I want to mutate multiple columns containing the string "account". Specifically, I want these columns to take "NA" when a certain condition is met, and another value when the condition is not met. Below I present my attempt inspired on here and here. So far, unsuccessful. Still trying, nevertheless any help would be much appreciated.
My data
df<-as.data.frame(structure(list(low_account = c(1, 1, 0.5, 0.5, 0.5, 0.5), high_account = c(16,
16, 56, 56, 56, 56), mid_account_0 = c(8.5, 8.5, 28.25, 28.25,
28.25, 28.25), mean_account_0 = c(31.174, 30.1922101449275, 30.1922101449275,
33.3055555555556, 31.174, 33.3055555555556), median_account_0 = c(2.1,
3.8, 24.2, 24.2, 24.2, 24.2), low_account.1 = c(1, 1, 0.5, 0.5, 0.5,
0.5), high_account.1 = c(16, 16, 56, 56, 56, 56), row.names = c("A001", "A002", "A003", "A004", "A005", "A006"))))
df
low_account high_account mid_account_0 mean_account_0 median_account_0 low_account.1 high_account.1 row.names
1 1.0 16 8.50 31.17400 2.1 1.0 16 A001
2 1.0 16 8.50 30.19221 3.8 1.0 16 A002
3 0.5 56 28.25 30.19221 24.2 0.5 56 A003
4 0.5 56 28.25 33.30556 24.2 0.5 56 A004
5 0.5 56 28.25 31.17400 24.2 0.5 56 A005
6 0.5 56 28.25 33.30556 24.2 0.5 56 A006
My attempt
sample_data<-df%>% mutate_at(select(contains("account") , ifelse(. <= df$low_account& >= df$high_account, NA, .)))
Error: No tidyselect variables were registered Call
rlang::last_error()to see a backtrace
Expected output
df
low_account high_account mid_account_0 mean_account_0 median_account_0 low_account.1 high_account.1 row.names
1 1.0 16 8.50 NA 2.1 1.0 16 A001
2 1.0 16 8.50 NA 3.8 1.0 16 A002
3 0.5 56 28.25 30.19221 24.2 0.5 56 A003
4 0.5 56 28.25 33.30556 24.2 0.5 56 A004
5 0.5 56 28.25 31.17400 24.2 0.5 56 A005
6 0.5 56 28.25 33.30556 24.2 0.5 56 A006
The issue with the vars(contains('account')) is that it matches all the columns where the substring 'account' is present and when we do the logical comparison, the 'low_account' column gets converted to NA because it is definitely lower or equal to 'low_account', thus only that NA replaced column is available. So, instead, we can get the columns of interest 'mid', 'median', 'mean' columns and then do the replace
library(tidyverse)
df %>%
mutate_at(vars(matches("(mid|mean|median)_account")),
~ replace(., .<= low_account | .>= high_account, NA))
# low_account high_account mid_account_0 mean_account_0 median_account_0 low_account.1 high_account.1 row.names
#1 1.0 16 8.50 NA 2.1 1.0 16 A001
#2 1.0 16 8.50 NA 3.8 1.0 16 A002
#3 0.5 56 28.25 30.19221 24.2 0.5 56 A003
#4 0.5 56 28.25 33.30556 24.2 0.5 56 A004
#5 0.5 56 28.25 31.17400 24.2 0.5 56 A005
#6 0.5 56 28.25 33.30556 24.2 0.5 56 A006
来源：https://stackoverflow.com/questions/57043794/how-to-conditionally-mutate-multiple-columns-using-contains-and-ifelse