R language: how to split a data frame

Question

I want to split a data frame into several smaller ones. This looks like a very trivial question, however I cannot find a solution from web search.

Can anyone help?

Also, do you have any recommendation for a simple experiment design or survey R package ?

many thanks.

Leo

Answer 1

The key is that you can subset a data frame using vector indices. A quick example to get you thinking about what exactly you want to learn how to do:

> A <- data.frame(matrix(1:16, nrow=4, ncol=4))
> A
  X1 X2 X3 X4
1  1  5  9 13
2  2  6 10 14
3  3  7 11 15
4  4  8 12 16
> left.half <- c(1, 2)
> right.half <- c(3, 4)
> A.lh <- A[ , left.half]
> A.rh <- A[ , right.half]
> A.lh
  X1 X2
1  1  5
2  2  6
3  3  7
4  4  8
> A.rh
  X3 X4
1  9 13
2 10 14
3 11 15
4 12 16

A quick search at rseek.org found this, which is a great tutorial:

http://www.r-bloggers.com/select-operations-on-r-data-frames/

Also, Grant Farnsworth has a great guide to econmetrics in R that I find helpful. You can also find that with rseek.org's search engine.

Answer 2

If you want to split a dataframe according to values of some variable, I'd suggest using daply() from the plyr package.

library(plyr)
x <- daply(df, .(splitting_variable), function(x)return(x))

Now, x is an array of dataframes. To access one of the dataframes, you can index it with the name of the level of the splitting variable.

x$Level1
#or
x[["Level1"]]

I'd be sure that there aren't other more clever ways to deal with your data before splitting it up into many dataframes though.

Answer 3

subset() is also useful

subset(DATAFRAME, COLUMNNAME == "")

For a survey package, maybe the "survey" package is pertinent?

http://faculty.washington.edu/tlumley/survey/

Answer 4

You may also want to cut the data frame into an arbitrary number of smaller dataframes. Here, we cut into two dataframes.

x = data.frame(num = 1:26, let = letters, LET = LETTERS)
set.seed(10)
split(x, sample(rep(1:2, 13)))

gives

$`1`
   num let LET
3    3   c   C
6    6   f   F
10  10   j   J
12  12   l   L
14  14   n   N
15  15   o   O
17  17   q   Q
18  18   r   R
20  20   t   T
21  21   u   U
22  22   v   V
23  23   w   W
26  26   z   Z

$`2`
   num let LET
1    1   a   A
2    2   b   B
4    4   d   D
5    5   e   E
7    7   g   G
8    8   h   H
9    9   i   I
11  11   k   K
13  13   m   M
16  16   p   P
19  19   s   S
24  24   x   X
25  25   y   Y

Answer 5

The answer you want depends very much on how and why you want to break up the data frame.

For example, if you want to leave out some variables, you can create new data frames from specific columns of the database. The subscripts in brackets after the data frame refer to row and column numbers. Check out Spoetry for a complete description.

newdf <- mydf[,1:3]

Or, you can choose specific rows.

newdf <- mydf[1:3,]

And these subscripts can also be logical tests, such as choosing rows that contain a particular value, or factors with a desired value.

What do you want to do with the chunks left over? Do you need to perform the same operation on each chunk of the database? Then you'll want to ensure that the subsets of the data frame end up in a convenient object, such as a list, that will help you perform the same command on each chunk of the data frame.

Answer 6

I just posted a kind of a RFC that might help you: http://stackoverflow.com/questions/3318333/split-a-vector-into-chunks-in-r

x = data.frame(num = 1:26, let = letters, LET = LETTERS)
## number of chunks
n <- 2
dfchunk <- split(x, factor(sort(rank(row.names(x))%%n)))
dfchunk
$`0`
   num let LET
1    1   a   A
2    2   b   B
3    3   c   C
4    4   d   D
5    5   e   E
6    6   f   F
7    7   g   G
8    8   h   H
9    9   i   I
10  10   j   J
11  11   k   K
12  12   l   L
13  13   m   M

$`1`
   num let LET
14  14   n   N
15  15   o   O
16  16   p   P
17  17   q   Q
18  18   r   R
19  19   s   S
20  20   t   T
21  21   u   U
22  22   v   V
23  23   w   W
24  24   x   X
25  25   y   Y
26  26   z   Z

Cheers, Sebastian