Counting the amount of times a value appears per subjectid-CodePudding

I have a dataframe like so:

subjectid <- c(1, 1, 1, 2, 2, 3, 3, 3, 4, 4, 5)
response <- c("PD", "PD", "SD", "PD", "SD", "PD", "SD", "SD", "SD", "PD", "PR")
df <- data.frame(subjectid, response)

initial image

I want to count the amount of times PD SD and PR occurs per subjectid. So for subject 1 the first time PD occurs I want the value 1. The second time it occurs for subjectid = 1, I want the value 2. The catch is I want it to restart at 1 for subjectid 2. for the first time PD occurs for subjectid = 2 I want the value 1. I also want my new value variable to paste in the response before the number. My desired output is as follows:

final product

Any help would be much apricated!

CodePudding user response：

dplyr

library(dplyr)
df %>%
  group_by(subjectid, response) %>%
  mutate(value = paste(response, row_number())) %>%
  ungroup()
# # A tibble: 11 x 3
#    subjectid response value
#        <dbl> <chr>    <chr>
#  1         1 PD       PD 1 
#  2         1 PD       PD 2 
#  3         1 SD       SD 1 
#  4         2 PD       PD 1 
#  5         2 SD       SD 1 
#  6         3 PD       PD 1 
#  7         3 SD       SD 1 
#  8         3 SD       SD 2 
#  9         4 SD       SD 1 
# 10         4 PD       PD 1 
# 11         5 PR       PR 1

data.table

library(data.table)
DT <- as.data.table(df) # canonical method is setDF(df)
DT[, value := paste(response, rowid(subjectid, response))]

base R

df$value <- ave(df$response, df[c("subjectid", "response")],
                FUN = function(z) paste(z, seq_along(z)))

CodePudding user response：

Try this

library(dplyr)

df |> group_by(subjectid, response) |>
    mutate(value = paste0(response ," ", 1:n())) |>
    ungroup()

output

# A tibble: 11 × 3
   subjectid response value
       <dbl> <chr>    <chr>
 1         1 PD       PD 1 
 2         1 PD       PD 2 
 3         1 SD       SD 1 
 4         2 PD       PD 1 
 5         2 SD       SD 1 
 6         3 PD       PD 1 
 7         3 SD       SD 1 
 8         3 SD       SD 2 
 9         4 SD       SD 1 
10         4 PD       PD 1 
11         5 PR       PR 1