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

Question

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 1

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)

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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)]