Fix links

Author: thomasp85

R/guide-colorbar.R

@@ -5,8 +5,6 @@ NULL
 #'
 #' Colour bar guide shows continuous colour scales mapped onto values.
 #' Colour bar is available with `scale_fill` and `scale_colour`.
-#' For more information, see the inspiration for this function:
-#' \href{https://www.mathworks.com/help/techdoc/ref/colorbar.html}{Matlab's colorbar function}.
 #'
 #' Guides can be specified in each `scale_*` or in [guides()].
 #' `guide="legend"` in `scale_*` is syntactic sugar for

README.Rmd

@@ -22,7 +22,7 @@ knitr::opts_chunk$set(
 
 ## Overview
 
-ggplot2 is a system for declaratively creating graphics, based on [The Grammar of Graphics][gg-book]. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details. 
+ggplot2 is a system for declaratively creating graphics, based on [The Grammar of Graphics][gg-book]. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.
 
 ## Installation
 
@@ -40,7 +40,7 @@ pak::pak("tidyverse/ggplot2")
 
 ## Cheatsheet
 
-<a href="https://github.com/rstudio/cheatsheets/blob/master/data-visualization.pdf"><img src="https://raw.githubusercontent.com/rstudio/cheatsheets/master/pngs/thumbnails/data-visualization-cheatsheet-thumbs.png" width="630" height="252"/></a>  
+<a href="https://github.com/rstudio/cheatsheets/blob/master/data-visualization.pdf"><img src="https://raw.githubusercontent.com/rstudio/cheatsheets/master/pngs/thumbnails/data-visualization-cheatsheet-thumbs.png" width="630" height="252"/></a>
 
 ## Usage
 
@@ -52,7 +52,7 @@ It's hard to succinctly describe how ggplot2 works because it embodies a deep ph
 #|  per gallon are inversely correlated."
 library(ggplot2)
 
-ggplot(mpg, aes(displ, hwy, colour = class)) + 
+ggplot(mpg, aes(displ, hwy, colour = class)) +
   geom_point()
 ```
 
@@ -61,7 +61,7 @@ ggplot(mpg, aes(displ, hwy, colour = class)) +
 
 [![lifecycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html)
 
-ggplot2 is now over 10 years old and is used by hundreds of thousands of people to make millions of plots. That means, by-and-large, ggplot2 itself changes relatively little. When we do make changes, they will be generally to add new functions or arguments rather than changing the behaviour of existing functions, and if we do make changes to existing behaviour we will do them for compelling reasons. 
+ggplot2 is now over 10 years old and is used by hundreds of thousands of people to make millions of plots. That means, by-and-large, ggplot2 itself changes relatively little. When we do make changes, they will be generally to add new functions or arguments rather than changing the behaviour of existing functions, and if we do make changes to existing behaviour we will do them for compelling reasons.
 
 If you are looking for innovation, look to ggplot2's rich ecosystem of extensions. See a community maintained list at <https://exts.ggplot2.tidyverse.org/gallery/>.
 
@@ -70,25 +70,25 @@ If you are looking for innovation, look to ggplot2's rich ecosystem of extension
 If you are new to ggplot2 you are better off starting with a systematic introduction, rather than trying to learn from reading individual documentation pages. Currently, there are three good places to start:
 
 1.  The [Data Visualization][r4ds-vis] and
-    [Communication][r4ds-comm] chapters in 
+    [Communication][r4ds-comm] chapters in
     [R for Data Science][r4ds]. R for Data Science is designed to
     give you a comprehensive introduction to the
     [tidyverse](https://www.tidyverse.org), and these two chapters will
-    get you up to speed with the essentials of ggplot2 as quickly as 
+    get you up to speed with the essentials of ggplot2 as quickly as
     possible.
-    
+
 1.  If you'd like to take an online course, try
     [Data Visualization in R With ggplot2][oreilly] by Kara Woo.
-    
+
 1.  If you'd like to follow a webinar, try
-    [Plotting Anything with ggplot2](https://youtu.be/h29g21z0a68) by Thomas Lin 
+    [Plotting Anything with ggplot2](https://youtu.be/h29g21z0a68) by Thomas Lin
     Pedersen.
 
-1.  If you want to dive into making common graphics as quickly 
-    as possible, I recommend [The R Graphics Cookbook][cookbook] 
+1.  If you want to dive into making common graphics as quickly
+    as possible, I recommend [The R Graphics Cookbook][cookbook]
     by Winston Chang. It provides a set of recipes to solve common
     graphics problems.
-    
+
 If you've mastered the basics and want to learn more, read [ggplot2: Elegant Graphics for Data Analysis][ggplot2-book]. It describes the theoretical underpinnings of ggplot2 and shows you how all the pieces fit together. This book helps you understand the theory that underpins ggplot2, and will help you create new types of graphics specifically tailored to your needs.
 
 ## Getting help
@@ -104,7 +104,7 @@ There are two main places to get help with ggplot2:
 
 [community]: https://forum.posit.co/
 [ggplot2-book]: https://ggplot2-book.org
-[gg-book]: https://www.amazon.com/Grammar-Graphics-Statistics-Computing/dp/0387245448/ref=as_li_ss_tl
+[gg-book]: https://link.springer.com/book/10.1007/0-387-28695-0
 [so]: https://stackoverflow.com/questions/tagged/ggplot2?sort=frequent&pageSize=50
 [cookbook]: https://r-graphics.org
 [r4ds]: https://r4ds.hadley.nz

README.md

@@ -15,9 +15,9 @@ coverage](https://codecov.io/gh/tidyverse/ggplot2/branch/main/graph/badge.svg)](
 
 ggplot2 is a system for declaratively creating graphics, based on [The
 Grammar of
-Graphics](https://www.amazon.com/Grammar-Graphics-Statistics-Computing/dp/0387245448/ref=as_li_ss_tl).
-You provide the data, tell ggplot2 how to map variables to aesthetics,
-what graphical primitives to use, and it takes care of the details.
+Graphics](https://link.springer.com/book/10.1007/0-387-28695-0). You
+provide the data, tell ggplot2 how to map variables to aesthetics, what
+graphical primitives to use, and it takes care of the details.
 
 ## Installation
 
@@ -49,11 +49,13 @@ then add on layers (like `geom_point()` or `geom_histogram()`), scales
 ``` r
 library(ggplot2)
 
-ggplot(mpg, aes(displ, hwy, colour = class)) + 
+ggplot(mpg, aes(displ, hwy, colour = class)) +
   geom_point()
 ```
 
-<img src="man/figures/README-example-1.png" alt="Scatterplot of engine displacement versus highway miles per gallon, for 234 cars coloured by 7 'types' of car. The displacement and miles per gallon are inversely correlated."  />
+<img src="man/figures/README-example-1.png" alt="Scatterplot of engine displacement versus highway miles per
+ gallon, for 234 cars coloured by 7 'types' of car. The displacement and miles
+ per gallon are inversely correlated."  />
 
 ## Lifecycle
 

man/figures/README-example-1.png

@@ -370,7 +370,7 @@ ggplot(mpg, aes(displ, drv, fill = after_stat(density))) +
 
 ## Creating a new geom
 
-It's harder to create a new geom than a new stat because you also need to know some grid. ggplot2 is built on top of grid, so you'll need to know the basics of drawing with grid. If you're serious about adding a new geom, I'd recommend buying [R graphics](https://www.amazon.com/dp/B00I60M26G/ref=cm_sw_su_dp) by Paul Murrell. It tells you everything you need to know about drawing with grid.
+It's harder to create a new geom than a new stat because you also need to know some grid. ggplot2 is built on top of grid, so you'll need to know the basics of drawing with grid. If you're serious about adding a new geom, I'd recommend buying [R graphics](https://www.routledge.com/R-Graphics-Third-Edition/Murrell/p/book/9781498789059) by Paul Murrell. It tells you everything you need to know about drawing with grid.
 
 ### A simple geom