Simple one:
rbind(data, AVERAGES=colMeans(data))
[Edit] If your data.frame
contains other types than numeric
(like factor
or character
) then you could use more complicated but safer method:
rbind(data, AVERAGES=as.data.frame(lapply(data, mean)))
Simple example:
data <- data.frame(
x_Date = Sys.Date()+1:3,
x_numeric = 1:3+.1,
x_POSIXt = Sys.time()+1:3,
x_factor = factor(letters[1:3]),
x_character = letters[1:3],
x_logical = c(TRUE,FALSE,TRUE),
x_complex = 1i+1:3,
stringsAsFactors = FALSE,
row.names=paste("Row",1:3)
)
rbind(data, AVERAGES=as.data.frame(lapply(data , mean)))
# Warning in mean.default(X[[4L]], ...) :
# argument is not numeric or logical: returning NA
# Calls: rbind -> as.data.frame -> lapply -> FUN -> mean.default
# Warning in mean.default(X[[5L]], ...) :
# argument is not numeric or logical: returning NA
# Calls: rbind -> as.data.frame -> lapply -> FUN -> mean.default
# x_Date x_numeric x_POSIXt x_factor x_character x_logical x_complex
# Row 1 2010-04-21 1.1 2010-04-20 23:30:42 a a 1.000000 1+1i
# Row 2 2010-04-22 2.1 2010-04-20 23:30:43 b b 0.000000 2+1i
# Row 3 2010-04-23 3.1 2010-04-20 23:30:44 c c 1.000000 3+1i
# AVERAGES 2010-04-22 2.1 2010-04-20 23:30:43 <NA> <NA> 0.666667 2+1i
logical
column is converted to numeric, and for non-numeric columns there are NA
's