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Calculate row (column) sums for R data.frame object

Source: R/colMeans3.R, R/rowMeans3.R
rowMeans3.Rd

Calculates the mean of each row (column) in a data.frame object, with options for handling NA values, preserving row names, and appending results to the original data.frame.

Only numeric columns are considered for calculations.

Usage

colMeans3(
  x,
  na.rm = FALSE,
  useNames = FALSE,
  silence_warnings = FALSE,
  no_check = FALSE
)

rowMeans3(
  x,
  na.rm = FALSE,
  useNames = FALSE,
  silence_warnings = FALSE,
  no_check = FALSE,
  append = FALSE
)

Arguments

x

A data.frame with at least one row and one column.

na.rm

Logical. Should NA values be removed before calculation? Default is FALSE.

useNames

Logical. Should the resulting vector preserve row (column) names from the input data.frame? Default is FALSE.

silence_warnings

Logical. Should warnings be suppressed when non-numeric columns are dropped? Default is FALSE.

no_check

Logical. Skip input validation and numeric column filtering? Default is FALSE.

append

Logical. Should the means be appended as a new column row_means instead of returning them as a vector? Default is FALSE.

Value

If append = FALSE (default), returns a numeric vector of row (column) means. If useNames = TRUE and the input has non-default row (column) names, the returned vector will preserve these names.

If append = TRUE, returns the original data.frame with an additional row_means column.

See also

colMeans3 for column-wise mean

Author

Yinchun Su

Examples

df <- data.frame(
  a = 1:5,
  b = 6:10,
  c = 11:15
)

# Basic usage
rowMeans3(df)
#> [1]  6  7  8  9 10
colMeans3(df)
#> [1]  5.00000 13.33333 21.66667

# Append means as new column
rowMeans3(df, append = TRUE)
#>   a  b  c row_means
#> 1 1  6 11         6
#> 2 2  7 12         7
#> 3 3  8 13         8
#> 4 4  9 14         9
#> 5 5 10 15        10

# Preserve row names
rownames(df) <- paste0("row", seq_len(nrow(df)))
colnames(df) <- LETTERS[seq_len(ncol(df))]
rowMeans3(df, useNames = TRUE)
#> row1 row2 row3 row4 row5 
#>    6    7    8    9   10 
colMeans3(df, useNames = TRUE)
#>        A        B        C 
#>  5.00000 13.33333 21.66667