Split data.frame based on levels of a factor into new data.frames

ghz 1years ago ⋅ 8107 views

Question

I'm trying to create separate data.frame objects based on levels of a factor. So if I have:

df <- data.frame(
  x=rnorm(25),
  y=rnorm(25),
  g=rep(factor(LETTERS[1:5]), 5)
)

How can I split df into separate data.frames for each level of g containing the corresponding x and y values? I can get most of the way there using split(df, df$g), but I'd like the each level of the factor to have its own data.frame.

What's the best way to do this?

Answer

I think that split does exactly what you want.

Notice that X is a list of data frames, as seen by str:

X <- split(df, df$g)
str(X)

If you want individual object with the group g names you could assign the elements of X from split to objects of those names, though this seems like extra work when you can just index the data frames from the list split creates.

#I used lapply just to drop the third column g which is no longer needed.
Y <- lapply(seq_along(X), function(x) as.data.frame(X[[x]])[, 1:2]) 

#Assign the dataframes in the list Y to individual objects
A <- Y[[1]]
B <- Y[[2]]
C <- Y[[3]]
D <- Y[[4]]
E <- Y[[5]]

#Or use lapply with assign to assign each piece to an object all at once
lapply(seq_along(Y), function(x) {
    assign(c("A", "B", "C", "D", "E")[x], Y[[x]], envir=.GlobalEnv)
    }
)

Edit Or even better than using lapply to assign to the global environment use list2env:

names(Y) <- c("A", "B", "C", "D", "E")
list2env(Y, envir = .GlobalEnv)
A
#r