Split many dataframes by a column, and save as different dataframes-CodePudding

I have many dataframes. I would like to split them based on the values in a column (a factor). Then I would like to store the result of the split in separate data frame that have a specific name.

For the sake of a mrp, consider some generated data,

for (i in 1:10) {
assign(paste("df_",i,sep = ""), data.frame(x = rep(1,12), y  = c(rep("a",4),rep("b",4),rep("c",4))))
}

here we have 10 dfs, df_1, df_2... to df_10. (real data is similar to generated data, but in real data column z is different for each df).

Now, I want to split the dfs by 'y' (column 2).

For 1 df, I can do the following;

splitdf <- split(df_1,df_1$y)
namessplit <- c("a","b","c")
for (i in 1:length(splitdf)) {
  assign(paste("df_1_",namessplit[[i]],sep = ""),splitdf[[i]])
}

While this works for 1 df, how can I do it for all the dfs?

Big thanks in advance!

CodePudding user response：

It is not recommended to create multiple objects in the global env, but if we want to know how to create the objects from a nested list - Loop over the outer list sequence and then in the inner list sequence, paste the corresponding names to assign the extracted inner list element

lst1 <- lapply(mget(ls(pattern = "^df_\\d $")), \(x) split(x, x$y))
for(i in seq_along(lst1)) {
   for(j in seq_along(lst1[[i]]))  {
   assign(paste0(names(lst1)[i], "_", names(lst1[[i]][j])), lst1[[i]][[j]])
  }
}

-checking for objects created in the global env

> ls(pattern = "^df_\\d _[a-z] $")
 [1] "df_1_a"  "df_1_b"  "df_1_c"  "df_10_a" "df_10_b" "df_10_c" "df_2_a"  "df_2_b"  "df_2_c"  "df_3_a"  "df_3_b"  "df_3_c"  "df_4_a" 
[14] "df_4_b"  "df_4_c"  "df_5_a"  "df_5_b"  "df_5_c"  "df_6_a"  "df_6_b"  "df_6_c"  "df_7_a"  "df_7_b"  "df_7_c"  "df_8_a"  "df_8_b" 
[27] "df_8_c"  "df_9_a"  "df_9_b"  "df_9_c"