dplyr if else without the else/ conditional mutate in one chunk

I am trying to add a column to my dataframe based on if a string is detected in another column. I have done this in two chunks of code and then merged them together, but I am trying to streamline my code so that there is less to type out in the future. I also noticed I performed a join incorrectly on a dataset I've been working with for months, so the fewers joins, the better.

Here is what currently works for me, but feels unnecessarily long.

dtc_final2022<- dtc_final1 %>% 
  filter (str_detect(detection_timestamp_utc, "2022")) %>%
  mutate(Year = "2022") 

dtc_final2021 <-  dtc_final1 %>% 
  filter (str_detect(detection_timestamp_utc, "2021")) %>%
  mutate(Year = "2021")

dtc_final2 <- full_join(dtc_final2021, dtc_final2022)

dtc_final1 is a dataset with timestamps from many years. I am only interested in adding a "year" to timestamps that contain 2021 and 2022. In the future, I will add 2023 and 2024.

This is what I would like to do, but in doing so, I replace the previous year with NA. Is there a way to run an ifelse function without the 'else'? Also, please remember that I cant use the other year as the 'else' since in the future, I will have 4 years to deal with, and not just 2.

dtc_final2 <- dtc_final1 %>%
  mutate(Year = ifelse(str_detect(detection_timestamp_utc, "2021"), "2021", NA),
         Year = ifelse(str_detect(detection_timestamp_utc, "2022"), "2022", NA))

I try to do everyling in dplyr but if a for loop does the trick, then I guess I'll buck up.

Thanks in advance!

For multiple sequential/nested ifelses, we can use case_when.

dtc_final2 <- dtc_final1 %>% 
    mutate(Year = case_when(str_detect(detection_timestamp_utc, "2021") ~ 2021,
                            str_detect(detection_timestamp_utc, "2022") ~ 2022,
                            TRUE ~ NA)

There are likely better options for this specific case, hard to tell without seeing the data.
if detection_timestamp_utc is a proper date object, we likely hava a better way with the lubridate package.

dtc_final2 <- dtc_final1 %>% 
    mutate(Year = lubidate::year(as.Date(detection_timestamp_utc)))

</details>



# 答案2
**得分**: 1

使用`str_extract()`而不是`str_detect()`，并使用一个正则表达式来捕获感兴趣的两个年份：

```R
mutate(dtc_final1, Year=str_extract(detection_timestamp_utc, "^202[12]"))

mutate(dtc_final1, Year=str_extract(detection_timestamp_utc, "^202[12]"))