I have this time series data frame as follows:
df <- read.table(text =
"Year Month Value
2021 1 4
2021 2 11
2021 3 18
2021 4 6
2021 5 20
2021 6 5
2021 7 12
2021 8 4
2021 9 11
2021 10 18
2021 11 6
2021 12 20
2022 1 14
2022 2 11
2022 3 18
2022 4 9
2022 5 22
2022 6 19
2022 7 22
2022 8 24
2022 9 17
2022 10 28
2022 11 16
2022 12 26",
header = TRUE)
I want to turn this data frame into a time series object of date column and value column only so that I can use the ts function to filter the starting point and the endpoint like ts(ts, start = starts, frequency = 12). R should know that 2022 is a year and the corresponding 1:12 are its months, the same thing should apply to 2021. I will prefer lubridate package.
pacman::p_load(
dplyr,
lubridate)
UPDATE
I now use unite function from dplyr package.
df|>
unite(col='date', c('Year', 'Month'), sep='')
Perhaps this?
df |>
tidyr::unite(col='date', c('Year', 'Month'), sep='-') |>
mutate(date = lubridate::ym(date))
# date Value
# 1 2021-01-01 4
# 2 2021-02-01 11
# 3 2021-03-01 18
# 4 2021-04-01 6
# 5 2021-05-01 20
# 6 2021-06-01 5
# 7 2021-07-01 12
# 8 2021-08-01 4
# 9 2021-09-01 11
# 10 2021-10-01 18
# 11 2021-11-01 6
# 12 2021-12-01 20
# 13 2022-01-01 14
# 14 2022-02-01 11
# 15 2022-03-01 18
# 16 2022-04-01 9
# 17 2022-05-01 22
# 18 2022-06-01 19
# 19 2022-07-01 22
# 20 2022-08-01 24
# 21 2022-09-01 17
# 22 2022-10-01 28
# 23 2022-11-01 16
# 24 2022-12-01 26