Q:

arguments provided as a list not getting evaluated properly

I am working on a custom function whose goal is to run a function (..f) for all combinations of grouping variables grouping.var provides for a given dataframe and then tidy those results into a dataframe using broom package. 
Here is a custom function I've written. Note that ... are supplied to ..f, while additional arguments for broom::tidy method are supplied via tidy.args list.
# setup
set.seed(123)
library(tidyverse)
options(pillar.sigfig = 8)

# custom function
grouped_tidy <- function(data,
                         grouping.vars,
                         ..f,
                         ...,
                         tidy.args = list()) {
  # check how many variables were entered for grouping variable vector
  grouping.vars <-
    as.list(rlang::quo_squash(rlang::enquo(grouping.vars)))
  grouping.vars <-
    if (length(grouping.vars) == 1) {
      grouping.vars
    } else {
      grouping.vars[-1]
    }

  # quote all argument to `..f`
  dots <- rlang::enquos(...)

  # running the grouped analysis
  df_results <- data %>%
    dplyr::group_by(.data = ., !!!grouping.vars, .drop = TRUE) %>%
    dplyr::group_map(
      .tbl = ., 
      .f = ~ broom::tidy(
        x = rlang::exec(.fn = ..f, !!!dots, data = .x),
        unlist(tidy.args)
    ))

  # return the final dataframe with results
  return(df_results)
}

As shown by examples below, although this function works, I am doubtful the tidy.args list is getting evaluated properly because irrespective of what conf.level I choose, I always get the same results to the 4th decimal place.

95% CI

# using the function to get 95% CI
grouped_tidy(
  data = ggplot2::diamonds,
  grouping.vars = c(cut),
  ..f = stats::lm,
  formula = price ~ carat - 1,
  tidy.args = list(conf.int = TRUE, conf.level = 0.95)
)

#> # A tibble: 5 x 8
#> # Groups:   cut [5]
#>   cut       term   estimate std.error statistic p.value  conf.low conf.high
#>   <ord>     <chr>     <dbl>     <dbl>     <dbl>   <dbl>     <dbl>     <dbl>
#> 1 Fair      carat 4510.7919 42.614474 105.85117       0 4427.2062 4594.3776
#> 2 Good      carat 5260.8494 27.036670 194.58200       0 5207.8454 5313.8534
#> 3 Very Good carat 5672.5054 18.675939 303.73334       0 5635.8976 5709.1132
#> 4 Premium   carat 5807.1392 16.836474 344.91422       0 5774.1374 5840.1410
#> 5 Ideal     carat 5819.4837 15.178657 383.39911       0 5789.7324 5849.2350

99% CI

# using the function to get 99% CI
grouped_tidy(
  data = ggplot2::diamonds,
  grouping.vars = c(cut),
  ..f = stats::lm,
  formula = price ~ carat - 1,
  tidy.args = list(conf.int = TRUE, conf.level = 0.99)
)

#> # A tibble: 5 x 8
#> # Groups:   cut [5]
#>   cut       term   estimate std.error statistic p.value  conf.low conf.high
#>   <ord>     <chr>     <dbl>     <dbl>     <dbl>   <dbl>     <dbl>     <dbl>
#> 1 Fair      carat 4510.7919 42.614474 105.85117       0 4427.2062 4594.3776
#> 2 Good      carat 5260.8494 27.036670 194.58200       0 5207.8454 5313.8534
#> 3 Very Good carat 5672.5054 18.675939 303.73334       0 5635.8976 5709.1132
#> 4 Premium   carat 5807.1392 16.836474 344.91422       0 5774.1374 5840.1410
#> 5 Ideal     carat 5819.4837 15.178657 383.39911       0 5789.7324 5849.2350

Any idea on how I can change the function so that the list of arguments will be evaluated properly by broom::tidy?

A:

set.seed(123)
library(tidyverse)
options(pillar.sigfig = 8)

grouped_tidy <- function(data,
                         grouping.vars,
                         ..f,
                         ...,
                         tidy.args = list()) {

  # functions passed to group_map must accept
  # .x and .y arguments, where .x is the data

  tidy_group <- function(.x, .y) {

    # presumes ..f won't explode if called with these args
    model <- ..f(..., data = .x)

    # mild variation on do.call to call function with
    # list of arguments
    rlang::exec(broom::tidy, model, !!!tidy.args)
  }

  data %>%
    group_by(!!!grouping.vars, .drop = TRUE) %>%
    group_map(tidy_group) %>% 
    ungroup()  # don't get bitten by groups downstream
}

grouped_tidy(
  data = ggplot2::diamonds,

  # wrap grouping columns in vars() like in scoped dplyr verbs
  grouping.vars = vars(cut),  

  ..f = stats::lm,
  formula = price ~ carat - 1,
  tidy.args = list(conf.int = TRUE, conf.level = 0.95)
)
#> # A tibble: 5 x 8
#>   cut       term   estimate std.error statistic p.value  conf.low conf.high
#>   <ord>     <chr>     <dbl>     <dbl>     <dbl>   <dbl>     <dbl>     <dbl>
#> 1 Fair      carat 4510.7919 42.614474 105.85117       0 4427.2062 4594.3776
#> 2 Good      carat 5260.8494 27.036670 194.58200       0 5207.8454 5313.8534
#> 3 Very Good carat 5672.5054 18.675939 303.73334       0 5635.8976 5709.1132
#> 4 Premium   carat 5807.1392 16.836474 344.91422       0 5774.1374 5840.1410
#> 5 Ideal     carat 5819.4837 15.178657 383.39911       0 5789.7324 5849.2350

Created on 2019-02-23 by the reprex package (v0.2.1)

