find similar row index in 2 dataframe in R-CodePudding

Here is my test dataset :

test
        date app count
1 21-10-18   A     2
2 21-10-19   A     3
3 21-10-23   A     5
4 21-10-19   B     2
5 21-10-24   B     3

I would like to group the data based on app column and replace the latest date by sys.Date in the date column. I could get the latest date per app by :

latest_date <- test %>% group_by(app)%>%slice(n())

latest_date 
# A tibble: 2 x 3
# Groups:   app [2]
  date       app   count
  <date>     <chr> <int>
1 21-10-23 A         5
2 21-10-24 B         3

How could I find the row indexes in test dataset which are match with the rows in latest_date ? (which (test == latest_date)) ????

what I need at the end is :

        date app count
1 21-10-18   A     2
2 21-10-19   A     3
3 21-12-13   A     5
4 21-10-19   B     2
5 21-12-13   B     3

CodePudding user response：

Use replace after doing a group by 'app'

library(dplyr)
library(lubridate)
test %>% 
   mutate(date = ymd(date)) %>%
   group_by(app) %>% 
   mutate(date = replace(date, which.max(date), Sys.Date())) %>%
   ungroup

-output

# A tibble: 5 × 3
  date       app   count
  <date>     <chr> <int>
1 2021-10-18 A         2
2 2021-10-19 A         3
3 2021-12-13 A         5
4 2021-10-19 B         2
5 2021-12-13 B         3

data

test <- structure(list(date = c("21-10-18", "21-10-19", "21-10-23", "21-10-19", 
"21-10-24"), app = c("A", "A", "A", "B", "B"), count = c(2L, 
3L, 5L, 2L, 3L)), class = "data.frame", row.names = c("1", "2", 
"3", "4", "5"))