Splitting into separate dataframes based on factor levels

[joewranglesdata]

I have a dataset that includes a factor with lots of levels, and I would like to filter the dataset by this factor to create new dataframes, naming each new dataframe according to the factor level that it comes from.

At the moment, I'm doing this like this:

library(tidyverse)
data("iris")
setosa <- filter(iris, Species == "setosa")
versicolor <- filter(iris, Species == "versicolor")
virginica <- filter(iris, Species == "virginica")

This works, but my actual data has a lot more levels than iris$Species, so it quickly becomes unwieldy. Does anyone know a better way to do this? I've tried using group_split(), which is close, but doesn't quite do what I'd like - rather than a list of tibbles, I'd like each one to be saved as separate dataframe and named accordingly, as above.

Any help much appreciated!

[nirgrahamuk]

use attach to make a list of data.frames accessible 'as if it were' in your global environment

data(iris)

(iris_split <- split(iris,iris$Species))

attach(iris_split)

head(virginica)
tail(virginica)

[joewranglesdata]

@nirgrahamuk

data(iris)

(iris_split <- split(iris,iris$Species))

attach(iris_split)

head(virginica)
tail(virginica)

That's just what I needed, thank you so much!