I'm relatively new to R and running into a problem I can't seem to solve. My apologies if this question has been asked before, but answers related to 'finding lowest' I'm running into here seem to focus on extracting the lowest value, I haven't found much about using it as a condition to add new values to a column.
A simplified example of what I'm trying to achieve is below. I have a list of building names and the years they have been in use, and I want to add to the column first_year "yes" and "no" depending on if the year the building is in use is the first year or not.
building_name year_inuse first_year
office 2020 yes
office 2021 no
office 2022 no
office 2023 no
house 2020 yes
house 2021 no
house 2022 no
house 2023 no
retail 2020 yes
retail 2021 no
retail 2022 no
retail 2023 no
I grouped the data by the building names, and now I'm thinking about doing something like:
data_new <- data %>% mutate(first_year = if_else(...., "yes", "no"))
so add a condition in the if_else that tests if the year is the lowest from the group, and if so add a yes, otherwise add a no. However, I can't seem to figure out how to do this and if this is even the best approach.
Help is much appreciated.
If the 'year_inuse' is not ordered, use arrange before doing this i.e. arrange by 'building_name', 'year_inuse', create a logical vector with duplicated, convert it to numeric index (1 + ), then use that index to replace with a vector of values i.e. 'yes', 'no'
library(dplyr)
data_new <- data %>%
arrange(building_name, year_inuse) %>%
mutate(first_year = c("no", "yes")[1 + !duplicated(building_name)])
-ouptut
# building_name year_inuse first_year
#1 house 2020 yes
#2 house 2021 no
#3 house 2022 no
#4 house 2023 no
#5 office 2020 yes
#6 office 2021 no
#7 office 2022 no
#8 office 2023 no
#9 retail 2020 yes
#10 retail 2021 no
#11 retail 2022 no
#12 retail 2023 no
data <- structure(list(building_name = c("office", "office", "office",
"office", "house", "house", "house", "house", "retail", "retail",
"retail", "retail"), year_inuse = c(2020L, 2021L, 2022L, 2023L,
2020L, 2021L, 2022L, 2023L, 2020L, 2021L, 2022L, 2023L)),
row.names = c(NA,
-12L), class = "data.frame")