Add incremental values based on row numbers in tidyverse?-CodePudding

I have this tibble:

tibble(country = c("USA","USA","USA","USA","CHINA","CHINA","CHINA","CHINA","SPAIN","SPAIN","SPAIN","SPAIN"), 
       values = c(10,20,100,30,60,70,80,90,100,20,100,90))

how can i make the following column - the condition is population column starts at value 1 and increments by 1, when the values == 100, it resets to the value 1 and increment starts again - see last example SPAIN where the change happens twice.

So final tibble is:

tibble(country = c("USA","USA","USA","USA","CHINA","CHINA","CHINA","CHINA","SPAIN","SPAIN","SPAIN","SPAIN"), 
       values = c(10,20,100,30,60,70,80,90,100,20,100,90), 
       population = c(1,2,1,2,1,2,3,4,1,2,1,2))

Any help given thanks

CodePudding user response：

We could use rowid on the 'country' and the cumulative sum of logical vector

library(dplyr)
library(data.table)
df1 %>%
    mutate(population = rowid(country, cumsum(values == 100)))

-output

# A tibble: 12 × 3
   country values population
   <chr>    <dbl>      <int>
 1 USA         10          1
 2 USA         20          2
 3 USA        100          1
 4 USA         30          2
 5 CHINA       60          1
 6 CHINA       70          2
 7 CHINA       80          3
 8 CHINA       90          4
 9 SPAIN      100          1
10 SPAIN       20          2
11 SPAIN      100          1
12 SPAIN       90          2

CodePudding user response：

Slightly different approach from akrun but same logic:

library(dplyr)

df %>% 
  group_by(country, id_Group =cumsum(values == 100) 1) %>% 
  mutate(population = row_number(), .keep="used")

   country id_Group population
   <chr>      <dbl>      <int>
 1 USA            1          1
 2 USA            1          2
 3 USA            2          1
 4 USA            2          2
 5 CHINA          2          1
 6 CHINA          2          2
 7 CHINA          2          3
 8 CHINA          2          4
 9 SPAIN          3          1
10 SPAIN          3          2
11 SPAIN          4          1
12 SPAIN          4          2