I have a list of dataframes that to manipulate individually that looks like this:
df_list <- list(A1 = data.frame(v1 = 1:10,
v2 = 11:20),
A2 = data.frame(v1 = 21:30,
v2 = 31:40))
df_list
Using lapply allows me to run a function over the list of dataframes like this:
library(tidyverse)
some_func <- function(lizt, comp = 2){
lizt <- lapply(lizt, function(x){
x <- x %>%
mutate(IMPORTANT_v3 = v2 + comp)
return(x)
})
}
df_list_1 <- some_func(df_list)
df_list_1
So far so good but I need to run the function multiple times with different arguments so using mapply returns:
df_list_2 <- mapply(some_func,
comp = c(2, 3, 4),
MoreArgs = list(
lizt = df_list
),
SIMPLIFY = F
)
df_list_2
This creates a new list of dataframes for each argument fed to the function in mapply giving me 3 lists of 2 dataframes. This is good but the output I'm looking for is to append a new column to each original dataframe for each argument in the mapply that would look like this:
desired_df_list <- list(A1 = data.frame(v1 = 1:10,
v2 = 11:20,
IMPORTANT_v3 = 13:22,
IMPORTANT_v4 = 14:23,
IMPORTANT_v5 = 15:24),
A2 = data.frame(v1 = 21:30,
v2 = 31:40,
IMPORTANT_v3 = 33:42,
IMPORTANT_v4 = 34:43,
IMPORTANT_v5 = 35:44))
desired_df_list
How can I wrangle the output of lists of lists of dataframes to isolate and append only the desired new columns (IMPORTANT_v3) to the original dataframe? Also open to other options such as mutating multiple columns inside the lapply using mapply but I haven't figured out how to code that as yet.
Thanks!