variable based on other variables in R - r

Question

I have a df like this
my_df <- data.frame(
b1 = c(2, 6, 3, 6, 4, 2, 1, 9, NA),
b2 = c(100, 4, 106, 102, 6, 6, 1, 1, 7),
b3 = c(75, 79, 8, 0, 2, 3, 9, 5, 80),
b4 = c(NA, 6, NA, 10, 12, 8, 3, 6, 2),
b5 = c(2, 12, 1, 7, 8, 5, 5, 6, NA),
b6 = c(9, 2, 4, 6, 7, 6, 6, 7, 9),
b7 = c(1, 3, 7, 7, 4, 2, 2, 9, 5),
b8 = c(NA, 8, 4, 5, 1, 4, 1, 3, 6),
b9 = c(4, 5, 7, 9, 5, 1, 1, 2, NA),
b10 = c(14, 2, 4, 2, 1, 1, 1, 1, 5))
I want to create a new column (NEW) which says BLUE or RED based on columns b2 and b3. so, if column b2 is Greater than or equal to 100 0R b3 is Greater than or equal to 75, then input BLUE otherwise input RED.
So that I will have something like this:
my_df <- data.frame(
b1 = c(2, 6, 3, 6, 4, 2, 1, 9, NA),
b2 = c(100, 4, 106, 102, 6, 6, 1, 1, 7),
b3 = c(75, 79, 8, 0, 2, 3, 9, 5, 80),
b4 = c(NA, 6, NA, 10, 12, 8, 3, 6, 2),
b5 = c(2, 12, 1, 7, 8, 5, 5, 6, NA),
b6 = c(9, 2, 4, 6, 7, 6, 6, 7, 9),
b7 = c(1, 3, 7, 7, 4, 2, 2, 9, 5),
b8 = c(NA, 8, 4, 5, 1, 4, 1, 3, 6),
b9 = c(4, 5, 7, 9, 5, 1, 1, 2, NA),
b10 = c(14, 2, 4, 2, 1, 1, 1, 1, 5),
NEW = c("BLUE", "BLUE", "BLUE", "BLUE", "RED", "RED", "RED", "RED", "BLUE"))
I have been able to work this out using this:
library (tidyverse)
greater_threshold <- 99.9
greater_threshold1 <- 74.9
my_df1 <- my_df %>%
mutate(NEW = case_when(b2 > greater_threshold ~ "BLUE",
b3 > greater_threshold1 ~ "BLUE",
+ T~"RED"))
At the moment, you can see that I am setting my 'greater threshold' to be slightly less than the required value. Although it works well. My question is this. Is there a way I set set my 'greater threshold to be ≥ 100 for b2 and ≥ 75 for b3.

Answer 1

For this example, I'd go whit if_else instead of case_when:
library(dplyr)
greater_threshold <- 100
greater_threshold1 <- 75
my_df <- data.frame(
b1 = c(2, 6, 3, 6, 4, 2, 1, 9, NA),
b2 = c(100, 4, 106, 102, 6, 6, 1, 1, 7),
b3 = c(75, 79, 8, 0, 2, 3, 9, 5, 80),
b4 = c(NA, 6, NA, 10, 12, 8, 3, 6, 2),
b5 = c(2, 12, 1, 7, 8, 5, 5, 6, NA),
b6 = c(9, 2, 4, 6, 7, 6, 6, 7, 9),
b7 = c(1, 3, 7, 7, 4, 2, 2, 9, 5),
b8 = c(NA, 8, 4, 5, 1, 4, 1, 3, 6),
b9 = c(4, 5, 7, 9, 5, 1, 1, 2, NA),
b10 = c(14, 2, 4, 2, 1, 1, 1, 1, 5)
)
my_df1 <- my_df %>%
mutate(
NEW = if_else(
b2 >= greater_threshold | b3 >= greater_threshold1,
"BLUE",
"RED"
)
)
my_df1
# b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 NEW
# 1 2 100 75 NA 2 9 1 NA 4 14 BLUE
# 2 6 4 79 6 12 2 3 8 5 2 BLUE
# 3 3 106 8 NA 1 4 7 4 7 4 BLUE
# 4 6 102 0 10 7 6 7 5 9 2 BLUE
# 5 4 6 2 12 8 7 4 1 5 1 RED
# 6 2 6 3 8 5 6 2 4 1 1 RED
# 7 1 1 9 3 5 6 2 1 1 1 RED
# 8 9 1 5 6 6 7 9 3 2 1 RED
# 9 NA 7 80 2 NA 9 5 6 NA 5 BLUE