I have the following data frame:
df <- data.frame(id=1:56,
x_1 = runif(56), x_2 = runif(56), x_3 = runif(56),
x_4 = runif(56))
I am trying to add a value (let’s say 0.5) to a new column of this df if id is equal to any of the following numbers: 1:27, 32, 44:50, 54, 55, 56, and then add another value (let’s say 0.4) to all of the remaining rows that have an id value not included in the aforementioned range. Then I will multiply each other cell in the row by these new values.
I know I can do this with an ifelse or mutate statement, but that would require typing out each individual number that id could be equal to which I’m hoping is unnecessary.
Any help would be appreciated!
>Solution :
A suggestion using dplyr:
library(dplyr)
IDs <- c(1:27, 32, 44:50, 54, 55, 56)
set.seed(42)
df <- data.frame(id=1:56,
# x_1 = runif(56), x_2 = runif(56), x_3 = runif(56),
# x_4 = runif(56))
IDs <- c(1:27, 32, 44:50, 54, 55, 56)
We can first assign multi to be one of 0.4 or 0.5 based on the id:
tibble(df) %>%
mutate(multi = if_else(id %in% IDs, 0.5, 0.4)) %>%
tail()
# # A tibble: 6 x 6
# id x_1 x_2 x_3 x_4 multi
# <int> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 51 0.333 0.740 0.602 0.547 0.4
# 2 52 0.347 0.733 0.197 0.893 0.4
# 3 53 0.398 0.536 0.535 0.490 0.4
# 4 54 0.785 0.00227 0.180 0.172 0.5
# 5 55 0.0389 0.609 0.452 0.543 0.5
# 6 56 0.749 0.837 0.317 0.961 0.5
From this, we can easily multiple that value against a subset of columns using dplyr::across.
tibble(df) %>%
mutate(multi = if_else(id %in% IDs, 0.5, 0.4)) %>%
mutate(across(x_1:x_4, ~ multi * .)) %>%
tail
# # A tibble: 6 x 6
# id x_1 x_2 x_3 x_4 multi
# <int> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 51 0.133 0.296 0.241 0.219 0.4
# 2 52 0.139 0.293 0.0788 0.357 0.4
# 3 53 0.159 0.214 0.214 0.196 0.4
# 4 54 0.392 0.00114 0.0898 0.0858 0.5
# 5 55 0.0195 0.304 0.226 0.272 0.5
# 6 56 0.374 0.418 0.159 0.481 0.5
The two steps could be combined into a single mutate. They could even be combined into a single assignment without it if you no longer need multi around.