How to Sum Across Multiple Columns Using dplyr

You can use the following methods to sum values across multiple columns of a data frame using dplyr:

Method 1: Sum Across All Columns

df %>%
  mutate(sum = rowSums(., na.rm=TRUE))

Method 2: Sum Across All Numeric Columns

df %>%
  mutate(sum = rowSums(across(where(is.numeric)), na.rm=TRUE))

Method 3: Sum Across Specific Columns

df %>%
  mutate(sum = rowSums(across(c(col1, col2))))

The following examples show how to each method with the following data frame that contains information about points scored by various basketball players during different games:

#create data frame
df frame(game1=c(22, 25, 29, 13, 22, 30),
                 game2=c(12, 10, 6, 6, 8, 11),
                 game3=c(NA, 15, 15, 18, 22, 13))

#view data frame
df

  game1 game2 game3
1    22    12    NA
2    25    10    15
3    29     6    15
4    13     6    18
5    22     8    22
6    30    11    13

Example 1: Sum Across All Columns

The following code shows how to calculate the sum of values across all columns in the data frame:

library(dplyr)

#sum values across all columns
df %>%
  mutate(total_points = rowSums(., na.rm=TRUE))

  game1 game2 game3 total_points
1    22    12    NA           34
2    25    10    15           50
3    29     6    15           50
4    13     6    18           37
5    22     8    22           52
6    30    11    13           54

Example 2: Sum Across All Numeric Columns

The following code shows how to calculate the sum of values across all numeric columns in the data frame:

library(dplyr) 

#sum values across all numeric columns
df %>%
  mutate(total_points = rowSums(across(where(is.numeric)), na.rm=TRUE))

  game1 game2 game3 total_points
1    22    12    NA           34
2    25    10    15           50
3    29     6    15           50
4    13     6    18           37
5    22     8    22           52
6    30    11    13           54

Example 3: Sum Across Specific Columns

The following code shows how to calculate the sum of values across the game1 and game2 columns only:

library(dplyr) 

#sum values across game1 and game2 only
df %>%
  mutate(first2_sum = rowSums(across(c(game1, game2))))

  game1 game2 game3 first2_sum
1    22    12    NA         34
2    25    10    15         35
3    29     6    15         35
4    13     6    18         19
5    22     8    22         30
6    30    11    13         41

Additional Resources

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

How to Remove Rows Using dplyr
How to Arrange Rows Using dplyr
How to Filter by Multiple Conditions Using dplyr