diff --git a/import.Rmd b/import.Rmd
index dcd9ad9..d2e7c8c 100644
--- a/import.Rmd
+++ b/import.Rmd
@@ -472,39 +472,25 @@ There are two printed outputs: the column specification generated by looking at
 problems(challenge)
 ```
 
-A good strategy is to work column by column until there are no problems remaining. Here we can see that there are a lot of parsing problems with the `x` column - there are trailing characters after the integer value. That suggests we need to use a double parser instead.
-
-To fix the call, start by copying and pasting the column specification into your original call:
-
-```{r, eval = FALSE}
-challenge <- read_csv(
-  readr_example("challenge.csv"), 
-  col_types = cols(
-    x = col_integer(),
-    y = col_character()
-  )
-)
-```
-
-Then you can tweak the type of the `x` column:
-
-```{r}
-challenge <- read_csv(
-  readr_example("challenge.csv"), 
-  col_types = cols(
-    x = col_double(),
-    y = col_character()
-  )
-)
-```
-
-That fixes the first problem, but if we look at the last few rows, you'll see that they're dates stored in a character vector:
+A good strategy is to work column by column until there are no problems remaining. Here we can see that there are a lot of parsing problems with the `y` column. If we look at the last few rows, you'll see that they're dates stored in a character vector:  
 
 ```{r}
 tail(challenge)
 ```
 
-You can fix that by specifying that `y` is a date column:
+That suggests we need to use a date parser instead. To fix the call, start by copying and pasting the column specification into your original call:
+
+```{r, eval = FALSE}
+challenge <- read_csv(
+  readr_example("challenge.csv"), 
+  col_types = cols(
+    x = col_double(),
+    y = col_logical()
+  )
+)
+```
+
+Then you can fix the type of the `y` column by specifying that `y` is a date column:
 
 ```{r}
 challenge <- read_csv(