How to count rows by group in R

Counting rows by group is a fundamental data manipulation task.

With dplyr

The tidyverse way uses count() or group_by() with tally():

library(dplyr)

# Simple count by group
counts <- df %>%
  count(department)

# Count by multiple groups
counts <- df %>%
  count(department, status)

# Count and sort
counts <- df %>%
  count(department, sort = TRUE)

# Count with additional columns
counts <- df %>%
  count(department, gender, wt = salary, name = "total_salary")

With base R

# Using table()
dept_counts <- table(df$department)

# Using by() 
counts <- by(df$department, df$department, length)

# Using aggregate()
counts <- aggregate(rep(1, nrow(df)), by = list(department = df$department), sum)

With data.table

library(data.table)

dt <- as.data.table(df)

# Simple count by group
counts <- dt[, .N, by = department]

# Count by multiple groups
counts <- dt[, .N, by = .(department, status)]

# Count and sort
counts <- dt[, .N, by = department][order(-N)]

With table() for Frequency Tables

# Single variable
table(df$department)

# Two-way table
table(df$department, df$status)

# Proportions
prop.table(table(df$department))

Common Variations

Task	dplyr	data.table
Count all	n()	.N
Weighted count	count(wt = x)	dt[, sum(x), by = group]
Count unique	n_distinct(x)	uniqueN(x)

See Also

• group_by() — dplyr grouping
• count() — dplyr count function
• table() — Base R tabulation