Mention distinct

data-transform.qmd

@@ -96,6 +96,7 @@ Let's dive in!
 
 The most important verbs that operate on rows are `filter()`, which changes which rows are present without changing their order, and `arrange()`, which changes the order of the rows without changing which are present.
 Both functions only affect the rows, and the columns are left unchanged.
+We'll also discuss `distinct()` which finds rows with unique values but unlike `arrange()` and `filter()` it can also optionally modify the columns.
 
 ### `filter()`
 
@@ -197,6 +198,23 @@ flights |>
   arrange(desc(arr_delay))
 ```
 
+### `distinct()`
+
+`distinct()` finds all the unique rows in a dataset, so in a technical sense, it primarily operates on the rows.
+Most of the time, however, you'll want to the distinct combination of some variables, so you can also optionally supply column names:
+
+```{r}
+# This would remove any duplicate rows if there were any
+flights |> 
+  distinct()
+
+# This finds all unique origin and destination pairs.
+flights |> 
+  distinct(origin, dest)
+```
+
+Note that if you want to find the number of duplicates, or rows that weren't duplicated, you're better off swapping `distinct()` for `count()` and then filtering as needed.
+
 ### Exercises
 
 1.  Find all flights that
@@ -213,10 +231,12 @@ flights |>
 
 3.  Sort `flights` to find the fastest flights (Hint: try sorting by a calculation).
 
-4.  Which flights traveled the farthest?
+4.  Was there a flight on every day of 2017?
-    Which traveled the shortest?
 
-5.  Does it matter what order you used `filter()` and `arrange()` in if you're using both?
+5.  Which flights traveled the farthest distance?
+    Which traveled the least distance?
+
+6.  Does it matter what order you used `filter()` and `arrange()` in if you're using both?
     Why/why not?
     Think about the results and how much work the functions would have to do.
 
@@ -224,6 +244,7 @@ flights |>
 
 There are four important verbs that affect the columns without changing the rows: `mutate()`, `select()`, `rename()`, and `relocate()`.
 `mutate()` creates new columns that are functions of the existing columns; `select()`, `rename()`, and `relocate()` change which columns are present, their names, or their positions.
+We'll also discuss `pull()` since it allows you to get a column out of data frame.
 
 ### `mutate()` {#sec-mutate}