I want to change a data frame value in my 'type' column to 'H', based on a row-wise condition where any value in a row is greater than or equal to 340.
# make data frame
df <- data.frame(
cell_1 = c(50,10,10,125,110,300,75),
cell_2 = c(0,75,10,70,35,70,85),
cell_3 = c(340,230,10,10,110,10,80),
cell_4 = c(10,75,70,70,35,10,85),
cell_5 = c(0,10,300,125,110,10,75),
type = c('A','A','J','U','S','L','F'),
uniq_Id = c(1,2,3,4,5,6,7)
)
# change 'type' to 'H' if any of the cell values in each row are greater than or equal to 340
apply(df[,1:5], 1, function(i) {
if (any(i >= 340)) {
df$type = 'H'
}
})
Output to the console suggests it's working. However, there's no change in the data frame after the apply function. I want 'type' in row 1 to be 'H'.
cell_1 cell_2 cell_3 cell_4 cell_5 type uniq_Id
1 50 0 340 10 0 A 1
2 10 75 230 75 10 A 2
3 10 10 10 70 300 J 3
4 125 70 10 70 125 U 4
5 110 35 110 35 110 S 5
6 300 70 10 10 10 L 6
7 75 85 80 85 75 F 7
Try any of these. They are non-destructive, i.e. they preserve the input df.
transform(df, type = replace(type, apply(df[1:5] >= 340, 1, any), "H"))
transform(df, type = replace(type, apply(df[1:5], 1, max) >= 340, "H"))
transform(df, type = replace(type, do.call("pmax", df[1:5]) >= 340, "H"))
transform(df, type = replace(type, Reduce(pmax, df[1:5]) >= 340, "H"))
library(dplyr)
df %>%
mutate(type = replace(type, any(pick(starts_with("cell")) >= 340), "H"), .by = uniq_Id)