Starting from a list of lists like outcome:
id <- c(1,2,3,4,5,1,2,3,4,5)
month <- c(3,4,2,1,5,7,3,1,8,9)
preds <- c(0.5,0.1,0.15,0.23,0.75,0.6,0.49,0.81,0.37,0.14)
l_1 <- data.frame(id, preds, month)
preds <- c(0.45,0.18,0.35,0.63,0.25,0.63,0.29,0.11,0.17,0.24)
l_2 <- data.frame(id, preds, month)
preds <- c(0.58,0.13,0.55,0.13,0.76,0.3,0.29,0.81,0.27,0.04)
l_3 <- data.frame(id, preds, month)
preds <- c(0.3,0.61,0.18,0.29,0.85,0.76,0.56,0.91,0.48,0.91)
l_4 <- data.frame(id, preds, month)
outcome <- list(l_1, l_2, l_3, l_4)
My interest is to take the assigned unique row values and create a new variable as if we do:
sample <- outcome[[1]]
sample$unique_id <- rownames(sample)
However, I don´t want to go manually because my list has 100 lists. Moreover, I don´t want to assign values manually to each row because I want to preserve the row names generated by R.
Any clue?
We may also use rownames_to_column
library(dplyr)
library(purrr)
library(tibble)
map(outcome, ~ .x %>%
rownames_to_column('unique_id'))
With lapply
and cbind
:
lapply(outcome, function(x) {
cbind(unique_id=rownames(x), x)
})
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