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Jonathan Page 2016-08-16 02:11:45 -10:00 committed by Hadley Wickham
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## Introduction
Visualisation is an important tool for insight generation, but it is rare that you get the data in exactly the right form you need. Often you'll need to create some new variables or summaries, or maybe you just want to rename the variables or reorder the observations in order to make the data a little easier to work with. You'll learn how to do all that (and more!) in this chapter which will teach you how to transform your data using the dplyr package and a new dataset on flights departing New York City in 2013.
Visualisation is an important tool for insight generation, but it is rare that you get the data in exactly the right form you need. Often you'll need to create some new variables or summaries, or maybe you just want to rename the variables or reorder the observations in order to make the data a little easier to work with. You'll learn how to do all that (and more!) in this chapter, which will teach you how to transform your data using the dplyr package and a new dataset on flights departing New York City in 2013.
### Prerequisites
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### Dplyr basics
In this chapter you are going to learn the five key dplyr functions that allow you to solve vast majority of your data manipulation challenges:
In this chapter you are going to learn the five key dplyr functions that allow you to solve the vast majority of your data manipulation challenges:
* Pick observations by their values (`filter()`).
* Reorder the rows (`arrange()`).