Set Preceding and Succeeding rows-CodePudding

I want all the values in column values prior to string "%" should be flagged as "YES". Else "NO". It should be checked by each unique values of column Id.

df=data.frame('Id'=c(101,101,101,101,102,102,102,102),
              'values'=c('a','%','a','c','a','d','%','c'))

All the preceding rows should be flagged as "YES". For example, In Id = 102, YES should be appeared against values "a", "d".

CodePudding user response：

With dplyr you can use lead in conjunction with a vector of values YES and NO. This assumes you only have one % per group. It does not search for last occurrence of %.

library(dplyr)

df %>% 
  group_by(Id) %>% 
  mutate(flag=values=="%", flag=c("YES", "NO")[cumsum(flag) 1]) %>% 
  ungroup()
# A tibble: 8 × 3
     Id values flag 
  <dbl> <chr>  <chr>
1   101 a      YES  
2   101 %      NO   
3   101 a      NO   
4   101 c      NO   
5   102 a      YES  
6   102 d      YES  
7   102 %      NO   
8   102 c      NO

CodePudding user response：

With tidyverse, we can use str_detect with lead to determine if % is the next value, and if so, then return 1 and if not, NA. Then, we can group by Id and use fill to add 1 to the previous rows. Then, we can convert to YES and NO.

library(tidyverse)

df %>% 
  mutate(flag = ifelse(str_detect(lead(values), "%"), 1, NA)) %>% 
  group_by(Id) %>% 
  fill(flag, .direction = "up") %>% 
  mutate(flag = ifelse(is.na(flag), "NO", "YES"))

     Id values flag 
  <dbl> <chr>  <chr>
1   101 a      YES  
2   101 %      NO   
3   101 a      NO   
4   101 c      NO   
5   102 a      YES  
6   102 d      YES  
7   102 %      NO   
8   102 c      NO