Reputation: 9247
My goal is to modify the values of certain columns (chosen through their names) only on a subset of rows that verify a certain condition, using dplyr
.
I have this toy dataframe
library(dplyr)
set.seed(42)
df1 <- data.frame(
Date = rep(seq.Date(as.Date("2020-01-01"), as.Date("2020-01-31"), "day"), each = 24),
A1 = runif(744, min = 0, max = 1000),
A2 = runif(744, min = 0, max = 1000),
B1 = runif(744, min = 0, max = 1000),
B2 = runif(744, min = 0, max = 1000)
)
Let's say I want to multiply by 0.2 the values of the columns that start with the letter "B" only in the rows whose Date
is either 2020-01-01
or 2020-01-06
. The code in this case is pretty simple:
df2 <- df1 %>%
mutate(
B1 = if_else(Date %in% as.Date(c("2020-01-01", "2020-01-06")), 0.2 * B1, B1),
B2 = if_else(Date %in% as.Date(c("2020-01-01", "2020-01-06")), 0.2 * B2, B2)
)
However, if I have a lot of variables starting with the letter "B" I want to do this in an automatic way. I've tried mutate_at
in the following chunk of code
df2 <- df1 %>%
mutate_at(
vars(starts_with("B")),
if_else(Date %in% as.Date(c("2020-01-01", "2020-01-06")), 0.2 * ., .)
)
but R gives me the following error:
Error in Date %in% as.Date(c("2020-01-01", "2020-01-06")) :
object "Date" not found
What am I doing wrong? I've looked at this question but I would like to find a way that does not define a custom function.
Upvotes: 2
Views: 819
Reputation: 2698
See this post for more info
df1 %>%
mutate_at(vars(starts_with("B")),
.funs = list(~ if_else(Date %in% as.Date(c("2020-01-01", "2020-01-06")), 0.2 * ., .)))
Upvotes: 2