Data transformation
Author: David Kane

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## Introduction

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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

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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