Group_by - retain rows based on value in below row of dataset - r

Question

Hi I am looking to retain rows in a dataset similar to the below:
ID
Value1
Value2
A
1
0
A
0
1
A
1
1
A
0
1
A
0
0
A
0
0
A
1
0
A
1
1
A
0
1
Where 'Value1' = 1 and 'Value2' in the immediate below row = 1. Under these conditions both rows should be retained; any other rows corresponding to ID 'A' should not be retained. Can anyone help with this please? In this example the below output should be returned:
ID
Value1
Value2
A
1
0
A
0
1
A
1
1
A
0
1
A
1
0
A
1
1
A
0
1

Answer 1

The logic is keep all the rows where row before has Value1=1 and row immediately after has Value2=1. I've added a few rows to your data to check different scenarios.
df=structure(list(ID = c("A", "A", "A", "A", "A", "A", "A", "A",
"A"), Value1 = c(1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L), Value2 = c(0L,
1L, 0L, 0L, 0L, 1L, 0L, 1L, 1L)), class = "data.frame", row.names = c(NA,
-9L))
ID Value1 Value2
1 A 1 0
2 A 0 1
3 A 0 0
4 A 1 0
5 A 0 0
6 A 0 1
7 A 1 0
8 A 0 1
9 A 0 1
edit: your edit requires you to distinguish between 1's in Value1 and Value2 columns, there are probably a number of options available here, one option is to say that if Value=1 then this starts a new sequence, so the next row needs to have Value2=1 and Value1!=1.
tmp=which((df$Value1==1)+c(tail(df$Value1!=1 & df$Value2==1,-1),NA)==2)
df[sort(c(tmp,tmp+1)),]
ID Value1 Value2
1 A 1 0
2 A 0 1
7 A 1 0
8 A 0 1
note the row names/indices.

Answer 2

You can try
library(dplyr)
inds <- df |> summarise(n = which(Value1 == 1 & c(Value2[2:n()] , 0) == 1))
df |> slice(unlist(Map(c , inds$n , inds$n + 1)))
data
ID Value1 Value2
1 A 1 0
2 A 0 1
3 A 1 0
4 A 0 1