Using a loop to create multiple dataframes from a single dataset - r

Question

Quick question for you. I have the following:
a <- c(1,5,2,3,4,5,3,2,1,3)
b <- c("a","a","f","d","f","c","a","r","a","c")
c <- c(.2,.6,.4,.545,.98,.312,.112,.4,.9,.5)
df <- data.frame(a,b,c)
What i am looking to do is utilize a for loop to create multiple data frames from rows based on the column contents of column B (i.e. a df for the "a," the "d," and so on).
At the same time, I would also like to name the data frame based on the corresponding value from column B (df will be named "a" for the data frame created from the "a."
I tried making it work based off the answers provided here Using a loop to create multiple data frames in R but i had no luck.
If it helps, I have variables created with levels() and nlevels() to use in the loop to keep it scalable based on how my data changes. Any help would be much appreciated.
Thanks!

Answer 1

This should do:
require(dplyr)
df$b <- as.character(df$b)
col.filters <- unique(df$b)
lapply(seq_along(col.filters), function(x) {
filter(df, b == col.filters[x])
}
) -> list
names(list) <- col.filters
list2env(list, .GlobalEnv)
Naturally, you don't need dplyr to do this. You can just use base syntax:
df$b <- as.character(df$b)
col.filters <- unique(df$b)
lapply(seq_along(col.filters), function(x) {
df[df[, "b"] == col.filters[x], ]
}
) -> list
names(list) <- col.filters
list2env(list, .GlobalEnv)
But I find dplyrmuch more intuitive.
Cheers