Conditional Mutating using specific identifiers in a data frame-CodePudding

I have a dataset that employs a similar approach to this one.

ID <- c(4,5,6,7,3,8,9)
quantity <- c(20,300, 350, 21, 44, 20, 230)
measurementvalue <- c("tin", "kg","kg","tin","tin","tin","kg")
kgs <- c(21,12, 30,23,33,11,24)

DF <- data.frame(ID, quantity, measurementvalue)

My standard way of deriving a new column totalkgs using conditional mutating is the code below.

DF <- DF %>%
  mutate(totalkgs = 
           ifelse(quantity == "tin", quantity * 5, 
                  ifelse(quantity =="kg", quantity*1, quantity)))

However, the dataset had erroneous entries in the column quantity so I'd like to perform a division on those specific identifiers. All the final values of both the multiplication and division should be store in the column totalkgs. How do I go about this?

Let's assume the id's with the error data are 3,5,9,7. and I'd like to divide the values found in the column quantity with 10.

CodePudding user response：

You could use case_when:

ID <- c(4,5,6,7,3,8,9)
quantity <- c(20,300, 350, 21, 44, 20, 230)
measurementvalue <- c("tin", "kg","kg","tin","tin","tin","kg")
kgs <- c(21,12, 30,23,33,11,24)
DF <- data.frame(ID, quantity, measurementvalue)

library(dplyr)
DF %>%
  mutate(quantity2 = ifelse(ID %in% c(3,5,9,7), quantity/10, quantity)) %>%
  mutate(totalkgs = case_when(measurementvalue == "tin" ~ quantity2 * 5,
                              measurementvalue == "kg" ~ quantity2 * 1, 
                              TRUE ~ quantity2)) %>%
  select(-quantity2) #if you want
#>   ID quantity measurementvalue totalkgs
#> 1  4       20              tin    100.0
#> 2  5      300               kg     30.0
#> 3  6      350               kg    350.0
#> 4  7       21              tin     10.5
#> 5  3       44              tin     22.0
#> 6  8       20              tin    100.0
#> 7  9      230               kg     23.0

^{Created on 2022-07-05 by the reprex package (v2.0.1)}