sum_n() computes row sums from a data.frame or matrix, handling missing values (NAs) automatically.
Row-wise sums are calculated across selected numeric columns, with an optional condition on the minimum number (or proportion) of valid (non-missing) values required for a row to be included.
Non-numeric columns are excluded automatically and reported.
Usage
sum_n(
data = NULL,
select = dplyr::everything(),
exclude = NULL,
min_valid = NULL,
digits = NULL,
regex = FALSE,
verbose = FALSE
)Arguments
- data
A
data.frameormatrix.- select
Columns to include. If
regex = FALSE, use tidyselect syntax (default:dplyr::everything()). Ifregex = TRUE, provide a regular expression pattern (character string).- exclude
Columns to exclude (default:
NULL).- min_valid
Minimum number of valid (non-NA) values required per row. If a proportion, it's applied to the number of selected columns.
- digits
Optional number of decimal places to round the result.
- regex
If
TRUE, theselectargument is treated as a regular expression. IfFALSE, uses tidyselect helpers.- verbose
If
TRUE, prints a message about processing.
Examples
library(dplyr)
# Create a simple numeric data frame
df <- tibble(
var1 = c(10, NA, 30, 40, 50),
var2 = c(5, NA, 15, NA, 25),
var3 = c(NA, 30, 20, 50, 10)
)
# Compute row-wise sums (all values must be valid by default)
sum_n(df)
#> [1] NA NA 65 NA 85
# Require at least 2 valid (non-NA) values per row
sum_n(df, min_valid = 2)
#> [1] 15 NA 65 90 85
# Require at least 50% valid (non-NA) values per row
sum_n(df, min_valid = 0.5)
#> [1] 15 NA 65 90 85
# Round the results to 1 decimal
sum_n(df, digits = 1)
#> [1] NA NA 65 NA 85
# Select specific columns
sum_n(df, select = c(var1, var2))
#> [1] 15 NA 45 NA 75
# Select specific columns using a pipe
df |> select(var1, var2) |> sum_n()
#> [1] 15 NA 45 NA 75
# Exclude a column
sum_n(df, exclude = "var3")
#> [1] 15 NA 45 NA 75
# Select columns ending with "1"
sum_n(df, select = ends_with("1"))
#> [1] 10 NA 30 40 50
# Use with native pipe
df |> sum_n(select = starts_with("var"))
#> [1] NA NA 65 NA 85
# Use inside dplyr::mutate()
df |> mutate(sum_score = sum_n(min_valid = 2))
#> # A tibble: 5 × 4
#> var1 var2 var3 sum_score
#> <dbl> <dbl> <dbl> <dbl>
#> 1 10 5 NA 15
#> 2 NA NA 30 NA
#> 3 30 15 20 65
#> 4 40 NA 50 90
#> 5 50 25 10 85
# Select columns directly inside mutate()
df |> mutate(sum_score = sum_n(select = c(var1, var2), min_valid = 1))
#> # A tibble: 5 × 4
#> var1 var2 var3 sum_score
#> <dbl> <dbl> <dbl> <dbl>
#> 1 10 5 NA 15
#> 2 NA NA 30 NA
#> 3 30 15 20 45
#> 4 40 NA 50 40
#> 5 50 25 10 75
# Select columns before mutate
df |> select(var1, var2) |> mutate(sum_score = sum_n(min_valid = 1))
#> # A tibble: 5 × 3
#> var1 var2 sum_score
#> <dbl> <dbl> <dbl>
#> 1 10 5 15
#> 2 NA NA NA
#> 3 30 15 45
#> 4 40 NA 40
#> 5 50 25 75
# Show verbose message
df |> mutate(sum_score = sum_n(min_valid = 2, digits = 1, verbose = TRUE))
#> sum_n(): Row sums computed with min_valid = 2, regex = FALSE
#> # A tibble: 5 × 4
#> var1 var2 var3 sum_score
#> <dbl> <dbl> <dbl> <dbl>
#> 1 10 5 NA 15
#> 2 NA NA 30 NA
#> 3 30 15 20 65
#> 4 40 NA 50 90
#> 5 50 25 10 85
# Add character and grouping columns
df_mixed <- mutate(df,
name = letters[1:5],
group = c("A", "A", "B", "B", "A")
)
df_mixed
#> # A tibble: 5 × 5
#> var1 var2 var3 name group
#> <dbl> <dbl> <dbl> <chr> <chr>
#> 1 10 5 NA a A
#> 2 NA NA 30 b A
#> 3 30 15 20 c B
#> 4 40 NA 50 d B
#> 5 50 25 10 e A
# Non-numeric columns are ignored
sum_n(df_mixed)
#> sum_n(): Ignored non-numeric columns: name, group
#> [1] NA NA 65 NA 85
# Use inside mutate with mixed data
df_mixed |> mutate(sum_score = sum_n(select = starts_with("var")))
#> # A tibble: 5 × 6
#> var1 var2 var3 name group sum_score
#> <dbl> <dbl> <dbl> <chr> <chr> <dbl>
#> 1 10 5 NA a A NA
#> 2 NA NA 30 b A NA
#> 3 30 15 20 c B 65
#> 4 40 NA 50 d B NA
#> 5 50 25 10 e A 85
# Use everything(), but exclude known non-numeric
sum_n(df_mixed, select = everything(), exclude = "group")
#> sum_n(): Ignored non-numeric columns: name
#> [1] NA NA 65 NA 85
# Select columns using regex
sum_n(df_mixed, select = "^var", regex = TRUE)
#> [1] NA NA 65 NA 85
sum_n(df_mixed, select = "ar", regex = TRUE)
#> [1] NA NA 65 NA 85
# Apply to a subset of rows
df_mixed[1:3, ] |> sum_n(select = starts_with("var"))
#> [1] NA NA 65
# Store the result in a new column
df_mixed$sum_score <- sum_n(df_mixed, select = starts_with("var"))
df_mixed
#> # A tibble: 5 × 6
#> var1 var2 var3 name group sum_score
#> <dbl> <dbl> <dbl> <chr> <chr> <dbl>
#> 1 10 5 NA a A NA
#> 2 NA NA 30 b A NA
#> 3 30 15 20 c B 65
#> 4 40 NA 50 d B NA
#> 5 50 25 10 e A 85
# With a numeric matrix
mat <- matrix(c(1, 2, NA, 4, 5, NA, 7, 8, 9), nrow = 3, byrow = TRUE)
mat
#> [,1] [,2] [,3]
#> [1,] 1 2 NA
#> [2,] 4 5 NA
#> [3,] 7 8 9
mat |> sum_n(min_valid = 2)
#> [1] 3 9 24