parent
f023ef409e
commit
8e84a7890f
|
@ -16,7 +16,7 @@ library(tibble)
|
|||
|
||||
## Creating tibbles {#tibbles}
|
||||
|
||||
Almost all of the functions that you'll use in this book produce tibbles as tibbles are one of the unifying features of the tidyverse. Most other R packages use regular data frames, so you might want to coerce a data frame to a tibble. You can do that with `as_tibble()`:
|
||||
Almost all of the functions that you'll use in this book produce tibbles, as tibbles are one of the unifying features of the tidyverse. Most other R packages use regular data frames, so you might want to coerce a data frame to a tibble. You can do that with `as_tibble()`:
|
||||
|
||||
```{r}
|
||||
as_tibble(iris)
|
||||
|
|
|
@ -23,7 +23,7 @@ This part of the book proceeds as follows:
|
|||
You'll learn the underlying principles, and how to get your data into a
|
||||
tidy form.
|
||||
|
||||
Data wrangling also encompasses data transformation, which you've already learn a little about. Now we'll focus on new skills for three specific types of data you will frequently encounter in practice:
|
||||
Data wrangling also encompasses data transformation, which you've already learned a little about. Now we'll focus on new skills for three specific types of data you will frequently encounter in practice:
|
||||
|
||||
* [Relational data] will give you tools for working with multiple
|
||||
interrelated datasets.
|
||||
|
|
Loading…
Reference in New Issue