutorial covers Chapter 4: Data transformation from R for Data Science (2e) by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund. You will learn about the key functions from the dplyr package for working with data including [filter()](https://dplyr.tidyverse.org/reference/filter.html), [arrange()](https://dplyr.tidyverse.org/reference/arrange.html), [select()](https://dplyr.tidyverse.org/reference/select.html), [mutate()](https://dplyr.tidyverse.org/reference/mutate.html), and [summarize()](https://dplyr.tidyverse.org/reference/summarise.html).

The goal of this chapter is to give you an overview of all the key tools for transforming a data frame. We’ll start with functions that operate on rows and then columns of a data frame, then circle back to talk more about the pipe, an important tool that you use to combine verbs.

Summary

This tutorial covered Chapter 4: Data transformation from R for Data Science (2e) by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund. You learned about the key functions from the dplyr package for working with data including filter(), arrange(), select(), mutate(), and summarize().

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Data transformation

David Kane