I have a dataset with over 15000 rows, which looks similar to this:
ID valid_from valid_until action action_text
1 1 01/01/2010 31/01/2016 1 Text1
2 1 01/02/2016 01/01/2021 2 Text2
3 2 01/10/2010 30/09/2019 4 Text4
4 3 01/05/2015 31/12/2015 3 Text3
5 3 01/01/2016 30/09/2020 3 Text3
I would like to combine the rows so that the last entry in column valid_until within the same ID becomes the first entry. Basically the first entry in column "valid_until" should be replaced with the last entry within the ID and rows which are not the first entries within an ID should be deleted.
To be more clear, I would like my result to look like this:
ID valid_from valid_until action action_text
1 1 01/01/2010 01/01/2021 1 Text1
2 2 01/10/2010 30/09/2019 4 Text4
3 3 01/05/2015 30/09/2020 3 Text3
Does anyone have an idea, how I could do this in R?
Thank you very much in advance!
CodePudding user response:
library(dplyr)
df %>% group_by(ID) %>%
mutate(valid_from=min(valid_from),
valid_until=max(valid_until),
action=first(action),
action_text=first(action_text)) %>%
distinct(across(everything()))
CodePudding user response:
We may convert the date columns to Date
class and just change the 'valid_until' column before doing the distinct
library(dplyr)
library(lubridate)
df1 %>%
mutate(across(starts_with('valid'), dmy)) %>%
group_by(ID) %>%
mutate(valid_until = max(valid_until)) %>%
distinct(ID, .keep_all = TRUE) %>%
ungroup
-output
# A tibble: 3 × 5
ID valid_from valid_until action action_text
<int> <date> <date> <int> <chr>
1 1 2010-01-01 2021-01-01 1 Text1
2 2 2010-10-01 2019-09-30 4 Text4
3 3 2015-05-01 2020-09-30 3 Text3
data
df1 <- structure(list(ID = c(1L, 1L, 2L, 3L, 3L), valid_from = c("01/01/2010",
"01/02/2016", "01/10/2010", "01/05/2015", "01/01/2016"), valid_until = c("31/01/2016",
"01/01/2021", "30/09/2019", "31/12/2015", "30/09/2020"), action = c(1L,
2L, 4L, 3L, 3L), action_text = c("Text1", "Text2", "Text4", "Text3",
"Text3")), class = "data.frame", row.names = c("1", "2", "3",
"4", "5"))