Relate function to specific dataset

[Salvardore]

Hello everyone,

I am new to the community so I am not sure if my topic is placed correctly here, but surely you will let me know. My question ist quite simple I guess:

I want to create a custom function that requires the user to first define the data-source (i.e. a tibble) the function is supposed to operate on so that in the subsequent arguments I will only have to name the variable names without having to adress the entire data frame, just as it is the case in classical ggplot2 functions for example:

ggplot(data = my_data,....variable argumentes)

I tried this, but it does not seem to work:

a and b are variables within my_data_frame

• my_data_frame is a random objects such as a tibble*

alpha <- function(data = x, a, b) {
z = a*b
print(z)
}

alpha(data = my_data_frame, a,b)

I hope it is clear what I mean. I am looking forward to your help.

Thanks a Lot
Salvi

[arisp99]

Hey there!

This topic is actually one of the more advanced aspects of R and programming such a function is a bit complex. The underlying principle uses something called data masking. This topic and the more broad topic of metaprogramming are extensively covered in chapters 17-21 of Hadley's Advanced R Book. I would highly recommend reading those chapters to learn more as this topic is too complicated to explain in a couple of lines. An example would look like the following:

suppressMessages(library(dplyr)) # to get starwars dataset
starwars
#> # A tibble: 87 × 14
#>    name     height  mass hair_color skin_color eye_color birth_year sex   gender
#>    <chr>     <int> <dbl> <chr>      <chr>      <chr>          <dbl> <chr> <chr> 
#>  1 Luke Sk…    172    77 blond      fair       blue            19   male  mascu…
#>  2 C-3PO       167    75 <NA>       gold       yellow         112   none  mascu…
#>  3 R2-D2        96    32 <NA>       white, bl… red             33   none  mascu…
#>  4 Darth V…    202   136 none       white      yellow          41.9 male  mascu…
#>  5 Leia Or…    150    49 brown      light      brown           19   fema… femin…
#>  6 Owen La…    178   120 brown, gr… light      blue            52   male  mascu…
#>  7 Beru Wh…    165    75 brown      light      blue            47   fema… femin…
#>  8 R5-D4        97    32 <NA>       white, red red             NA   none  mascu…
#>  9 Biggs D…    183    84 black      light      brown           24   male  mascu…
#> 10 Obi-Wan…    182    77 auburn, w… fair       blue-gray       57   male  mascu…
#> # … with 77 more rows, and 5 more variables: homeworld <chr>, species <chr>,
#> #   films <list>, vehicles <list>, starships <list>

bmi <- function(data, height, weight) {
  height <- rlang::enquo(height)
  weight <- rlang::enquo(weight)
  
  rlang::eval_tidy(weight, data) / (rlang::eval_tidy(height, data) / 100)^2
}

bmi(starwars, height, mass)
#>  [1]  26.02758  26.89232  34.72222  33.33007  21.77778  37.87401  27.54821
#>  [8]  34.00999  25.08286  23.24598  23.76641        NA  21.54509  24.69136
#> [15]  24.72518 443.42857  26.64360  33.95062  39.02663  25.95156  23.35095
#> [22]  35.00000  31.30194  25.21625  25.79592  25.61728        NA        NA
#> [29]  25.82645  26.56250  23.89326  24.67038        NA  17.18034  16.34247
#> [36]        NA        NA        NA  31.88776        NA        NA  26.12245
#> [43]        NA  17.35892  50.92802        NA  24.46460  23.76641  20.91623
#> [50]  22.64681        NA  14.76843        NA        NA  22.63468        NA
#> [57]  24.83565        NA        NA  23.88844  19.44637  18.14487        NA
#> [64]  21.47709        NA  23.58984  19.48696  26.01775  16.78076        NA
#> [71]        NA  24.03461        NA  12.88625        NA  17.99015  34.07922
#> [78]  24.83746  22.35174  15.14960  18.85192        NA        NA        NA
#> [85]        NA        NA  16.52893

^{Created on 2022-04-05 by the reprex package (v2.0.1)}

---

Thankfully, depending on what you want to do, there may be an easier way to accomplish this using base::with():

starwars$height + starwars$mass
#>  [1]  249.0  242.0  128.0  338.0  199.0  298.0  240.0  129.0  267.0  259.0
#> [11]  272.0     NA  340.0  260.0  247.0 1533.0  247.0  290.0   83.0  245.0
#> [21]  261.2  340.0  303.0  256.0  254.0  263.0     NA     NA  108.0  228.0
#> [31]  282.0  281.0     NA  262.0  306.0     NA     NA     NA  152.0     NA
#> [41]     NA  255.0     NA  233.0  139.0     NA  228.0  272.0  280.0  283.0
#> [51]     NA  234.0     NA     NA  268.0     NA  270.0     NA     NA  263.0
#> [61]  226.2  216.0     NA  273.0     NA  262.0  223.0  300.0  317.0     NA
#> [71]     NA   94.0     NA  241.0     NA  235.0  375.0  370.0  267.0  226.0
#> [81]  286.0     NA     NA     NA     NA     NA  210.0

with(starwars, height + mass)
#>  [1]  249.0  242.0  128.0  338.0  199.0  298.0  240.0  129.0  267.0  259.0
#> [11]  272.0     NA  340.0  260.0  247.0 1533.0  247.0  290.0   83.0  245.0
#> [21]  261.2  340.0  303.0  256.0  254.0  263.0     NA     NA  108.0  228.0
#> [31]  282.0  281.0     NA  262.0  306.0     NA     NA     NA  152.0     NA
#> [41]     NA  255.0     NA  233.0  139.0     NA  228.0  272.0  280.0  283.0
#> [51]     NA  234.0     NA     NA  268.0     NA  270.0     NA     NA  263.0
#> [61]  226.2  216.0     NA  273.0     NA  262.0  223.0  300.0  317.0     NA
#> [71]     NA   94.0     NA  241.0     NA  235.0  375.0  370.0  267.0  226.0
#> [81]  286.0     NA     NA     NA     NA     NA  210.0

^{Created on 2022-04-05 by the reprex package (v2.0.1)}