I am trying to use dplyr's new NSE language approach to create a conditional mutate, using a vector input. Where I am having trouble is setting the column equal to itself, see mwe below:
df <- data.frame("Name" = c(rep("A", 3), rep("B", 3), rep("C", 4)),
"X" = runif(1:10),
"Y" = runif(1:10)) %>%
tbl_df() %>%
mutate_if(is.factor, as.character)
ColToChange <- "Name"
ToChangeTo <- "Big"
Now, using the following:
df %>% mutate( !!ColToChange := ifelse(X >= 0.5 & Y >= 0.5, ToChangeTo, !!ColToChange))
Sets the ColToChange
value to Name
, not back to its original value. I am thus trying to use the syntax above to achieve this:
df %>% mutate( !!ColToChange := ifelse(X >= 0.5 & Y >= 0.5, ToChangeTo, Name))
But instead of Name
, have it be the vector.
You need to use rlang:sym
to evaluate ColToChange
as a symbol Name
first, then evaluate it as a column with !!
:
library(rlang); library(dplyr);
df %>% mutate(!!ColToChange := ifelse(X >= 0.5 & Y >= 0.5, ToChangeTo, !!sym(ColToChange)))
# A tibble: 10 x 3
# Name X Y
# <chr> <dbl> <dbl>
# 1 A 0.05593119 0.3586310
# 2 A 0.70024660 0.4258297
# 3 Big 0.95444388 0.7152358
# 4 B 0.45809482 0.5256475
# 5 Big 0.71348123 0.5114379
# 6 B 0.80382633 0.2665391
# 7 Big 0.99618062 0.5788778
# 8 Big 0.76520307 0.6558515
# 9 C 0.63928001 0.1972674
#10 C 0.29963517 0.5855646