R Changing format to columns of dataframes using functional programming - r

Question

The situation is the following: I have a list of dataframes, and for each dataframe I have a list of columns whose format I need to change. Setup:
df1 <- data.frame(a = c("2020-03-02", "2020-12-22", "2020-07-03"), b = c(4, 5, 6), c = c("2020-03-13", "2019-11-03", "2011-05-02"))
df2 <- data.frame(d = c(1, 2, 3), e = c("2020-05-21", "2014-08-31", "1999-01-21"), f = c(7, 8, 9))
datasets <- list("first" = df1, "second" = df2)
dates <- list("first" = c("a", "c"), "second" = c("e"))
One could do this by 1. Looping over the list of dataframes, 2. for each dataframe, looping over the list of columns one wants to change, and reassign them in place. Something like this:
for (i in names(datasets)) {
for (j in dates[i]) {
for (k in datasets[[i]][j]) {
k <- as.Date(k)
}
}
}
This is ugly, so I wanted to try to do the same using purrr. I thought this would be a good idea:
library(purrr)
walk2(datasets, dates, ~ walk(.x[.y], ~ {.x <- as.Date(.x)}))
But the datasets remain unperturbed after this operation. Why?

Answer 1

Here is a solution that uses purrr and dplyr:
library(purrr)
library(dplyr)
datasets <- datasets %>%
imap(~{
.x %>%
mutate_at(vars(dates[[.y]]), as.Date)
})
str(datasets)
#List of 2
#$ first :'data.frame': 3 obs. of 3 variables:
# ..$ a: Date[1:3], format: "2020-03-02" "2020-12-22" "2020-07-03"
# ..$ b: num [1:3] 4 5 6
# ..$ c: Date[1:3], format: "2020-03-13" "2019-11-03" "2011-05-02"
#$ second:'data.frame': 3 obs. of 3 variables:
# ..$ d: num [1:3] 1 2 3
# ..$ e: Date[1:3], format: "2020-05-21" "2014-08-31" "1999-01-21"
# ..$ f: num [1:3] 7 8 9