You can use the drop_na() function from the tidyr package in R to drop rows with missing values in a data frame.
There are three common ways to use this function:
Method 1: Drop Rows with Missing Values in Any Column
df %>% drop_na()
Method 2: Drop Rows with Missing Values in Specific Column
df %>% drop_na(col1)
Method 3: Drop Rows with Missing Values in One of Several Specific Columns
df %>% drop_na(c(col1, col2))
The following examples show how to use each of these methods in practice with the following data frame:
#create data frame df <- data.frame(points=c(10, NA, 15, 15, 14, 16), assists=c(4, NA, 4, NA, 9, 3), rebounds=c(NA, 5, 10, 7, 7, NA)) #view data frame df points assists rebounds 1 10 4 NA 2 NA NA 5 3 15 4 10 4 15 NA 7 5 14 9 7 6 16 3 NA
Example 1: Drop Rows with Missing Values in Any Column
The following code shows how to use drop_na() to drop rows with missing values in any column:
library(tidyr)
#drop rows with missing values in any column
df %>% drop_na()
points assists rebounds
1 15 4 10
2 14 9 7
The only rows left are the ones with no missing values in any column.
Example 2: Drop Rows with Missing Values in Specific Column
The following code shows how to use drop_na() to drop rows with missing values in the rebounds column:
library(tidyr)
#drop rows with missing values in rebounds column
df %>% drop_na(rebounds)
points assists rebounds
1 NA NA 5
2 15 4 10
3 15 NA 7
4 14 9 7
The only rows left are the ones with no missing values in the rebounds column.
Example 3: Drop Rows with Missing Values in One of Several Specific Columns
The following code shows how to use drop_na() to drop rows with missing values in the points or assists columns:
library(tidyr)
#drop rows with missing values in the points or assists columns
df %>% drop_na(c(points, assists))
points assists rebounds
1 10 4 NA
2 15 4 10
3 14 9 7
4 16 3 NA
The only rows left are the ones with no missing values in the points or assists columns.
Note: You can find the complete online documentation for the drop_na() method here.
Additional Resources
The following tutorials explain how to perform other common tasks in R:
How to Retrieve Row Numbers in R
How to Append Rows to a Data Frame in R
How to Apply Function to Each Row in Data Frame in R