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Tweaking wrangle intro

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hadley 2016-07-24 14:53:59 -05:00
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wrangle.Rmd
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@ -8,23 +8,28 @@ In this part of the book, you'll learn about data wrangling, the art of getting
knitr::include_graphics("diagrams/data-science-wrangle.png")
```
* In [data import], you'll learn the art of data import: how to get your data
off of disk and into R.
Data wrangling is import because it allows you to work with your own data. You'll learn:
* In [tidy data], you'll learn about tidy data, a consistent way of storing your
data that makes transformation, visualiation, and modelling easier.
* In [tibbles], you'll learn about the variant of the data frame that we use
in this book: the __tibble__. You'll learn what makes them different
from regular data frames, and how you can construct them "by hand".
* You've already learned the basics of data transformation. In this part of the
book we'll dive deeper into tools useful for specific types of data:
* In [data import], you'll learn the art of data import: how to get your
data off of disk and into R. We'll focus on plain-text rectangular
formats, but will give you pointers to packages that help with other
types of data.
* [Dates and times] will give you the key tools for working with
dates, and date times.
* [Strings] will introduce regular expressions, a powerful tool for
manipulating strings.
* [Relational data] will give you tools for working with multiple
interrelated datasets.
* In [tidy data], you'll learn about tidy data, a consistent way of storing
your data that makes transformation, visualisation, and modelling easier.
Before we get to those chapters we'll take a brief discussion to discuss the "tibble" in more detail, in [tibbles].
Data wrangling also encompasses data transformation. You've already learned the basics, and now you'll learn new skills for specific types of data:
* [Dates and times] will give you the key tools for working with
dates, and date times.
* [Strings] will introduce regular expressions, a powerful tool for
manipulating strings.
* [Relational data] will give you tools for working with multiple
interrelated datasets.