Mutate 2 vectors into a single vector in R-CodePudding

I have a variable named Tactic (migratory tactics for a predatory species of fish) that contains three levels i.e "Migr", "OcRes", "EstRes" see data below:

combo1 <- structure(list(Sex = c("F", "M", "F", NA, "M", "F", NA, NA, "M", 
"F", NA, "M", "F", "F", NA, "F", "F", NA, "M", "F", NA, "M", 
"F", "F", "F", "F", "F", "M", NA, "F", "M", "M", "F", "F", "M", 
"F", NA, NA, NA, NA, NA, NA, "F", "F", NA, NA, NA, "M", "F", 
"F", NA, "F", "F", NA, NA, "M", "F", NA, "F", NA, "M", NA, "F", 
NA, NA, NA, NA, "F", "M", "M", NA, "F"), Tactic = c("Migr", "Migr", 
"Migr", "Migr", "Migr", "Migr", "Migr", "Migr", "Migr", "Migr", 
"Migr", "Migr", "Migr", "Migr", "Migr", "OcRes", "Migr", "Migr", 
"Migr", "Migr", "Migr", "Migr", "OcRes", "Migr", "Migr", "Migr", 
"Migr", "Migr", "Migr", "Migr", "Migr", "Migr", "Migr", "Migr", 
"Migr", "EstRes", "Migr", "Migr", "Migr", "Migr", "Migr", "Migr", 
"Migr", "Migr", "Migr", "Migr", "Migr", "Migr", "Migr", "Migr", 
"Migr", "Migr", "Migr", "EstRes", "Migr", "Migr", "Migr", "EstRes", 
"Migr", "OcRes", "Migr", "EstRes", "Migr", "Migr", "Migr", "Migr", 
"Migr", "Migr", "Migr", "Migr", "Migr", "Migr")), class = "data.frame", row.names = c(NA, 
-72L))

I want to reduce the data for 5-year-olds from 2018 only, and create a new column with EstRes (Estuary) and OcRes (Ocean Residents) renamed as Resident, and all others renamed as Migratory; so I can then plot and compare the average lengths (cm) of Residents versus Migrants. I think I am close but not quite there. Any assistance would be greatly appreciated.

avlen<-combo1 %>% 
      filter(Age_Year%in%5) %>%
      filter(Sample.Year%in%2018) %>% 
      droplevels() %>% 
      mutate(TacticB = case_when(Tactic = EstRes ~ Resident, Tactic = OcRes ~ Resident, TRUE ~ 'Migratory'))
      group_by(TacticB) %>% 
      summarise(avlen=mean(Length_cm), stdev=sd(Length_cm))
avlen

This is edited in from the comment:

avlen <-combo1 %>% filter(Age_Year%in%5) %>% 
      filter(Sample.Year%in%2018) %>% droplevels() %>% 
      mutate(TacticB = case_when(Tactic == "EstRes" ~ Resident, 
               Tactic == "OcRes" ~ Resident, 
               TRUE ~ as.character("Migratory"))%>% 
      group_by(TacticB) %>% 
      summarise(avlen=mean(Length_cm), stdev=sd(Length_cm))%>% 
      avlen   # and the editor is guessing that final `%>%` is not correct.

CodePudding user response：

Do you mean this? I'm not sure that your sample data do not including many variables.

combo1 %>%
  filter(Age_Year == 5, Sample.Year == 2018) %>%
  mutate(TacticB = ifelse(Tactic %in% c("EstRes", "OcRes"), "Resident", "Migratory")) %>%
  group_by(TacticB) %>% 
  summarise(avlen=mean(Length_cm), stdev=sd(Length_cm))