From 24067c751315115c2e6d7ea2c2d030f522545b20 Mon Sep 17 00:00:00 2001 From: hadley Date: Thu, 11 Aug 2016 08:41:07 -0500 Subject: [PATCH] Wrangle proofing --- wrangle.Rmd | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/wrangle.Rmd b/wrangle.Rmd index 4b48023..4c15a76 100644 --- a/wrangle.Rmd +++ b/wrangle.Rmd @@ -2,34 +2,34 @@ # Introduction {#wrangle-intro} -In this part of the book, you'll learn about data wrangling, the art of getting your data into R in a useful form. Data wrangling encompasses three main pieces: +In this part of the book, you'll learn about data wrangling, the art of getting your data into R in a useful form for visualisation and modelling. Data wrangling is very important: without it you can't work with your own data! There are three main parts to data wrangling: ```{r echo = FALSE, out.width = "75%"} knitr::include_graphics("diagrams/data-science-wrangle.png") ``` -Data wrangling is import because it allows you to work with your own data. You'll learn: +This part of the book proceeds as follows: * 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". -* In [data import], you'll learn the art of data import: how to get your - data from 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. +* In [data import], you'll learn how to get your data from 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. * In [tidy data], you'll learn about tidy data, a consistent way of storing your data that makes transformation, visualisation, and modelling easier. + You'll learn the underlying principles, and how to get your data into a + tidy form. -Data wrangling also encompasses data transformation. You've already learned the basics, and now you'll learn new skills for specific types of data: +Data wrangling also encompasses data transformation, which you've already learn a little about. Now we'll focus new skills for three specific types of data you will frequently encounter in practice: * [Dates and times] will give you the key tools for working with - dates, and date-times. + 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. -