Using case_when to categorize a variable by date ranges?

Question

I currently have a list of transactions and I would like to add a categorical value to each of them depending on the age of the transaction. Sample Data:

Date    Transaction 
9/2/2020    44
8/29/2020   65.3
8/29/2020   34
8/29/2020   195
8/28/2020   180
8/28/2020   195
8/28/2020   48
8/27/2020   195
8/27/2020   65.3
8/27/2020   77

Pseudocode:

today<- lubridate::day(Sys.Date())
mutate(Age= case_when(
                         Date between(today, today -7) ~ "< Week Old",
                         Date between(today, today -30) ~ "30days Old",
                         Date between(today, today -60) ~ "60days Old",
                         Date >= between(today, today -90) ~ "90days+ Old"))

Is it possible to filter data in a mutate using between for date ranges?

#Currently familiarizing and exploring the cut suggestion, thanks

What is your actual question or what is wrong with your current code? — Tim Biegeleisen, Sep 02 '20 at 07:12
If that is the best approach since it is not generating the column in the current state :/ — Raul, Sep 02 '20 at 07:14
@Sotos I need to familiarize my self with cut, I've read a bit on it but don't quite get it that's why I went with using today and subtracting the days — Raul, Sep 02 '20 at 07:18
Ok, I reopened. Maybe add an attempt with `cut` so we can see where you are having difficulty — Sotos, Sep 02 '20 at 07:21

score 2 · Accepted Answer · answered Sep 02 '20 at 07:32

2

Your first try with case_when was a good idea. But you used the between and day function not in the right way. Maybe try this:

today <- lubridate::today()

df %>% 
  mutate(Age = case_when(
   between(Date, today-7, today) ~ "< Week Old",
   between(Date, today-30, today) ~ "30days Old",
   between(Date, today-60, today) ~ "60days Old",
   TRUE ~ "90days+ Old"))

answered Sep 02 '20 at 07:32

tamtam

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Im glad to see that I was close, thanks for the pointer! – Raul Sep 02 '20 at 11:53

Using case_when to categorize a variable by date ranges?

1 Answers1