Rachit Agrawal Rachit Agrawal - 1 month ago 7
R Question

R subsetting a data frame into multiple data frames based on multiple column values

I am trying to subset a data frame, where I get multiple data frames based on multiple column values. Here is my example

>df
v1 v2 v3 v4 v5
A Z 1 10 12
D Y 10 12 8
E X 2 12 15
A Z 1 10 12
E X 2 14 16


The expected output is something like this where I am splitting this data frame into multiple data frames based on column
v1
and
v2


>df1
v3 v4 v5
1 10 12
1 10 12
>df2
v3 v4 v5
10 12 8
>df3
v3 v4 v5
2 12 15
2 14 16


I have written a code which is working right now but don't think that's the best way to do it. There must be a better way to do it. Assuming
tab
is the data.frame having the initial data. Here is my code:

v1Factors<-levels(factor(tab$v1))
v2Factors<-levels(factor(tab$v2))

for(i in 1:length(v1Factors)){
for(j in 1:length(v2Factors)){
subsetTab<-subset(tab, v1==v1Factors[i] & v2==v2Factors[j], select=c("v3", "v4", "v5"))
print(subsetTab)
}
}


Can someone suggest a better method to do the above?

Answer

You are looking for split

split(df, with(df, interaction(v1,v2)), drop = TRUE)
$E.X
  v1 v2 v3 v4 v5
3  E  X  2 12 15
5  E  X  2 14 16

$D.Y
  v1 v2 v3 v4 v5
2  D  Y 10 12  8

$A.Z
  v1 v2 v3 v4 v5
1  A  Z  1 10 12

As noted in the comments

any of the following would work

library(microbenchmark)
microbenchmark(
                split(df, list(df$v1,df$v2), drop = TRUE), 
               split(df, interaction(df$v1,df$v2), drop = TRUE),
               split(df, with(df, interaction(v1,v2)), drop = TRUE))


Unit: microseconds
                                                  expr      min        lq    median       uq      max neval
            split(df, list(df$v1, df$v2), drop = TRUE) 1119.845 1129.3750 1145.8815 1182.119 3910.249   100
     split(df, interaction(df$v1, df$v2), drop = TRUE)  893.749  900.5720  909.8035  936.414 3617.038   100
 split(df, with(df, interaction(v1, v2)), drop = TRUE)  895.150  902.5705  909.8505  927.128 1399.284   100

It appears interaction is slightly faster (probably due the fact that the f = list(...) are just converted to an interaction within the function)


Edit

If you just want use the subset data.frames then I would suggest using data.table for ease of coding

library(data.table)

dt <- data.table(df)
dt[, plot(v4, v5), by = list(v1, v2)]
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