How to Use drop_na in tidyr to Remove Missing Values in R

Use drop_na() from the tidyr package in R to remove rows containing missing values (NA) from a data frame. You can apply it to all columns or specify particular columns to check for missing values.

Syntax

The basic syntax of drop_na() is simple. You pass a data frame as the first argument. Optionally, you can specify one or more column names to only remove rows where those columns have missing values.

• drop_na(data): Removes rows with any NA in any column.
• drop_na(data, column1, column2): Removes rows with NA only in specified columns.

r

drop_na(data, ...)

Example

This example shows how to remove rows with missing values from a data frame using drop_na(). It first removes rows with any NA, then only those with NA in the age column.

r

library(tidyr)
library(dplyr)

# Create example data frame
people <- tibble(
  name = c("Alice", "Bob", "Carol", "David"),
  age = c(25, NA, 30, 22),
  city = c("NY", "LA", NA, "Chicago")
)

# Remove rows with any NA
clean_any <- drop_na(people)

# Remove rows with NA only in 'age'
clean_age <- drop_na(people, age)

clean_any
clean_age

Output

# A tibble: 2 × 3
  name    age city   
  <chr> <dbl> <chr>  
1 Alice    25 NY     
2 David    22 Chicago

# A tibble: 3 × 3
  name    age city   
  <chr> <dbl> <chr>  
1 Alice    25 NY     
2 Carol    30 NA     
3 David    22 Chicago

Common Pitfalls

One common mistake is expecting drop_na() to remove rows with missing values only in some columns without specifying those columns. By default, it removes rows with NA in any column. Another pitfall is forgetting to load the tidyr package before using drop_na().

r

library(tidyr)

# Wrong: expecting to remove NA only in 'age' but not specifying it
people <- tibble(
  name = c("Alice", "Bob", "Carol"),
  age = c(25, NA, 30),
  city = c("NY", "LA", NA)
)

# This removes rows with NA in any column
drop_na(people)

# Correct: specify 'age' to remove rows with NA only in 'age'
drop_na(people, age)

Output

# A tibble: 1 × 3
  name    age city 
  <chr> <dbl> <chr>
1 Alice    25 NY   

# A tibble: 2 × 3
  name    age city 
  <chr> <dbl> <chr>
1 Alice    25 NY   
2 Carol    30 NA  

Quick Reference

Usage	Description
drop_na(data)	Remove rows with any missing values in all columns
drop_na(data, col1, col2)	Remove rows with missing values only in specified columns
Requires tidyr package	Load with library(tidyr) before use
Returns a tibble	Original data frame without rows containing NA as specified

Key Takeaways

Use drop_na() to remove rows with missing values from data frames in R.

Specify columns in drop_na() to target missing values only in those columns.

Always load the tidyr package with library(tidyr) before using drop_na().

drop_na() returns a new data frame without modifying the original by default.

By default, drop_na() removes rows with NA in any column if no columns are specified.