CODEWITHSUNDEEP
rfunction
user2453780
user2453780

Reputation: 15

Apply a function on all elements in a Dataframe

I am sure the answer is simple, but I did a lot a searching the last days, but apparently not able to figure out the right thing to do.. The problem is: I have imported a dataset via RODBC that shows what how much profit each user is generating

userdata <- sqlQuery(channel, query) 
userdata    

  USER   P1  P2   P2   P3
1 322    459 354  349  699 
2 232    249 311  349  699 
3 433    390 393  349  699

Then I have made a 4 functions that have their own set of conditions, and they will simply return a number, customer lifetime value. I like to use the functions on each of the columns P1,P2,P2,P4. For example apply clvP1() for each element in column P1 and so on. End result begin that the values in 'userdata' are updated, so I can send this back to database.

So if anyone has a tip, please let me know.

thanks,

Upvotes: 1

Views: 2981

Answers (2)

topchef
topchef

Reputation: 19783

To apply function clvP1 on column P1 of a data frame simply: 

 userdata$P1 = clvP1(userdata[,'P1'])

Complete solution:

 new_userdata = with(userdata, data.frame(USER=USER, P1=clvP1(P1), P2=clvP2(P2),
                                          P3=clvP3(P3), P4=clvP4(P4)))

Upvotes: 2

thelatemail
thelatemail

Reputation: 93813

Here's a worked example of how you could apply specific functions to specific columns:

Example data:

test <- data.frame(a=1:3,b=4:6)
test

  a b
1 1 4
2 2 5
3 3 6

Define functions as columnname+"fun"

afun <- function(x) {exp(x)}
bfun <- function(x) {log(x)}

Apply afun to col a and bfun to col b and so on...

data.frame(
  mapply(
    function(x,y) do.call(y,list(x)),
    test, 
    paste(names(test),"fun",sep=""),
    SIMPLIFY=FALSE
        )
)

Result

#     exp(a)   log(b)    as defined by afun and bfun
          a        b
1  2.718282 1.386294
2  7.389056 1.609438
3 20.085537 1.791759

Upvotes: 1

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