4

I have, for example, this three datasets (in my case, they are many more and with a lot of variables):

data_frame1 <- data.frame(a=c(1,5,3,3,2), b=c(3,6,1,5,5), c=c(4,4,1,9,2))
data_frame2 <- data.frame(a=c(6,0,9,1,2), b=c(2,7,2,2,1), c=c(8,4,1,9,2))
data_frame2 <- data.frame(a=c(0,0,1,5,1), b=c(4,1,9,2,3), c=c(2,9,7,1,1))

on each data frame I want to add a variable resulting from a transformation of an existing variable on that data frame. I would to do this by a loop. For example:

datasets <- c("data_frame1","data_frame2","data_frame3")
vars <- c("a","b","c")
for (i in datasets){
    for (j in vars){
        # here I need a code that create a new variable with transformed values
        # I thought this would work, but it didn't...
        get(i)$new_var <- log(get(i)[,j])
    }
}

Do you have some valid suggestions about that?

Moreover, it would be great for me if it were possible also to assign the new column names (in this case new_var) by a character string, so I could create the new variables by another for loop nested in the other two.

Hope I've not been too tangled in explain my problem.

Thanks in advance.

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3
  • thanks. Could you also explain me the other method? Commented Jan 20, 2013 at 21:52
  • I had read your deleted comment. You sayd that there is a less complicated method to do this. Commented Jan 20, 2013 at 21:57
  • No, a log for some columns, and other transformations for other columns... Commented Jan 20, 2013 at 21:58

2 Answers 2

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7

You can put your dataframes in a list and use lapply to process them one by one. So no need to use a loop in this case.

For example you can do this : 

data_frame1 <- data.frame(a=c(1,5,3,3,2), b=c(3,6,1,5,5), c=c(4,4,1,9,2))
data_frame2 <- data.frame(a=c(6,0,9,1,2), b=c(2,7,2,2,1), c=c(8,4,1,9,2))
data_frame3 <- data.frame(a=c(0,0,1,5,1), b=c(4,1,9,2,3), c=c(2,9,7,1,1))

ll <- list(data_frame1,data_frame2,data_frame3)
lapply(ll,function(df){
  df$log_a <- log(df$a)          ## new column with the log a
  df$tans_col <- df$a+df$b+df$c  ## new column with sums of some columns or any other           
                                 ##   transformation
  ###  .....
  df

})

the dataframe1 becomes :

[[1]]
  a b c     log_a tans_col
1 1 3 4 0.0000000        8
2 5 6 4 1.6094379       15
3 3 1 1 1.0986123        5
4 3 5 9 1.0986123       17
5 2 5 2 0.6931472        9
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5 Comments

@agstudy I tried your solution on my data. I notice that it doesn't really write the new variables. In you example, log_a and tans_col are not inserted in the data frames. Certainly I'm mistakiing something...
@this.is.not.a.nick in this case I use the $ will create the new variable.. df$log_a will create a variable of name log_a...what have you tried with your data?
@agstudy Yes, but if, following your example, I then type ll[[1]]$log_a, R returns me NULL
@this.is.not.a.nick it is normal , R do the transformation in a copy of ll so you need to do something like ll <- lapply(ll,function(df)... to change the value of your list..
...as I imagined, my problem was stupid. :) Thanks a lot @agstudy
1

I had the same need and wanted to change also the columns in my actual list of dataframes.

I found a great method here (the purrr::map2 method in the question works for dataframes with different columns), followed by 

list2env(list_of_dataframes ,.GlobalEnv)
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