Using the wizard function

1. Introduction

The wizard() function extracts and sorts unique values of a selected column from a data frame, and optionally pastes into a character string.

For our examples, we will use the mtcars data.

2. Using a symbol argument

wizard(data, col, .collapse = NULL) uses a symbol for its <data-masking> argument col.

mtcars |> wizard(cyl)
#> [1] 4 6 8

This shows sorted unique values of the cyl column of mtcars.

If there is a potentially confounding variable of the same name in the global environment,

(cyl <- c(100:110))
#>  [1] 100 101 102 103 104 105 106 107 108 109 110

…nevertheless, <data-masking> ensures that the col argument of wizard() correctly refers to the cyl column of the mtcars data.

mtcars |> wizard(cyl)
#> [1] 4 6 8

But say there’s a similar variable Cyl in the global environment,

Cyl <- "Bad Luck!"

…and we confuse cyl with Cyl, we obtain an unexpected and puzzling result: -

mtcars |> wizard(Cyl)
#> [1] "Bad Luck!"

3. Using the `.data` pronoun

Using the .data pronoun¹ from the rlang package circumvents this problem by throwing a meaningful error message: -

mtcars |> wizard(.data$cyl)
#> [1] 4 6 8

try(mtcars |> wizard(.data$Cyl))
#> Error in .data$Cyl : Column `Cyl` not found in `.data`.

4. Symbolise and inject

The col argument might be saved as a character variable, for example: -

(col_var <- "cyl")
#> [1] "cyl"

…which needs converting to a symbol and injecting² using the injection operator !! from the rlang package: -

mtcars |> wizard(!!sym(col_var))
#> [1] 4 6 8

Again, if we confuse cyl with Cyl, we obtain an unexpected and confusing result: -

(col_var <- "Cyl")
#> [1] "Cyl"

mtcars |> wizard(!!sym(col_var))
#> [1] "Bad Luck!"

Using data_sym() from rlang circumvents this problem by prefacing the symbol with the data pronoun: -

data_sym(col_var)
#> .data$Cyl

try(mtcars |> wizard(!!data_sym(col_var)))
#> Error in .data$Cyl : Column `Cyl` not found in `.data`.

5. Examples using `lapply()`

(We could also use purrr::map(), but it has no particular advantage here so base lapply() is preferable.)

mtcars |> lapply(wizard, data = mtcars)
#> $mpg
#>  [1] 10.4 13.3 14.3 14.7 15.0 15.2 15.5 15.8 16.4 17.3 17.8 18.1 18.7 19.2 19.7
#> [16] 21.0 21.4 21.5 22.8 24.4 26.0 27.3 30.4 32.4 33.9
#> 
#> $cyl
#> [1] 4 6 8
#> 
#> $disp
#>  [1]  71.1  75.7  78.7  79.0  95.1 108.0 120.1 120.3 121.0 140.8 145.0 146.7
#> [13] 160.0 167.6 225.0 258.0 275.8 301.0 304.0 318.0 350.0 351.0 360.0 400.0
#> [25] 440.0 460.0 472.0
#> 
#> $hp
#>  [1]  52  62  65  66  91  93  95  97 105 109 110 113 123 150 175 180 205 215 230
#> [20] 245 264 335
#> 
#> $drat
#>  [1] 2.76 2.93 3.00 3.07 3.08 3.15 3.21 3.23 3.54 3.62 3.69 3.70 3.73 3.77 3.85
#> [16] 3.90 3.92 4.08 4.11 4.22 4.43 4.93
#> 
#> $wt
#>  [1] 1.513 1.615 1.835 1.935 2.140 2.200 2.320 2.465 2.620 2.770 2.780 2.875
#> [13] 3.150 3.170 3.190 3.215 3.435 3.440 3.460 3.520 3.570 3.730 3.780 3.840
#> [25] 3.845 4.070 5.250 5.345 5.424
#> 
#> $qsec
#>  [1] 14.50 14.60 15.41 15.50 15.84 16.46 16.70 16.87 16.90 17.02 17.05 17.30
#> [13] 17.40 17.42 17.60 17.82 17.98 18.00 18.30 18.52 18.60 18.61 18.90 19.44
#> [25] 19.47 19.90 20.00 20.01 20.22 22.90
#> 
#> $vs
#> [1] 0 1
#> 
#> $am
#> [1] 0 1
#> 
#> $gear
#> [1] 3 4 5
#> 
#> $carb
#> [1] 1 2 3 4 6 8

Here we use setNames() to obtain an eponymously named character vector of the first four mtcar names: -

(carnames <- setNames(nm = names(mtcars))[1:4])
#>    mpg    cyl   disp     hp 
#>  "mpg"  "cyl" "disp"   "hp"

…and use it in three equivalent versions where lapply() uses the .data pronoun ,data_sym() or data_syms() in an anonymous function: -

carnames |> lapply(\(x) wizard(mtcars, .data[[x]]))
#> $mpg
#>  [1] 10.4 13.3 14.3 14.7 15.0 15.2 15.5 15.8 16.4 17.3 17.8 18.1 18.7 19.2 19.7
#> [16] 21.0 21.4 21.5 22.8 24.4 26.0 27.3 30.4 32.4 33.9
#> 
#> $cyl
#> [1] 4 6 8
#> 
#> $disp
#>  [1]  71.1  75.7  78.7  79.0  95.1 108.0 120.1 120.3 121.0 140.8 145.0 146.7
#> [13] 160.0 167.6 225.0 258.0 275.8 301.0 304.0 318.0 350.0 351.0 360.0 400.0
#> [25] 440.0 460.0 472.0
#> 
#> $hp
#>  [1]  52  62  65  66  91  93  95  97 105 109 110 113 123 150 175 180 205 215 230
#> [20] 245 264 335

carnames |> lapply(\(x) wizard(mtcars, !!data_sym(x)))
#> $mpg
#>  [1] 10.4 13.3 14.3 14.7 15.0 15.2 15.5 15.8 16.4 17.3 17.8 18.1 18.7 19.2 19.7
#> [16] 21.0 21.4 21.5 22.8 24.4 26.0 27.3 30.4 32.4 33.9
#> 
#> $cyl
#> [1] 4 6 8
#> 
#> $disp
#>  [1]  71.1  75.7  78.7  79.0  95.1 108.0 120.1 120.3 121.0 140.8 145.0 146.7
#> [13] 160.0 167.6 225.0 258.0 275.8 301.0 304.0 318.0 350.0 351.0 360.0 400.0
#> [25] 440.0 460.0 472.0
#> 
#> $hp
#>  [1]  52  62  65  66  91  93  95  97 105 109 110 113 123 150 175 180 205 215 230
#> [20] 245 264 335

carnames |> data_syms() |> lapply(\(x) wizard(mtcars, !!x))
#> $mpg
#>  [1] 10.4 13.3 14.3 14.7 15.0 15.2 15.5 15.8 16.4 17.3 17.8 18.1 18.7 19.2 19.7
#> [16] 21.0 21.4 21.5 22.8 24.4 26.0 27.3 30.4 32.4 33.9
#> 
#> $cyl
#> [1] 4 6 8
#> 
#> $disp
#>  [1]  71.1  75.7  78.7  79.0  95.1 108.0 120.1 120.3 121.0 140.8 145.0 146.7
#> [13] 160.0 167.6 225.0 258.0 275.8 301.0 304.0 318.0 350.0 351.0 360.0 400.0
#> [25] 440.0 460.0 472.0
#> 
#> $hp
#>  [1]  52  62  65  66  91  93  95  97 105 109 110 113 123 150 175 180 205 215 230
#> [20] 245 264 335

If one of the names is incorrect: -

carnames["cyl"] <- "Cyl"
carnames
#>    mpg    cyl   disp     hp 
#>  "mpg"  "Cyl" "disp"   "hp"

…these all provide meaningful error messages as previously shown: -

try(carnames |> lapply(\(x) wizard(mtcars, .data[[x]])))
#> Error in .data[["Cyl"]] : Column `Cyl` not found in `.data`.

try(carnames |> lapply(\(x) wizard(mtcars, !!data_sym(x))))
#> Error in .data$Cyl : Column `Cyl` not found in `.data`.

try(carnames |> data_syms() |> lapply(\(x) wizard(mtcars, !!x)))
#> Error in .data$Cyl : Column `Cyl` not found in `.data`.

Without the .data pronoun, the error might be easily overlooked: -

carnames |> lapply(\(x) wizard(mtcars, !!sym(x)))
#> $mpg
#>  [1] 10.4 13.3 14.3 14.7 15.0 15.2 15.5 15.8 16.4 17.3 17.8 18.1 18.7 19.2 19.7
#> [16] 21.0 21.4 21.5 22.8 24.4 26.0 27.3 30.4 32.4 33.9
#> 
#> $cyl
#> [1] "Bad Luck!"
#> 
#> $disp
#>  [1]  71.1  75.7  78.7  79.0  95.1 108.0 120.1 120.3 121.0 140.8 145.0 146.7
#> [13] 160.0 167.6 225.0 258.0 275.8 301.0 304.0 318.0 350.0 351.0 360.0 400.0
#> [25] 440.0 460.0 472.0
#> 
#> $hp
#>  [1]  52  62  65  66  91  93  95  97 105 109 110 113 123 150 175 180 205 215 230
#> [20] 245 264 335

carnames |> syms() |> lapply(\(x) wizard(mtcars, !!x))
#> $mpg
#>  [1] 10.4 13.3 14.3 14.7 15.0 15.2 15.5 15.8 16.4 17.3 17.8 18.1 18.7 19.2 19.7
#> [16] 21.0 21.4 21.5 22.8 24.4 26.0 27.3 30.4 32.4 33.9
#> 
#> $cyl
#> [1] "Bad Luck!"
#> 
#> $disp
#>  [1]  71.1  75.7  78.7  79.0  95.1 108.0 120.1 120.3 121.0 140.8 145.0 146.7
#> [13] 160.0 167.6 225.0 258.0 275.8 301.0 304.0 318.0 350.0 351.0 360.0 400.0
#> [25] 440.0 460.0 472.0
#> 
#> $hp
#>  [1]  52  62  65  66  91  93  95  97 105 109 110 113 123 150 175 180 205 215 230
#> [20] 245 264 335

1. Introduction

2. Using a symbol argument

3. Using the .data pronoun

4. Symbolise and inject

5. Examples using lapply()

6. References

3. Using the `.data` pronoun

5. Examples using `lapply()`