[R] changing one character in the name of dataframes repeatedly

[Ivan Calandra]

Hi,

I think, what you want is assign().
for (i in 1:6) assign(paste("df", i, sep="."), split(df,df$a)[[i]])

But using lists is usually a better solution since you can work with 
them using functions such as lapply().

First, you don't need cbind() to create your data.frame:
df2 <- data.frame(a,b)
identical(df, df2)
[1] TRUE

Then, I think that
df_split <- split(df, df$a)
does pretty much what you want.
You could additionally adjust the names like this:
names(df_split) <- paste("df", 1:length(df_split), sep=".")

As a last comment, depending on what your ultimate goal is, you might 
not need to do it at all. Take a look at ?aggregate, ?by, ?summaryBy 
(from package doBy) and ?ddply( from package plyr) for example.

HTH,
Ivan


Le 3/11/2011 16:49, Bodnar Laszlo EB_HU a écrit :
> Dear R-community,
>
>
>
> I'd like to ask you a question concerning R again. I try to keep this simple because I am not willing to confuse you at all.
>
>
>
> I have a little data frame which I have created the following way:
>
>
>
> a<-c(1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4,5,5,5,5,5,6,6,6,6,6)
>
> b<-c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30)
>
> df<-as.data.frame(cbind(a,b))
>
> df
>
>
>
> Now in the next step I would have liked to create smaller dataframes where the data have been extracted (basically splitted) from the main 'df' dataframe according to the numbers in df$a. Something like this:
>
> a b
>
> 1 1
>
> 1 2
>
> 1 3
>
> 1 4
>
> 1 5
>
>
>
> a  b
>
> 2  6
>
> 2  7
>
> 2  8
>
> 2  9
>
> 2 10
>
>
>
> a  b
>
> 3 11
>
> 3 12
>
> 3 13
>
> 3 14
>
> 3 15
>
>
>
> a  b
>
> 4 16
>
> 4 17
>
> 4 18
>
> 4 19
>
> 4 20
>
>
>
> etc.
>
>
>
> It is not quite difficult to do this part. But!! I also want that the name of each and every small dataframe should refer to the fact that according to which number in df$a have I selected the data in df$b.
>
>
>
> For example:
>
>
>
> df.1 meaning I have only chosen those numbers in df$b which have value "1" in df$a
>
>
>
> df.1
>
> a b
>
> 1 1
>
> 1 2
>
> 1 3
>
> 1 4
>
> 1 5
>
>
>
> df.2 meaning I have only chosen those numbers in df$b which have value "2" in df$a.
>
>
>
> df.2
>
> a  b
>
> 2  6
>
> 2  7
>
> 2  8
>
> 2  9
>
> 2 10
>
>
>
> df.3 meaning I have only chosen those numbers in df$b which have value "3" in df$a.
>
> a  b
>
> 3 11
>
> 3 12
>
> 3 13
>
> 3 14
>
> 3 15
>
> etc...
>
>
>
> I know it would not be difficult to do this in this way:
>
> df.1<-split(df,df$a)[[1]]
>
> df.2<-split(df,df$a)[[2]]
>
> df.3<-split(df,df$a)[[3]]
>
> df.4<-split(df,df$a)[[4]]
>
> etc...
>
>
>
> But as a matter of fact, my real df dataframe consists of more than 4400 records so it is impossible to do this "manually" for a numerous times with the previously mentioned split function.
>
>
>
> I wanted to use loops and managing the problem in the following (wrong) way:
>
> for (i in 1:6)
>
>      {
>
>      df.i<-split(df,df$a)[[i]]
>
>      }
>
>
>
> After I wanted to enter df.1, df.2, etc... R sent me the message:
>
> Error: object 'df.1' not found.
>
>
>
> However, it recognized df.i and listed following:
>
>     a  b
>
> 6 26
>
> 6 27
>
> 6 28
>
> 6 29
>
> 6 30
>
>
>
> Can you help me with this matter? I wonder if there is a proper way to do this which I haven't figured out yet...
>
>
>
> Thank you very much and have a pleasant weekend,
>
> Laszlo Bodnar
>
>
>
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-- 
Ivan CALANDRA
PhD Student
University of Hamburg
Biozentrum Grindel und Zoologisches Museum
Abt. Säugetiere
Martin-Luther-King-Platz 3
D-20146 Hamburg, GERMANY
+49(0)40 42838 6231
ivan.calandra at uni-hamburg.de

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