How to Use summarize in dplyr: Simple Guide with Examples

In dplyr, use summarize() to create summary statistics by applying functions like mean() or sum() to columns. It reduces data to one row per group or overall when used with group_by() or alone.

Syntax

The basic syntax of summarize() is:

• summarize(data, new_column = summary_function(column))
• data: your data frame or tibble
• new_column: name for the summary result
• summary_function(column): function like mean(), sum(), n(), etc.

When combined with group_by(), it summarizes data by groups.

r

library(dplyr)

# Basic syntax
summarize(data, new_column = mean(column))

Example

This example shows how to calculate the average miles per gallon (mpg) for each number of cylinders (cyl) in the built-in mtcars dataset.

r

library(dplyr)

result <- mtcars %>%
  group_by(cyl) %>%
  summarize(avg_mpg = mean(mpg))

print(result)

Output

  cyl avg_mpg
1   4  26.66364
2   6  19.74286
3   8  15.10000

Common Pitfalls

Common mistakes include:

• Forgetting to use group_by() when you want summaries by group, which results in a single summary for the whole data.
• Using column names without summarize() inside group_by() which does not summarize.
• Not loading dplyr library before using summarize().

r

library(dplyr)

# Wrong: no group_by, so only one summary
mtcars %>%
  summarize(avg_mpg = mean(mpg))

# Right: with group_by to get group summaries
mtcars %>%
  group_by(cyl) %>%
  summarize(avg_mpg = mean(mpg))

Output

  avg_mpg
1 20.09062

  cyl avg_mpg
1   4  26.66364
2   6  19.74286
3   8  15.10000

Quick Reference

Function	Description	Example
mean()	Calculates average	summarize(data, avg = mean(column))
sum()	Calculates total sum	summarize(data, total = sum(column))
n()	Counts rows	summarize(data, count = n())
median()	Calculates median	summarize(data, med = median(column))
max()	Finds maximum value	summarize(data, max_val = max(column))

Key Takeaways

Use summarize() to create summary statistics from data frames.

Combine summarize() with group_by() to get summaries by groups.

Always load the dplyr package before using summarize().

Common summary functions include mean(), sum(), and n().

Without group_by(), summarize() returns one summary for the entire dataset.