R: Change value to NA in one column if in another column the datapoint is also NA-CodePudding

I have the following data:

structure(list(Name = c("A", "A", "A", "A", "A", "A", "B", "B", 
"B", "B", "B", "B", "C", "C", "C", "C", "C", "C"), Date = c("01.09.2018", 
"02.09.2018", "03.09.2018", "05.11.2021", "06.11.2021", "07.11.2021", 
"01.09.2018", "02.09.2018", "03.09.2018", "05.11.2021", "06.11.2021", 
"07.11.2021", "01.09.2018", "02.09.2018", "03.09.2018", "05.11.2021", 
"06.11.2021", "07.11.2021"), Category = c(1L, 1L, NA, NA, 2L, 
2L, 3L, 3L, 3L, NA, NA, 4L, 4L, 2L, NA, 2L, 2L, NA), Size = c(34L, 
23L, 12L, 53L, 23L, 53L, 23L, 54L, 65L, 75L, 67L, 45L, 45L, 23L, 
23L, 12L, 12L, NA), Sum_Size = c(34L, 23L, 35L, 128L, 35L, 53L, 
23L, 54L, 65L, 128L, 67L, 45L, 45L, 23L, 35L, 12L, 35L, NA)), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -18L), groups = structure(list(
    Category = c(1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 
    NA, NA, NA, NA), Date = c("01.09.2018", "02.09.2018", "02.09.2018", 
    "05.11.2021", "06.11.2021", "07.11.2021", "01.09.2018", "02.09.2018", 
    "03.09.2018", "01.09.2018", "07.11.2021", "03.09.2018", "05.11.2021", 
    "06.11.2021", "07.11.2021"), .rows = structure(list(1L, 2L, 
        14L, 16L, c(5L, 17L), 6L, 7L, 8L, 9L, 13L, 12L, c(3L, 
        15L), c(4L, 10L), 11L, 18L), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -15L), .drop = TRUE))

How can I change the data in column "Sum_Size" to NA if in the column "Category" there is also NA? So for instance, in row 3, "Sum_Size" should be NA.

I really appreciate any help!

CodePudding user response：

Here is a possible solution using an ifelse statement:

library(dplyr)

df %>% 
  mutate(Sum_Size= ifelse(is.na(Category), NA_real_, Sum_Size))

   Name  Date       Category  Size Sum_Size
   <chr> <chr>         <int> <int>    <dbl>
 1 A     01.09.2018        1    34       34
 2 A     02.09.2018        1    23       23
 3 A     03.09.2018       NA    12       NA
 4 A     05.11.2021       NA    53       NA
 5 A     06.11.2021        2    23       35
 6 A     07.11.2021        2    53       53
 7 B     01.09.2018        3    23       23
 8 B     02.09.2018        3    54       54
 9 B     03.09.2018        3    65       65
10 B     05.11.2021       NA    75       NA
11 B     06.11.2021       NA    67       NA
12 B     07.11.2021        4    45       45
13 C     01.09.2018        4    45       45
14 C     02.09.2018        2    23       23
15 C     03.09.2018       NA    23       NA
16 C     05.11.2021        2    12       12
17 C     06.11.2021        2    12       35
18 C     07.11.2021       NA    NA       NA