diff --git a/data-tidy.qmd b/data-tidy.qmd
index 8b1367d..9d07d38 100644
--- a/data-tidy.qmd
+++ b/data-tidy.qmd
@@ -448,7 +448,7 @@ knitr::include_graphics("diagrams/tidy-data/names-and-values.png", dpi = 270)
 ## Widening data
 
 So far we've used `pivot_longer()` to solve the common class of problems where values have ended up in column names.
-Next we'll pivot (HA HA) to `pivot_wider()`, which which makes datasets **wider** by increasing columns and reducing rows and helps when one observation is spread across multiple rows.
+Next we'll pivot (HA HA) to `pivot_wider()`, which makes datasets **wider** by increasing columns and reducing rows and helps when one observation is spread across multiple rows.
 This seems to arise less commonly in the wild, but it does seem to crop up a lot when dealing with governmental data.
 
 We'll start by looking at `cms_patient_experience`, a dataset from the Centers of Medicare and Medicaid services that collects data about patient experiences: