rolling mutate function applied to lists data frames - r

Question

I have some time series data where I use the rolling_origin function to apply different time series splits to the data which generates a number of lists. The time series starts from 2020-03-01 until 2020-10-30.
I want to start from 2020-04-15 such that I have 1 month before (2020-03-15) and 1 month after (2020-05-15). I can use an ifelse statement to add a 1 for observations after and a 0 for observations before.
rolledData %>%
map(., ~mutate(.x,
treatment_control = ifelse(date >= as.Date("2020-04-15"), 1, 0)
))
But what I want to do is to increment the ifelse date when mapped over the list. So the first one might start on the 2020-04-15 but in the next list in the sequence it would be changed to 2020-04-16, and the next list 2020-04-17, .... , until the end.
I could manually write out the results:
lst1 <- rolledData[[12]] %>%
mutate(
treatment_control = ifelse(date >= as.Date("2020-04-15"), 1, 0)
)
lst2 <- rolledData[[13]] %>%
mutate(
treatment_control = ifelse(date >= as.Date("2020-04-16"), 1, 0)
)
lst3 <- rolledData[[14]] %>%
mutate(
treatment_control = ifelse(date >= as.Date("2020-04-17"), 1, 0)
)
How can I map over the list and increment the treatment_control mutate?
Note: Because I am using financial data (which was just the easiest to obtain for a reproducible example) the weekends are removed (in my data I have a full week)
Data:
library(tidyquant)
library(rsample)
data <- tq_get(c("AAPL"),
get = "stock.prices",
from = "2020-03-01",
to = "2020-10-30")
rolledData <- data %>%
rolling_origin(
data = .,
initial = 60, # 2 months of data
assess = 0,
cumulative = FALSE,
skip = 0
)
rolledData <- rolledData$splits %>%
map(., ~analysis(.x))

Answer 1

If the dates are different, we can pass a vector of custom dates that have the same length as the rolledData in map2
library(dplyr)
library(purrr)
rolleData2 <- rolledData %>%
map2(., newdates,
~ .x %>%
mutate(treatment_control = +(date >= .y)
))
where
newdates <- seq(as.Date("2020-03-15"), length.out = length(rolledData), by = "1 day")
If it is based on the next month from the first 'date' value
library(lubridate)
rolledData2 <- rolledData %>%
map(~ .x %>%
mutate(treatment_control =
+(date >= (first(date) %m+% months(1)))))