'Create filtered dataframe with dplyr and for loop

I want to create several data frames from an original one in R using for loop. I want to get three separated data frames for each species to conduct separate analysis.

I tried the following code but it doesn't work:

data(iris)
library(dplyr)
for i in levels(iris$Species){
  paste0(i,".data") <- data.frame(filter(iris,
                                         Species=="i"))
}

I do not necessarily need dplyr but it's the one I am used to.

rfor-loopdplyrfilter


Solution 1:[1]

I think it is better to keep the separate frames in a list, which as pointed out in the comments is done easily with split(iris, iris$Species)

If you really want them out of the list and into separate named frames, you can use

list2env(split(iris, iris$Species),envir = .GlobalEnv)

Solution 2:[2]

An even better approach would be to keep everything in one data frame and then use dplyr/tidyr’s group_by() and nest() functions to fit a model for each group.

See here for a detailed walkthrough: https://tidyr.tidyverse.org/articles/nest.html

Sources

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Source: Stack Overflow

Solution Source
Solution 1 langtang
Solution 2 Brenton M. Wiernik

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