Filter grouped data by partial string specified in another column

I want to filter grouped data using either a.) a partial string specified in another column, or if easier, b.) a partial string which I specify in the code.

I have the following data frame:

  df <- structure(list(
  sen = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), 
  trial = c("standard", "standard", "standard", "standard", "standard", "silence", "silence", "silence", "silence", "silence", "deviant", "deviant", "deviant", "deviant", "deviant","standard", "standard", "standard", "standard", "standard", "silence", "silence", "silence", "silence", "silence", "deviant", "deviant", "deviant", "deviant", "deviant"),
  ppt = c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3), 
  ia_label = c("The_TW1", "cow_TW2", "jumped_TW3", "the_TW4", "gate_TW5","The_TW1", "cow_TW2", "jumped_TW3", "the_TW4", "gate_TW5", "The_TW1", "cow_TW2", "jumped_TW3", "the_TW4", "gate_TW5", "The_TW1", "cow_TW2", "jumped_TW3", "the_TW4", "gate_TW5","The_TW1", "cow_TW2", "jumped_TW3", "the_TW4", "gate_TW5", "The_TW1", "cow_TW2", "jumped_TW3", "the_TW4", "gate_TW5"), 
  target_pos = c("0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "TW3", "TW3", "TW3", "TW3", "TW3", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "TW4", "TW4", "TW4", "TW4", "TW4")),
  .Names = c("sen","trial","ppt","ia_label","target_pos"),
  row.names = c(NA, -30L),
  class = "data.frame")

sen	trial	ppt	ia_label	target_pos
1	standard	1	The_TW1	0
1	standard	1	cow_TW2	0
1	standard	1	jumped_TW3	0
1	standard	1	the_TW4	0
1	standard	1	gate_TW5	0
1	silence	2	The_TW1	0
1	silence	2	cow_TW2	0
1	silence	2	jumped_TW3	0
1	silence	2	the_TW4	0
1	silence	2	gate_TW5	0
1	deviant	3	The_TW1	TW3
1	deviant	3	cow_TW2	TW3
1	deviant	3	jumped_TW3	TW3
1	deviant	3	the_TW4	TW3
1	deviant	3	gate_TW5	TW3
2	standard	1	The_TW1	0
2	standard	1	cow_TW2	0
2	standard	1	jumped_TW3	0
2	standard	1	the_TW4	0
2	standard	1	gate_TW5	0
2	silence	2	The_TW1	0
2	silence	2	cow_TW2	0
2	silence	2	jumped_TW3	0
2	silence	2	the_TW4	0
2	silence	2	gate_TW5	0
2	deviant	3	The_TW1	TW4
2	deviant	3	cow_TW2	TW4
2	deviant	3	jumped_TW3	TW4
2	deviant	3	the_TW4	TW4
2	deviant	3	gate_TW5	TW4

and I want to filter the data frame by 'ia_label's that contain the string specified in the target_pos for deviant conditions (either tw3 or tw4) - but I want to group this by 'sen' - so for all of sen = 1, I want to keep only the rows with ia_label containing _TW3, and for sen = 2 I want to keep only the rows with ia_label containing _TW4:

sen	trial	ppt	ia_label	target_pos
1	standard	1	jumped_TW3	0
1	silence	2	jumped_TW3	0
1	deviant	3	jumped_TW3	TW3
2	standard	1	the_TW4	0
2	silence	2	the_TW4	0
2	deviant	3	the_TW4	TW4

I only have a small number of different strings that I need to filter by, so I don't mind running this manually by specifying the partial string I want to filter 'ia_label' by, if it isn't possible to filter each group by the partial string specified within the 'target_pos' column.

I have tried using the following code using group_by, filter and grepl but I receive the error below:

library(dplyr)
Df2 <- df %>% 
  group_by(sen) %>%
  filter(df, grepl("TW3",ia_label))

Output:

Error: Problem with filter() input ..1. x Input ..1 must be of size 15 or 1, not size 30. i Input ..1 is df. i The error occurred in group 1: sen = 1. Run rlang::last_error() to see where the error occurred.

Solution

The error is because you are both piping df into filter and specifying it inside filter. It will avoid the error if you change filter(df, grepl(... to filter(grepl(....

df %>%
  group_by(sen) %>% 
  filter(grepl("TW3", ia_label))

To do this for the first target_pos value corresponding to a trial == "deviant" by group, do this:

df %>% 
  group_by(sen) %>%
  filter(grepl(
    pattern = first(target_pos[trial == "deviant"]),
    x = ia_label
  ))
# # A tibble: 6 × 5
# # Groups:   sen [2]
#     sen trial      ppt ia_label   target_pos
#   <dbl> <chr>    <dbl> <chr>      <chr>     
# 1     1 standard     1 jumped_TW3 0         
# 2     1 silence      2 jumped_TW3 0         
# 3     1 deviant      3 jumped_TW3 TW3       
# 4     2 standard     1 the_TW4    0         
# 5     2 silence      2 the_TW4    0         
# 6     2 deviant      3 the_TW4    TW4