I have a dataframe which looks something like:
start_date end_date name value
1 2020-01-01 2020-01-06 x 2
2 2020-01-05 2020-01-07 y 4
I’d like to spread the dates by day, so that the name variables become columns taking their respective value, as so:
date x y
1 2020-01-01 2 NA
2 2020-01-02 2 NA
3 2020-01-03 2 NA
4 2020-01-04 2 NA
5 2020-01-05 2 4
6 2020-01-06 2 4
7 2020-01-07 NA 4
I would be interested in a base R solution, but also solutions using dplyr and/or lubridate
>Solution :
Convert the ‘_date’ columns to Date class (if it is not already in Date class), then create the ‘date’ column by getting the seq between the ‘start_date’, ‘end_date’ using map2 (or can also do after rowwise), unnest the list column and reshape into ‘wide’ format with pivot_wider
library(dplyr)
library(lubridate)
library(purrr)
library(tidyr)
df1 %>%
mutate(across(ends_with('_date'), ymd)) %>%
transmute(date = map2(start_date, end_date, seq, by = "1 day"),
name, value) %>%
unnest(date) %>%
pivot_wider(names_from = name, values_from = value)
-output
# A tibble: 7 × 3
date x y
<date> <int> <int>
1 2020-01-01 2 NA
2 2020-01-02 2 NA
3 2020-01-03 2 NA
4 2020-01-04 2 NA
5 2020-01-05 2 4
6 2020-01-06 2 4
7 2020-01-07 NA 4
data
df1 <- structure(list(start_date = c("2020-01-01", "2020-01-05"),
end_date = c("2020-01-06",
"2020-01-07"), name = c("x", "y"), value = c(2L, 4L)),
class = "data.frame", row.names = c("1",
"2"))