diff --git a/wrangle.Rmd b/wrangle.Rmd
index aa6a177..f819615 100644
--- a/wrangle.Rmd
+++ b/wrangle.Rmd
@@ -8,23 +8,28 @@ In this part of the book, you'll learn about data wrangling, the art of getting
 knitr::include_graphics("diagrams/data-science-wrangle.png")
 ```
 
-*   In [data import], you'll learn the art of data import: how to get your data 
-    off of disk and into R.
+Data wrangling is import because it allows you to work with your own data. You'll learn:
 
-*   In [tidy data], you'll learn about tidy data, a consistent way of storing your
-    data that makes transformation, visualiation, and modelling easier.
+*   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".
 
-*   You've already learned the basics of data transformation. In this part of the
-    book we'll dive deeper into tools useful for specific types of data:
+*   In [data import], you'll learn the art of data import: how to get your 
+    data off of 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.
 
-    * [Dates and times] will give you the key tools for working with 
-      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.
+*   In [tidy data], you'll learn about tidy data, a consistent way of storing
+    your data that makes transformation, visualisation, and modelling easier.
 
-Before we get to those chapters we'll take a brief discussion to discuss the "tibble" in more detail, in [tibbles].
+Data wrangling also encompasses data transformation. You've already learned the basics, and now you'll learn new skills for specific types of data:
+
+*   [Dates and times] will give you the key tools for working with 
+    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.