I would like to dynamically input a variable name using dplyr programming syntax, however, as many have described this can be quite confusing.
I've played around with various combinations of quo/enquo !! etc. to no avail. Here is the simplest form of my code
library(tidyverse)
df <- tibble(
  color1 = c("blue", "blue", "blue", "blue", "blue"),
  color2 = c("black", "black", "black", "black", "black"),
  value = 1:5
)
num <- 2
df %>%
  mutate(color3 = !!(paste0("color", num)))
#> # A tibble: 5 x 4
#>   color1 color2 value color3
#>   <chr>  <chr>  <int> <chr> 
#> 1 blue   black      1 color2
#> 2 blue   black      2 color2
#> 3 blue   black      3 color2
#> 4 blue   black      4 color2
#> 5 blue   black      5 color2
Created on 2018-12-19 by the reprex package (v0.2.1)
Instead I would like to evaluate the quoted input.
#> # A tibble: 5 x 4
#>   color1 color2 value color3
#>   <chr>  <chr>  <int> <chr> 
#> 1 blue   black      1 black 
#> 2 blue   black      2 black 
#> 3 blue   black      3 black 
#> 4 blue   black      4 black 
#> 5 blue   black      5 black
                Describe what the dplyr package in R is used for. Apply common dplyr functions to manipulate data in R. Employ the 'pipe' operator to link together a sequence of functions. Employ the 'mutate' function to apply other chosen functions to existing columns and create new columns of data.
This article will cover the five verbs of dplyr: select, filter, arrange, mutate, and summarize.
select() and rename(): For choosing variables and using their names as a base for doing so.
dplyr aims to provide a function for each basic verb of data manipulation. These verbs can be organised into three categories based on the component of the dataset that they work with: Rows: filter() chooses rows based on column values.
We can use sym from rlang to convert the string to symbol and then evaluate (!!)
library(dplyr)
df %>%
   mutate(color3 = !!(rlang::sym(paste0("color", num))))
# A tibble: 5 x 4
#  color1 color2 value color3
#  <chr>  <chr>  <int> <chr> 
#1 blue   black      1 black 
#2 blue   black      2 black 
#3 blue   black      3 black 
#4 blue   black      4 black 
#5 blue   black      5 black 
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