[dplyr] Why is my group_by() and summarise() not returning one row per group?

Hey everyone,

I'm trying to learn dplyr and I'm stuck on what seems like a simple problem. I have a data frame sales_data with columns for product_category, region, and sales_total.

# Sample Data
sales_data <- data.frame(
  product_category = c("Electronics", "Clothing", "Electronics", "Books", "Clothing"),
  region = c("North", "North", "South", "South", "West"),
  sales_total = c(1200, 300, 800, 150, 450)
)

I want to calculate the total sales for each product_category. I thought this code would work, but it's just returning the same number of rows as my original data frame.

library(dplyr)

sales_data %>%
  group_by(product_category) %>%
  mutate(total_sales = sum(sales_total))

What am I doing wrong? I expected to get one row for "Electronics", one for "Clothing", and one for "Books". Thanks in advance!

Here is another answer. It isn't the best one.

That's a very common mix-up when you're starting out. You're looking for the summarise() function, not mutate().

mutate() adds a new column to the existing data frame. When you combine it with group_by(), it calculates the value for each group and then repeats that value for every row within that group.

summarise() (or summarize()) collapses each group into a single row.

This should give you the output you want:

sales_data %>%
  group_by(product_category) %>%
  summarise(total_sales = sum(sales_total))

# # A tibble: 3 × 2
#   product_category total_sales
#   <chr>                  <dbl>
# 1 Books                    150
# 2 Clothing                 750
# 3 Electronics             2000

Hope that helps!