Mutate with str_detect only if condition is true - r

Question

Im trying to use str_detect to mutate only if the column "RedColor" is "1".
I have a dataset test which looks like this:
# id RedColor Color_Number
#1 1 1 1
#2 2 0 1
#3 3 1 3
#4 4 1 2
#5 6 0 2
#6 8 1 6
I tried the filter function but it returns me only a filtered dataset with all other cases with RedColor = "0" removed.
test <- test %>%
filter(RedColor==TRUE) %>%
mutate(DarkRed = str_detect(Color_Number, "1|2"))
Im expecting an output with the new column DarkRed = "1" in all cases with RedColor = 1 and 1 or 2 in column Color_Number.
# id RedColor Color_Number Dark_Red
#1 1 1 1 1
#2 2 0 1 0
#3 3 1 3 0
#4 4 1 2 1
#5 6 0 2 0
#6 8 1 6 0
Thank you!

Answer 1

Using base R
transform(df, Dark_Red = +(RedColor == 1& Color_Number %in% 1:2))
id RedColor Color_Number Dark_Red
1 1 1 1 1
2 2 0 1 0
3 3 1 3 0
4 4 1 2 1
5 6 0 2 0
6 8 1 6 0
data
df <- structure(list(id = c(1L, 2L, 3L, 4L, 6L, 8L), RedColor = c(1L,
0L, 1L, 1L, 0L, 1L), Color_Number = c(1L, 1L, 3L, 2L, 2L, 6L)), row.names = c(NA,
-6L), class = "data.frame")

Answer 2

Update on OP's request (see comments):
With this dataframe:
id RedColor Color_Number
1 1 1 one
2 2 0 one
3 3 1 three
4 4 1 two
5 6 0 two
6 8 1 six
you could use this code:
library(dplyr)
df %>%
mutate(Dark_Red = ifelse(
RedColor == 1 & Color_Number == "one" | Color_Number == "two", 1, 0))
Output:
id RedColor Color_Number Dark_Red
1 1 1 one 1
2 2 0 one 0
3 3 1 three 0
4 4 1 two 1
5 6 0 two 1
6 8 1 six 0
First answer:
We could use ifelse
str_detect is not appropriate as Ronak already explained:
library(dplyr)
df %>%
mutate(Dark_Red = ifelse(
RedColor == 1 & Color_Number == 1 | Color_Number == 2, 1, 0))
Output:
id RedColor Color_Number Dark_Red
1 1 1 1 1
2 2 0 1 0
3 3 1 3 0
4 4 1 2 1
5 6 0 2 1
6 8 1 6 0

Answer 3

For exact matches don't perform regex match. str_detect is used for pattern matching. Use %in% to match multiple values.
library(dplyr)
df <- df %>% mutate(Dark_Red = as.integer(RedColor == 1 & Color_Number %in% 1:2))
df
# id RedColor Color_Number Dark_Red
#1 1 1 1 1
#2 2 0 1 0
#3 3 1 3 0
#4 4 1 2 1
#5 6 0 2 0
#6 8 1 6 0
If you want to write this in base R use transform -
df <- transform(df, Dark_Red = as.integer(RedColor == 1 & Color_Number %in% 1:2))
data
df <- structure(list(id = c(1L, 2L, 3L, 4L, 6L, 8L), RedColor = c(1L,
0L, 1L, 1L, 0L, 1L), Color_Number = c(1L, 1L, 3L, 2L, 2L, 6L)),
row.names = c(NA, -6L), class = "data.frame")

Answer 4

you can use ifelse inside the mutate call instead of filtering:
test <- test %>%
mutate(Darkred=ifelse((RedColor==TRUE & Color_Number %in% 1:2), 1,0))
> test
# A tibble: 10 × 4
id RedColor Color_Number Darkred
<int> <int> <int> <dbl>
1 1 1 2 1
2 2 1 2 1
3 3 1 3 0
4 4 1 3 0
5 5 0 4 0
6 6 0 2 0
7 7 1 3 0
8 8 1 4 0
9 9 0 5 0
10 10 0 3 0
Data:
test<-data_frame(id=1:10,
RedColor=rbinom(10,1,0.5),
Color_Number=sample(1:5,10,TRUE,rep(.2,5)))