CODEWITHSUNDEEP
r
Fuv8
Fuv8

Reputation: 905

Split and save in new data.frames

I have a big data.frame (144 columns). I would like to split it in groups of 3 columns each (subfile or sub data.frame), and then save the sub data.frames in separated files. In other words: file1 will contain columns from 1 to 3, file2 will contain columns from 6 to 9 and so on.

Any idea about?

Just an example: 

  Hb1  Int1  Value1   Hb2  Int2  Value2         
   A     c     0.3     SW   n     0.34        
   V     sd    0.45    FG   b     0.345    
   N     wer   0.76    GH   m     0.67

So: File "output1" will contain: 

  Hb1  Int1   Value1   
   A     c     0.3
   V     sd    0.45    
   N     wer   0.76

File "output2" will contain: 

 Hb2    Int2  Value2     
 SW       n    0.34    
 FG       b    0.345    
 GH       m    0.67

and so on.

I tried to add a column to the transposed data.frame containing Index values such that:

Index = rep(1: 48, each = 3)

Then I tried to split the big data.frame according to the Index column but I'm not able to go on.

Upvotes: 4

Views: 3293

Answers (2)

agstudy
agstudy

Reputation: 121608

you was close with Index = rep(1: 48, each = 3) , you can use it to split the columns names.

lapply(split(colnames(DF),
             rep(1:48,each=3)),
       function(x)DF[,x])

Testing it with @Jilber example:

colnames(DF) <-  paste(c('Hb','Int',  'Value'),rep(1:48,each=3),sep='')

> ll <- lapply(split(colnames(DF),
+              rep(1:48,each=3)),
+        function(x)DF[,x])
> head(ll)
$`1`
         Hb1      Int1    Value1
1  155.56103 114.70061  50.15758
2  100.91212 108.93485 138.43324
3   65.02612  97.95829  60.55026
4  102.85399  99.80714  74.53144
5  152.52558 100.28795 109.27979
6  110.84282 122.67727 100.60916
7  100.06572  92.96498 118.99915
8  104.69424  91.46041  38.57983
9   74.59960 119.89719 158.41313
10 100.89299  85.79222 122.57668
11  92.87294  84.40889  95.39005
12  81.20039 127.29311  92.19261

$`2`
         Hb2      Int2    Value2
1  101.27385  96.21813  21.83450
2  124.26445 117.29466  53.67718
3  144.58042 111.06022  91.92567
4  120.74942  98.63582 123.98479
5   95.74860  79.96633 149.62814
6   74.78898  68.25731 122.72720
7  132.12760  97.76982  56.66394
8   47.18706 118.68346 113.63118
9  115.27

Upvotes: 3

Jilber Urbina
Jilber Urbina

Reputation: 61214

Maybe this is useful for you:

# A simple function (EDIT: FIXED) 
Split_and_save_DF <- function(DF, split){
  # Spliting your data frame by columns to get several data.frames
  DFlist <-lapply(seq(1, ncol(DF), split), function(x, i){x[, i:(i+(split-1))]}, x=DF)
  # Saving each data.frames as .txt file
  invisible(sapply(1:length(DFlist), function(x, i) write.table(x[[i]], file=paste0('DF', i, '.txt')), x=DFlist))
}

Example

DF <- data.frame(matrix(rnorm(144*12, 100, 30), ncol=144))
dim(DF) # a dataframe with 12 rows and 144 cols
Split_and_save_DF(DF=DF, split=3) # will produce 48 DF's

Where DF is the data.frame, and split is the number of columns you want the dataframe to be split by.

It's not a nice answer but it does what you want.

This function will split your DF and will save each new DF in your current working directory with names such as: DF1.txt, DF2.txt, DF3.txt.... so that you can read each file by doing:

read.table("DF1.txt", header=TRUE) # and so on

In order to check the output:

dim(read.table("DF1.txt", header=TRUE)) # checking dims of new DF's
[1] 12  3

Upvotes: 4

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