New column conditional on whether number is even/uneven and on column - r

Question

Say i have the following df:
id<-rep(1:2,c(7,6))
name<-c('a','t','signal','b','s','e','signal','x','signal','r','s','t','signal')
id name
1 1 a
2 1 t
3 1 signal
4 1 b
5 1 s
6 1 e
7 1 signal
8 2 x
9 2 signal
10 2 r
11 2 s
12 2 t
13 2 signal
I want to add a new column with a character value conditional on whether the id number is even or not, and whether the string 'signal' is reached in the 'name' column.
For uneven id numbers, and up to including 'signal' for the column 'name' I would like the character T. After the signal, the character should become 'C'.
For even id numbers, and up to including 'signal' for the column 'name' I would like the character C. After the signal, the character should become 'T'.
For the example given, this should result in the following data.frame:
id, name condition
1, a, T
1, t, T
1, signal, T
1, b, C
1, s, C
1, e, C
1, signal C
2, x, C
2, signal, C
2, r, T
2, s, T
2, t, T
2, signal T
Any help is very much appreciated!

Answer 1

This is not a vectorized solution, but for me it seems as a wroking code.
Data preparation - I add new column to describe the condition
id<-rep(1:2,c(7,6))
name<-c('a','t','signal','b','s','e','signal','x','signal','r','s','t','signal')
df <- data.frame(id, name)
df$condition <- rep("X", nrow(df))
I need to control two states: (i) if the signal has switched; (ii) if the id changes last (from even to odd and other way). Then I read row by row and update the condition state along with two variables.
signal <- F
last <- 1
for (i in 1:nrow(df)){
# id changed - reset signal
if (last != (df[i, "id"] %% 2)) signal <- F
if(!signal){
df[i,"condition"] <- ifelse(df[i,"id"] %% 2, "T", "C")
} else {
df[i, "condition"] <- ifelse(df[i,"id"] %% 2, "C", "T")
}
# signal is on
if (df[i, "name"] == "signal") signal <- T
# save last id (even or odd)
last <- df[i, "id"] %% 2
}
I hope it helps.

Answer 2

We could make use of %% with == to create the column
library(dplyr)
df1 %>%
group_by(id) %>%
mutate(ind = (cumsum(lag(name, default = name[1]) == 'signal')>0) + 1,
condition = c('T', 'C')[ifelse(id %%2 > 0, ind,
as.integer(factor(ind, levels = rev(unique(ind)))))] ) %>%
select(-ind)
# A tibble: 13 x 3
# Groups: id [2]
# id name condition
# <int> <chr> <chr>
# 1 1 a T
# 2 1 t T
# 3 1 signal T
# 4 1 b C
# 5 1 s C
# 6 1 e C
# 7 1 signal C
# 8 2 x C
# 9 2 signal C
#10 2 r T
#11 2 s T
#12 2 t T
#13 2 signal T
data
df1 <- data.frame(id, name, stringsAsFactors=FALSE)

Answer 3

Another approach could be
id <- rep(1:2,c(7,6))
name <- c('a','t','signal','b','s','e','signal','x','signal','r','s','t','signal')
df <- data.frame(id, name)
library(dplyr)
df %>%
group_by(id) %>%
mutate(FirstSignalIndex=min(which(name=='signal'))) %>%
mutate(condition = ifelse((id %% 2)==0,
ifelse(row_number()>FirstSignalIndex, 'T', 'C'),
ifelse(row_number()>FirstSignalIndex, 'C', 'T')))
Hope this helps!