Use dplyr coalesce in programming
I would like to use dplyr the programming magic new for version 0.7.0 up to coalesce
two columns together. Below I have listed a few of my attempts.
df <- data_frame(x = c(1, 2, NA), y = c(2, NA, 3))
# What I want to do:
mutate(df, y = coalesce(x, y))
# Here the expected output:
#> # A tibble: 3 x 2
#> x y
#> <dbl> <dbl>
#> 1 1 1
#> 2 2 2
#> 3 NA 3
I thought it fn1
would work, but it treats varname
like a character on the right side.
fn1 <- function(varname) {
mutate(df, UQ(varname) := coalesce(x, !!varname))
}
fn1("y")
# Error in mutate_impl(.data, dots) :
# Evaluation error: Argument 2 must be type double, not character.
Another try with enquo
:
fn2 <- function(varname) {
varname <- enquo(varname)
mutate(df, varname := coalesce(x, !!varname))
}
fn2("y") # same error
Maybe I can splice with !!!
instead? (Spoiler alert: I can't.)
fn3 <- function(varname) {
varnames <- c("x", varname)
mutate(df, UQ(varname) := coalesce(!!! varnames))
}
fn3("y")
#> # A tibble: 3 x 2
#> x y
#> <dbl> <chr>
#> 1 1 x
#> 2 2 x
#> 3 NA x
fn4 <- function(varname) {
varnames <- quo(c("x", varname))
mutate(df, UQ(varname) := coalesce(!!! varnames))
}
fn4("y")
# Error in mutate_impl(.data, dots) :
# Column `y` must be length 3 (the number of rows) or one, not 2
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You need to use !!sym
for varname
the right side
library(rlang)
fn1 <- function(varname) {
mutate(df, !!varname := coalesce(x, !!sym(varname)))
}
fn1("y")
# A tibble: 3 x 2
# x y
# <dbl> <dbl>
#1 1 1
#2 2 2
#3 NA 3
Or use UQ
:
fn1 <- function(varname) {
mutate(df, UQ(varname) := coalesce(x, UQ(sym(varname))))
}
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The following two approaches will work.
library(dplyr)
# Define a function to apply coalesce
col_fun1 <- function(df, Cols){
df2 <- df %>%
mutate(y = coalesce(!!!as.list(df %>% select(UQ(Cols)))))
return(df2)
}
# Test the function
col_fun1(df = df, Cols = c("x", "y"))
# A tibble: 3 x 2
x y
<dbl> <dbl>
1 1 1
2 2 2
3 NA 3
Or try this.
# Define a function to apply coalesce
col_fun2 <- function(df, Cols){
df2 <- df %>%
mutate(y = coalesce(!!!as.list(df[, Cols])))
return(df2)
}
# Test the function
col_fun2(df = df, Cols = c("x", "y"))
# A tibble: 3 x 2
x y
<dbl> <dbl>
1 1 1
2 2 2
3 NA 3
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