Unquote the Variable Name on the Right Side of Mutate Function in Dplyr

Unquote the variable name on the right side of mutate function in dplyr

I think you have to convert the RHS string to a quosure, which you can do with sym from the rlang package. So use

mutate(dt, !!varname_t1 := lag(!!rlang::sym(varname_t0)))

Then your function will yield

lag1_mutate(df, a, 1)
# [1] "a0"
# [1] "a1"
# # A tibble: 5 x 2
#      a0    a1
#   <int> <int>
# 1     3    NA
# 2     4     3
# 3     1     4
# 4     5     1
# 5     2     5

(You set no seed, so my tibble values are different from yours.)

piping dplyr mutate with unknown variable name

You don't need enquo there. That's for turning a value passed as a parameter into a quosure. Instead you need to turn a string into a symbol. For that you can use as.name() or rlang::sym()

ff <- function(tt){

  # find the variable name
  if(any(colnames(tt)=="AD")){
    vv <- quo(AD)
  } else {
    vv <- colnames(tt) %>% .[.!="f1"]
    vv <- as.name(vv)
  }

  # make the mutate
  tt %>% mutate(!!quo_name(vv) := as.factor(!!vv))      
}

dplyr::mutate unquote RHS

Your code should work as you expect by changing the line where you define qcol to:

qcol <- as.symbol(sprintf('q%i', i))

That is, since qcol was a string, you needed to turn it into a symbol before unquoting for it to be evaluated correctly in your mutate. Also I presume the column you wanted to refer to was the q0 column you defined in your data, not a non-existent column named qval0.

Is there a way to use mutate inside of ones own function?

You can use {{col}} := on left hand side in mutate -

library(dplyr)

collapsevars <- function(var, varcollapse){
  mydata <- mydata %>%
    mutate({{var}} := ifelse(rowSums(
      select(., all_of(varcollapse)) == "Yes") > 0,
      "Yes", "No"))
  mydata
}

collapsevars(afin, avars)

# A tibble: 20 x 6
#    a1    a2    b1    b2       c1 afin 
#   <fct> <fct> <fct> <fct> <dbl> <chr>
# 1 No    Yes   Yes   Yes      10 Yes  
# 2 N/A   N/A   N/A   No       14 No   
# 3 No    No    No    Yes       9 No   
# 4 No    No    N/A   No       14 No   
# 5 No    No    Yes   N/A      10 No   
# 6 No    N/A   N/A   Yes       8 No   
# 7 No    N/A   N/A   Yes      13 No   
# 8 No    N/A   Yes   No        9 No   
# 9 N/A   N/A   Yes   No       11 No   
#10 N/A   N/A   N/A   Yes      11 No   
#11 Yes   Yes   No    Yes       9 Yes  
#12 N/A   N/A   No    No        5 No   
#13 No    N/A   Yes   Yes      10 No   
#14 No    N/A   No    N/A       9 No   
#15 N/A   No    No    Yes       8 No   
#16 No    Yes   Yes   No       10 Yes  
#17 No    N/A   No    No       11 No   
#18 N/A   Yes   No    No       10 Yes  
#19 N/A   N/A   N/A   No        7 No 

Mutate a dynamic column name with conditions using other dynamic column names

use get to retreive column value instead

library(tidyverse)

d <- mtcars %>% tibble
fld_name <-  "mpg"
other_fld_name <- "cyl"

d %>% mutate(!!fld_name := ifelse(get(other_fld_name) < 5 ,NA, get(fld_name)))

#> # A tibble: 32 x 11
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1  21       6  160    110  3.9   2.62  16.5     0     1     4     4
#>  2  21       6  160    110  3.9   2.88  17.0     0     1     4     4
#>  3  NA       4  108     93  3.85  2.32  18.6     1     1     4     1
#>  4  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1
#>  5  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#>  6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#>  7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#>  8  NA       4  147.    62  3.69  3.19  20       1     0     4     2
#>  9  NA       4  141.    95  3.92  3.15  22.9     1     0     4     2
#> 10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
#> # ... with 22 more rows

^{Created on 2021-06-22 by the reprex package (v2.0.0)}

Using quoted variables in a custom dplyr wrapper function

Maybe I don't understand the use case, but why do the columns have to be quoted when you pass them from bar() to foo()? If you unquote the input, everything works as intended:

bar <- function(df, .cols) {
  .cols <- rlang::enquo(.cols)
  mutate(df, foo(!!.cols))      # <--- unquote before passing to foo()
}

# Or alternatively
bar <- function(df, .cols) {mutate(df, foo( {{.cols}} ))}

myiris %>%
  bar(Sepal.Length)             # works

How to iteratively add to a data frame in R using a for-loop?

You were very close with your base R approach. You just needed to:

• remove the assignment by the if. This is because in this base R approach, you're just creating a column and not returning the dataframe.
• refer to data[["x"]] (or data$x) rather than just x in the i=1 case.

Here's a complete working example:

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(stringr)

data <- data.frame(x = 10:15)

for(i in 1:3) {
  x_curnt <- str_c("x_", i)
  x_prior <- str_c("x_",i-1)

  if(i==1){
    data[[x_curnt]] <- data[["x"]] + 1
  } else {
    data[[x_curnt]] <- data[[x_prior]] + 1
  }
}

data
#>    x x_1 x_2 x_3
#> 1 10  11  12  13
#> 2 11  12  13  14
#> 3 12  13  14  15
#> 4 13  14  15  16
#> 5 14  15  16  17
#> 6 15  16  17  18

^{Created on 2022-09-16 by the reprex package (v2.0.1)}

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