How To Use Apply in R

The apply function lets you execute another function across a given dimension of a multidimensional data object like a data frame, matrix or array. It provides a quick way to run a function on every column or every row of a data frame, without having to write a custom for loop.

Code used in this code clip:

# Apply a function across the columns of a data frame

apply(X = mtcars, # data object
FUN = median, # function to apply
MARGIN = 2) # axis to apply to. 1 = rows, 2 = columns

# Apply a function across the rows of a data frame

stat_readout ＜- function(x){
return(paste(x["cyl"], "cylindar car with",
x["mpg"], "mpg, weighing", x["wt"] * 1000, "pounds."))
}

apply(X = mtcars, # data object
FUN = stat_readout, # function to apply
MARGIN = 1) # axis to apply to. 1 = rows, 2 = columns

# Function with additional arguments
stat_readout_custom ＜- function(x, args){
readout ＜- paste(x["cyl"], "cylindar car with")
for (stat in args){
readout ＜- paste(readout, "and", x[stat], stat)
}
return(readout)
}

apply(X = mtcars, # data object
FUN = stat_readout_custom, # function to apply
MARGIN = 1, # axis to apply to
args = c("mpg", "wt")) # additional arguments

* Note: YouTube does not allow greater than or less than symbols in the text description, so the code above will not be exactly the same as the code shown in the video! For R that means I may use = for assignment and the special Unicode large ＜ and ＞ symbols in place of the standard sized ones for dplyr pipes and comparisons. These special symbols should work as expected for R code on Windows, but may need to be replaced with standard greater than and less than symbols for other operating systems.

[bridgettsmith]

Thank you for the video, and explaining why we might want to use apply instead of a for loop

[homataha]

you could have use lapply as well right? for the first example