return FALSE; $r = well_tag_thread__update(array('id' => $id), $update); return $r; } function well_tag_thread_find($tagid, $page, $pagesize) { $arr = well_tag_thread__find(array('tagid' => $tagid), array('id' => -1), $page, $pagesize); return $arr; } function well_tag_thread_find_by_tid($tid, $page, $pagesize) { $arr = well_tag_thread__find(array('tid' => $tid), array(), $page, $pagesize); return $arr; } ?>r - How to find the date a categorical variable was last active? - Stack Overflow

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    r - How to find the date a categorical variable was last active? - Stack Overflow

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    I have this data fram and I want to create an additional column that tells me the date the category was previously active.

    DF <- data.frame(
  Date = rep(c("10-12-2024", "10-17-2024", "10-19-2024"), c(4L, 2L, 2L)),
  category = c("Red", "Red", "Blue", "Blue", "Blue", "Blue", "Red", "Blue")
)

    Output:

    Date category
    10-12-2024 Red
    10-12-2024 Red
    10-12-2024 Blue
    10-12-2024 Blue
    10-17-2024 Blue
    10-17-2024 Blue
    10-19-2024 Red
    10-19-2024 Blue

    I have this data fram and I want to create an additional column that tells me the date the category was previously active.

    DF <- data.frame(
  Date = rep(c("10-12-2024", "10-17-2024", "10-19-2024"), c(4L, 2L, 2L)),
  category = c("Red", "Red", "Blue", "Blue", "Blue", "Blue", "Red", "Blue")
)

    Output:

    Date category
    10-12-2024 Red
    10-12-2024 Red
    10-12-2024 Blue
    10-12-2024 Blue
    10-17-2024 Blue
    10-17-2024 Blue
    10-19-2024 Red
    10-19-2024 Blue

    So I would like a 3rd column of Previous active day for that category. I'm expecting the output to look like this:

    Date category previous active day
    10-12-2024 Red
    10-12-2024 Red
    10-12-2024 Blue
    10-12-2024 Blue
    10-17-2024 Blue 10-12-2024
    10-17-2024 Blue 10-12-2024
    10-19-2024 Red 10-12-2024
    10-19-2024 Blue 10-17-2024
    • r
    • dplyr
    • categorical-data
    Share Improve this question asked Jan 31 at 13:54 FPiperFPiper 831 silver badge3 bronze badges 3
    • Could you edit your question to include the code you attempted and why it didnt work? Its easier to help (and for you to proceed independently) if we build off of your current framework – jpsmith Commented Jan 31 at 13:59
    • 1 This appears to be a variation of with(DF, ave(Date, category, FUN = \(x) c(rep("", 1), head(x, -1)))) which is a simple lag by group-variable. You will find tons of answer to questions like those. I currently have no time to search for dupes, but there will be quite a few. What have you searched? Did you try adapt one? You might need to wrap some sort of consecutive_id() if you do not want entries if category is replicated. – Friede Commented Jan 31 at 14:00
    • 1 I answered this in a comment in your prior post. stackoverflow/questions/79355614/… – G. Grothendieck Commented Jan 31 at 14:18
    Add a comment  | 

    1 Answer 1

    Reset to default 1

    I would group by category and date then take the first entry - this identifies unique dates that each category was active. Then, lag the date variable by group and merge it back into the original data.

    library(dplyr)
DF <- data.frame(
  Date = rep(c("10-12-2024", "10-17-2024", "10-19-2024"), c(4L, 2L, 2L)),
  category = c("Red", "Red", "Blue", "Blue", "Blue", "Blue", "Red", "Blue")
)

DF %>% 
  group_by(Date, category) %>% 
  slice_head(n=1) %>% 
  group_by(category) %>% 
  mutate(previous_active_date = lag(Date)) %>% 
  right_join(DF)
#> Joining with `by = join_by(Date, category)`
#> # A tibble: 8 × 3
#> # Groups:   category [2]
#>   Date       category previous_active_date
#>   <chr>      <chr>    <chr>               
#> 1 10-12-2024 Blue     <NA>                
#> 2 10-12-2024 Blue     <NA>                
#> 3 10-12-2024 Red      <NA>                
#> 4 10-12-2024 Red      <NA>                
#> 5 10-17-2024 Blue     10-12-2024          
#> 6 10-17-2024 Blue     10-12-2024          
#> 7 10-19-2024 Blue     10-17-2024          
#> 8 10-19-2024 Red      10-12-2024

    Created on 2025-01-31 with reprex v2.1.1

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