R Apply() function on specific dataframe columns

Question

I want to use the apply function on a dataframe, but only apply the function to the last 5 columns.

B<- by(wifi,(wifi$Room),FUN=function(y){apply(y, 2, A)})

This applies A to all the columns of y

B<- by(wifi,(wifi$Room),FUN=function(y){apply(y[4:9], 2, A)})

This applies A only to columns 4-9 of y, but the total return of B strips off the first 3 columns... I still want those, I just don't want A applied to them.

wifi[,1:3]+B 

also does not do what I expected/wanted.

Swathe

The 'by' call is complicating this question. If it's relevant you should rewrite the question to clarify (what is wifi$Room?). I've ignored by in my answer below. – Stupidity

You could cbind(y[1:3], ...) to the result you are getting. – Studdard

Answer 1

Using an example data.frame and example function (just +1 to all values)

A <- function(x) x + 1
wifi <- data.frame(replicate(9,1:4))
wifi

#  X1 X2 X3 X4 X5 X6 X7 X8 X9
#1  1  1  1  1  1  1  1  1  1
#2  2  2  2  2  2  2  2  2  2
#3  3  3  3  3  3  3  3  3  3
#4  4  4  4  4  4  4  4  4  4

data.frame(wifi[1:3], apply(wifi[4:9],2, A) )
#or
cbind(wifi[1:3], apply(wifi[4:9],2, A) )

#  X1 X2 X3 X4 X5 X6 X7 X8 X9
#1  1  1  1  2  2  2  2  2  2
#2  2  2  2  3  3  3  3  3  3
#3  3  3  3  4  4  4  4  4  4
#4  4  4  4  5  5  5  5  5  5

Or even:

data.frame(wifi[1:3], lapply(wifi[4:9], A) )
#or
cbind(wifi[1:3], lapply(wifi[4:9], A) )

#  X1 X2 X3 X4 X5 X6 X7 X8 X9
#1  1  1  1  2  2  2  2  2  2
#2  2  2  2  3  3  3  3  3  3
#3  3  3  3  4  4  4  4  4  4
#4  4  4  4  5  5  5  5  5  5

Snaky

Is there a way to do this using $ to index a certain column by name instead of using [ : ] to index by column number? I tried adding colnames: colnames(wifi) = c("a", "b", "c", "d", "e", "f", "g", "h" ,"i") but any attempt at using lapply(wifi$e, 2, X) wasn't happening. – Rateable

@skotturi - you can do this like wifi[c("a","b","c")] to index multiple columns by name. – Snaky

@thelatemail,In apply(wifi[4:9],2, A),wifi[4:9] is data.frame.And apply can only used to array or matrix.Why your answer workable? – Redletter

@Redletter - that's because apply can be used on a data.frame. The data.frame will be coerced to a matrix as part of the function when apply is used. – Snaky

@thelatemail,will lose rowname or colname information? – Redletter

Answer 2

lapply is probably a better choice than apply here, as apply first coerces your data.frame to an array which means all the columns must have the same type. Depending on your context, this could have unintended consequences.

The pattern is:

df[cols] <- lapply(df[cols], FUN)

The 'cols' vector can be variable names or indices. I prefer to use names whenever possible (it's robust to column reordering). So in your case this might be:

wifi[4:9] <- lapply(wifi[4:9], A)

An example of using column names:

wifi <- data.frame(A=1:4, B=runif(4), C=5:8)
wifi[c("B", "C")] <- lapply(wifi[c("B", "C")], function(x) -1 * x)

Stupidity

A small correction: wifi <- data.frame(A=1:4, B=runif(4), C=5:8) – Bird

Could you be more explicit about how you created the [cols] vector? – Falda

@Falda you can just do cols <- c("var1", "var2") – Avionics

as alternative using dplyr avoiding the redundancy to repeat the column specification, you could do wifi[4:9] %<>% map_dbl(A) – Hearthside

@AgileBean: map is a nice alternative but I would advice using the %<>% operator. Please scroll to the end of r4ds.had.co.nz/pipes.html – Swarth

Answer 3

This task is easily achieved with the dplyr package's across functionality.

Borrowing the data structure suggested by thelatemail:

A <- function(x) x + 1
wifi <- data.frame(replicate(9,1:4))

We can indicate the columns we wish to apply the function to either by index like this:

library(dplyr)
wifi %>% 
   mutate(across(4:9, A))
#  X1 X2 X3 X4 X5 X6 X7 X8 X9
#1  1  1  1  2  2  2  2  2  2
#2  2  2  2  3  3  3  3  3  3
#3  3  3  3  4  4  4  4  4  4
#4  4  4  4  5  5  5  5  5  5

Or by name:

wifi %>% 
   mutate(across(X4:X9, A))
#  X1 X2 X3 X4 X5 X6 X7 X8 X9
#1  1  1  1  2  2  2  2  2  2
#2  2  2  2  3  3  3  3  3  3
#3  3  3  3  4  4  4  4  4  4
#4  4  4  4  5  5  5  5  5  5

Informer

Answer 4

As mentioned, you simply want the standard R apply function applied to columns (MARGIN=2):

wifi[,4:9] <- apply(wifi[,4:9], MARGIN=2, FUN=A)

Or, for short:

wifi[,4:9] <- apply(wifi[,4:9], 2, A)

This updates columns 4:9 in-place using the A() function. Now, let's assume that na.rm is an argument to A(), which it probably should be. We can pass na.rm=T to remove NA values from the computation like so:

wifi[,4:9] <- apply(wifi[,4:9], MARGIN=2, FUN=A, na.rm=T)

The same is true for any other arguments you want to pass to your custom function.

Swinson

Answer 5

The easiest way is to use the mutate function:

dataFunctionUsed <- data %>% 
  mutate(columnToUseFunctionOn = function(oldColumn ...))

Churl

Answer 6

I think what you want is mapply. You could apply the function to all columns, and then just drop the columns you don't want. However, if you are applying different functions to different columns, it seems likely what you want is mutate, from the dplyr package.

Falda