how to change conditionally row values when under column with specific header name-CodePudding

I have a dataset like the following one:

ProszęAveryextendedname <- c("A","A","A","A","B","B","B")
var2 <- c("B","B","B","B","B","B","B")
var3 <- c("B","B","B","B","B","B","B")

ProszęBveryextendedname <- c("A","A","A","A","B","B","B")
var5 <- c("B","B","B","B","B","B","B")
var6 <- c("B","B","B","B","B","B","B")

df <- data.frame(ProszęAveryextendedname , var2, var3, ProszęBveryextendedname, var5, var6)

please just to the special alphabet case, as long as possible. What I would like to do is to create a code so that every time under the column that has in its name head the word 'Proszę', there is a row with value 'A', the adjacent rows should have a NA value. How would it be possible to make this with a tidyverse, iterative function or via a loop?

I would like to add the small example of this

structure(list(`Prosze podac, ile godzin dziennie sluchasz zazwyczaj tresci AUDIO wymienione wyzej, BEZ PRZERYWANIA INNA AKTYWNOSCIA. 
` = c("nigdy", 
"okolo 1-2 godzin", "okolo 1-2 godzin", "mniej niz 1 godzine", 
"okolo 1-2 godzin"), `ogladanie tresci video, w tym granie w gry video, itp....19` = c("nigdy", 
"nigdy", "mniej niz 1 godzine", "nigdy", "nigdy"), `sluchanie muzyki, audycji radiowych, podcastów, audiobooków, itp.2` = c("nigdy", 
"okolo 1-2 godzin", "okolo 3- 4 godzin", "mniej niz 1 godzine", 
"nigdy"), `czytanie lub wykonywanie zadan zwiazanych ze szkola/studiami, itp.` = c("nigdy", 
"nigdy", "okolo 1-2 godzin", "mniej niz 1 godzine", "okolo 3- 4 godzin"
), `pisanie e-maili lub wysylanie postów w social mediach, itp.` = c("nigdy", 
"nigdy", "mniej niz 1 godzine", "mniej niz 1 godzine", "okolo 1-2 godzin"
)), row.names = c(NA, -5L), class = c("tbl_df", "tbl", "data.frame"
))

the solution that I would like to achieve is described above this the sample dataset

EXPECTED OUTCOME

Prosze podac, ile godzin dziennie sluchasz zazwyczaj tresci AUDIO wymienione wyzej, BEZ PRZERYWANIA INNA AKTYWNOSCIA.~1 oglad~2 sluch~3 czyta~4
  <chr>                                                                                                                   <chr>   <chr>   <chr>  
1 nigdy                                                                                                                   NA      NA       NA
2 okolo 1-2 godzin                                                                                                        nigdy   okolo ~ nigdy  
3 okolo 1-2 godzin                                                                                                        mniej ~ okolo ~ okolo ~
4 mniej niz 1 godzine                                                                                                     nigdy   mniej ~ mniej ~
5 okolo 1-2 godzin                                                                                                        nigdy   nigdy   okolo ~

SIMPLEST EXPECTED OUTCOME

  ProszeAveryextendedname var2 var3     ProszeBveryextendedname var5 var6
1                       A    NA    NA                       A    NA    NA
2                       A    NA    NA                       A    NA    NA
3                       A    NA    NA                       A    NA    NA
4                       A    NA    NA                       A    NA    NA
5                       B    B    B                         B    B      B
6                       B    B    B                         B    B      B
7                       B    B    B                         B    B      B

CodePudding user response：

library(dplyr)
library(purrr)
ind <- grepl("Proszę", names(df));
purrr::map_dfc(split.default(df, cumsum(ind)), 
 ~ .x %>% mutate(across(-1, 
    ~ replace(.x, cur_data()[[1]] == "A", NA))))

-output

  ProszęAveryextendedname var2 var3 ProszęBveryextendedname var5 var6
1                       A <NA> <NA>                       A <NA> <NA>
2                       A <NA> <NA>                       A <NA> <NA>
3                       A <NA> <NA>                       A <NA> <NA>
4                       A <NA> <NA>                       A <NA> <NA>
5                       B    B    B                       B    B    B
6                       B    B    B                       B    B    B
7                       B    B    B                       B    B    B