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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