How to Remove Rows with NA Values Using dplyr


You can use the following methods from the dplyr package to remove rows with NA values:

Method 1: Remove Rows with NA Values in Any Column

library(dplyr)

#remove rows with NA value in any column
df %>%
  na.omit()

Method 2: Remove Rows with NA Values in Certain Columns

library(dplyr)

#remove rows with NA value in 'col1' or 'col2'
df %>%
  filter_at(vars(col1, col2), all_vars(!is.na(.)))

Method 3: Remove Rows with NA Values in One Specific Column

library(dplyr)

#remove rows with NA value in 'col1'
df %>%
  filter(!is.na(col1))

The following examples show how to use these methods in practice with the following data frame:

#create data frame with some missing values
df <- data.frame(team=c('A', 'A', 'B', 'B', 'C'),
                 points=c(99, 90, 86, 88, NA),
                 assists=c(33, NA, 31, 39, 34),
                 rebounds=c(NA, 28, 24, 24, 28))

#view data frame
df

  team points assists rebounds
1    A     99      33       NA
2    A     90      NA       28
3    B     86      31       24
4    B     88      39       24
5    C     NA      34       28

Method 1: Remove Rows with NA Values in Any Column

The following code shows how to remove rows with NA values in any column of the data frame:

library(dplyr)

#remove rows with NA value in any column
df %>%
  na.omit()

  team points assists rebounds
3    B     86      31       24
4    B     88      39       24

The only two rows that are left are the ones without any NA values in any column.

Method 2: Remove Rows with NA Values in Certain Columns

The following code shows how to remove rows with NA values in any column of the data frame:

library(dplyr)

#remove rows with NA value in 'points' or 'assists' columns
df %>%
  filter_at(vars(points, assists), all_vars(!is.na(.)))

  team points assists rebounds
1    A     99      33       NA
2    B     86      31       24
3    B     88      39       24

The only rows left are the ones without any NA values in the ‘points’ or ‘assists’ columns.

Method 3: Remove Rows with NA Values in One Specific Column

The following code shows how to remove rows with NA values in one specific column of the data frame:

library(dplyr)

#remove rows with NA value in 'points' column
df %>%
  filter(!is.na(points))

  team points assists rebounds
1    A     99      33       NA
2    A     90      NA       28
3    B     86      31       24
4    B     88      39       24

The only rows left are the ones without any NA values in the ‘points’ column.

Additional Resources

The following tutorials explain how to perform other common operations using dplyr:

dplyr: How to Filter Rows that Contain Certain String
dplyr: How to Replace NA Values with Zero
dplyr: How to Use a “not in” Filter

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