I tried this:
library(tidyverse)
dummydat <- tibble::tribble(
~ID, ~Visite, ~Pet,
1L, 1L, "dog",
1L, 2L, "dog",
1L, 4L, "cat",
1L, 4L, "dog",
1L, 5L, "cat",
1L, 6L, "cat",
2L, 1L, "cat",
2L, 2L, "cat",
2L, 3L, "dog",
2L, 4L, "dog",
2L, 4L, "cat",
2L, 6L, "dog",
2L, 7L, "dog",
3L, 1L, "cat",
3L, 2L, "cat",
3L, 3L, "dog",
3L, 4L, "dog",
3L, 4L, "cat",
3L, 5L, "dog",
3L, 6L, "dog"
)
dummydat
library(dplyr)
dummydat2<- dummydat %>%
group_by(ID) %>%
mutate(Visite = case_when(duplicated(Visite, fromLast = TRUE) ~
lag(Visite) + 1L, TRUE ~ Visite))
dummydat2
dummydat3<- dummydat2 %>%
group_by(ID) %>%
mutate(Visite = case_when(duplicated(Visite, fromLast = FALSE) ~
lag(Visite) + 1L, TRUE ~ Visite))
dummydat3
dummydat4<- dummydat3 %>%
group_by(ID) %>% filter(!duplicated(Visite)) %>%
filter(!is.na(Pet))
dummydat4
I really don't get it. Yesterday it worked but today all values suddenly change ....
The result is:
# A tibble: 17 x 3
# Groups: ID [3]
ID Visite Pet
<int> <int> <chr>
1 1 NA dog
2 1 2 dog
3 1 3 cat
4 1 5 dog
5 1 6 cat
6 2 7 cat
7 2 8 cat
8 2 3 dog
9 2 4 dog
10 2 5 cat
11 2 6 dog
12 3 1 cat
13 3 2 cat
14 3 3 dog
15 3 4 dog
16 3 5 cat
17 3 6 dog
The values get completely confused!