Polish programming

program.qmd

@@ -45,14 +45,13 @@ In the following three chapters, you'll learn skills that will allow you to both
 
 1.  Copy-and-paste is a powerful tool, but you should avoid doing it more than twice.
     Repeating yourself in code is dangerous because it can easily lead to errors and inconsistencies.
-    Instead, in [Chapter -@sec-functions], you'll learn how to write **functions** which let you extract out repeated code so that it can be easily reused.
+    Instead, in @sec-functions, you'll learn how to write **functions** which let you extract out repeated code so that it can be easily reused.
 
-2.  As you start to write more powerful functions, you'll need a solid grounding in R's **data structures**, provided by vectors, which we discuss in [Chapter -@sec-vectors].
-    You must master the four common atomic vectors, the three important S3 classes built on top of them, and understand the mysteries of the list and data frame.
+2.  As you start to write more powerful functions, you'll need a solid grounding in R's **data structures**, provided by vectors, which we discuss in @sec-vectors. You must master the four common atomic vectors, the three important S3 classes built on top of them, and understand the mysteries of the list and data frame.
 
 3.  Functions extract out repeated code, but you often need to repeat the same actions on different inputs.
     You need tools for **iteration** that let you do similar things again and again.
-    These tools include for loops and functional programming, which you'll learn about in [Chapter -@sec-iteration].
+    These tools include for loops and functional programming, which you'll learn about in @sec-iteration.
 
 A common theme throughout these chapters is the idea of reducing duplication in your code.
 Reducing code duplication has three main benefits:
@@ -65,12 +64,12 @@ Reducing code duplication has three main benefits:
 3.  You're likely to have fewer bugs because each line of code is used in more places.
 
 One tool for reducing duplication is functions, which reduce duplication by identifying repeated patterns of code and extract them out into independent pieces that can be easily reused and updated.
-Another tool for reducing duplication is **iteration**, which helps you when you need to do the same thing to multiple inputs: repeating the same operation on different columns, or on different datasets.
+Another tool for reducing duplication is iteration, which helps you when you need to do the same thing to multiple inputs: repeating the same operation on different columns, or on different datasets.
 
 ## Learning more
 
-The goal of these chapters is to teach you the minimum about programming that you need to practice data science, which turns out to be a reasonable amount.
-Once you have mastered the material in this book, we strongly believe you should invest further in your programming skills.
+The goal of these chapters is to teach you the minimum about programming that you need to practice data science.
+Once you have mastered the material in this book, we strongly believe you should continue to invest in your programming skills.
 Learning more about programming is a long-term investment: it won't pay off immediately, but in the long term it will allow you to solve new problems more quickly, and let you reuse your insights from previous problems in new scenarios.
 
 To learn more you need to study R as a programming language, not just an interactive environment for data science.
@@ -84,4 +83,4 @@ We have written two books that will help you do so:
 -   [*Advanced R*](https://adv-r.hadley.nz/) by Hadley Wickham.
     This dives into the details of R the programming language.
     This is a great place to start if you have existing programming experience.
-    It's also a great next step once you've internalised the ideas in these chapters.
+    It's also a great next step once you've internalized the ideas in these chapters.