Merge branch 'master' of github.com:hadley/r4ds

.travis.yml

@@ -9,7 +9,8 @@ addons:
     packages:
       - libxml2-dev
 
-script: ./_build.sh
+script:
+  - Rscript -e 'bookdown::render_book("index.rmd")'
 
 deploy:
   skip_cleanup: true

_build.sh

@@ -1,2 +0,0 @@
-#!/usr/bin/env Rscript
-bookdown::render_book("index.rmd")

communicate.Rmd

@@ -1,3 +1,5 @@
-# Communicate your work
+# (PART) Communicate your work {-}
+
+# Introduction
 
 Reproducible, literate code is the data science equivalent of the Scientific Report (i.e, Intro, Methods and materials, Results, Discussion).

index.rmd

@@ -7,12 +7,15 @@ url: 'http\://r4ds.had.co.nz/'
 github-repo: hadley/r4ds
 twitter-handle: hadley
 cover-image: cover.png
+site: bookdown::bookdown_site
 ---
 
-# Welcome
+# Welcome {-}
 
-This is the book site for __"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. 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. You'll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You'll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualizing, and exploring data. (__R for Data Science__ was formerly called __Data Science with R__ in __Hands-On Programming with R__)
+This is the website for __"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. 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. You'll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You'll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualizing, and exploring data. 
 
-To be published by O'Reilly in July 2016. 
+To be published by O'Reilly in late 2016. 
 
 <img src="cover.png" width="250" height="328" alt="Cover image" />
+
+(R for Data Science was formerly called Data Science with R in Hands-On Programming with R)

program.Rmd

@@ -1,4 +1,6 @@
-# Programming
+# (PART) Programming {-}
+
+# Introduction
 
 Code is a tool of communication, not just to the computer, but to other people. This is important because every project you undertake is fundamentally collaborative. Even if you're not working with other people, you'll definitely be working with future-you. You want to write clear code so that future-you doesn't curse present-you when you look at a project again after several months have passed.
 

r4ds.Rproj

@@ -15,5 +15,4 @@ LaTeX: XeLaTeX
 AutoAppendNewline: Yes
 StripTrailingWhitespace: Yes
 
-BuildType: Custom
-CustomScriptPath: _build.sh
+BuildType: Website

r4ds.css

@@ -2,3 +2,14 @@
   opacity: 1;
   text-align: left;
 }
+
+#header .title {
+  margin-bottom: 0em;
+}
+#header h4.author {
+  margin: 0;
+  color: #666;
+}
+#header h4.author em {
+  font-style: normal;
+}

science.Rmd

@@ -1,3 +1,5 @@
-# Do science with data
+# (PART) Do science with data {-}
+
+# Introduction
 
 The scientific method guides data science. Data science solves known problems with the scientific method.

understand.Rmd

@@ -1,3 +1,5 @@
-# Understand your data
+# (PART) Understand your data {-}
+
+# Introduction
 
 Data poses a cognitive problem; Data comprehension is a skill.

work.Rmd

@@ -1,4 +1,6 @@
-# Work with your data
+# (PART) Work with your data {-}
+
+# Introduction
 
 With data, the relationships between values matter as much as the values themselves. Tidy data encodes those relationships.