Creating an Efficient data analysis workflow part 2. Filling in missing values error

Working on the guided project: Creating an efficient Data Analysis Workflow part 2. Ran into and issue when trying to fill in the missing purchase values with a the average of that same column. The code is very simple and straightforward so why is this happening?

Remove all of the missing values from the user_submitted_review column

complete_sales <- sales >
filter(user_submitted_review != “NA”)

Calculate average purchase quantity

purchase_mean <- complete_sales >
filter(total_purchased != “NA”) >
summarise(mean(total_purchased))

Fill in missing values with the average

complete_sales <- complete_sales >
mutate(imputed_purchases = if_else(total_purchased == “NA”,
purchase_mean, total_purchased)
)

This is the error that appears :Error: Can’t use NA as column index with [ at positions 1, 2, 3, 4, 5, and 4110 more.