You can use the drop_na() function from the 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

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 pointsorassists columns.

Note: You can find the complete online documentation for the drop_na() method .