Second crack and 2e structure

_bookdown.yml

@@ -11,24 +11,27 @@ rmd_files: [
   "data-visualize.Rmd",
   "workflow-basics.Rmd",
   "data-transform.Rmd",
-  "data-import.Rmd",
   "data-tidy.Rmd",
+  "data-import.Rmd",
   "workflow-scripts.Rmd",
   "EDA.Rmd",
   "workflow-projects.Rmd",
 
-  "wrangle.Rmd",
+  "data-types.Rmd",
   "tibble.Rmd",
-  "tidy.Rmd",
-  "rectangle.Rmd",
   "relational-data.Rmd",
-  "list-columns.Rmd",
-  "column-wise.Rmd",
-  "row-wise.Rmd",
+  "logicals-numbers.Rmd",
+  "vector-tools.Rmd",
+  "missing-values.Rmd",
   "strings.Rmd",
   "factors.Rmd",
   "datetimes.Rmd",
 
+  "wrangle.Rmd",
+  "column-wise.Rmd",
+  "list-columns.Rmd",
+  "rectangle.Rmd",
+
   "import.Rmd",
   "import-rectangular.Rmd",
   "import-spreadsheets.Rmd",

data-types.Rmd

@@ -0,0 +1,29 @@
+# (PART) Data types {.unnumbered}
+
+# Introduction {#data-types-intro}
+
+In this part of the book, you'll learn about data types, ...
+
+<!--# TO DO: Add a diagram? -->
+
+This part of the book proceeds as follows:
+
+-   In Chapter \@ref(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".
+
+Data wrangling also encompasses data transformation, which you've already learned a little about.
+Now we'll focus on new skills for specific types of data you will frequently encounter in practice:
+
+-   Chapter \@ref(relational-data) will give you tools for working with multiple interrelated datasets.
+
+<!--# TO DO: Something about logicals and numbers -->
+
+<!--# TO DO: Something about general vector tools -->
+
+<!--# TO DO: Something about missing values -->
+
+-   Chapter \@ref(strings) will give you tools for working with strings and introduce regular expressions, a powerful tool for manipulating strings.
+
+-   Chapter \@ref(factors) will introduce factors -- how R stores categorical data.
+    They are used when a variable has a fixed set of possible values, or when you want to use a non-alphabetical ordering of a string.
+
+-   Chapter \@ref(dates-and-times) will give you the key tools for working with dates and date-times.

index.Rmd

@@ -13,7 +13,7 @@ documentclass: book
 
 # Welcome {.unnumbered}
 
-<a href="http://amzn.to/2aHLAQ1"><img src="cover.png" alt="Buy from amazon" class="cover" width="250" height="375"/></a> This is the website for the work-in-progress 2nd edition of **"R for Data Science"**. This book will teach you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it.
+[![Buy from amazon](cover.png){.cover width="250"}](http://amzn.to/2aHLAQ1) This is the website for the work-in-progress 2nd edition of **"R for Data Science"**. This book will teach you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it.
 <!--# TO DO: Should "model it" stay here? Omitted? Mentioned with an explanation as to where to go for modeling? --> In this book, you will find a practicum of skills for data science.
 Just as a chemist learns how to clean test tubes and stock a lab, you'll learn how to clean data and draw plots---and many other things besides.
 These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R.

logicals-numbers.Rmd

@@ -0,0 +1,3 @@
+# Logicals and numbers
+
+## Introduction

missing-values.Rmd

@@ -0,0 +1,3 @@
+# Missing values
+
+## Introduction

rectangle.Rmd

@@ -1,4 +1,4 @@
-# Rectangle data
+# Rectangling data
 
 ## Introduction
 

row-wise.Rmd

@@ -1,16 +0,0 @@
-# Row-wise operations
-
-## Introduction
-
-<!--# TO DO: Write introduction. -->
-
-### Prerequisites
-
-In this chapter we'll continue using dplyr.
-dplyr is a member of the core tidyverse.
-
-```{r setup, message = FALSE}
-library(tidyverse)
-```
-
-<!--# TO DO: Write chapter around rowwise, etc. -->

vector-tools.Rmd

@@ -0,0 +1,3 @@
+# General vector tools
+
+## Introduction

whole-game.Rmd

@@ -17,6 +17,9 @@ In this part of the book you will learn some useful tools that have an immediate
 
 -   Visualisation alone is typically not enough, so in Chapter \@ref(data-transform) you'll learn the key verbs that allow you to select important variables, filter out key observations, create new variables, and compute summaries.
 
+-   In Chapter \@ref(data-tidy), 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.
+
 -   Before you can transform and visualise your data, you need to first get your data into R.
     In Chapter \@ref(data-import) you'll learn the basics of getting plain-text rectangular data into R.