working with lists of models using the pipe syntax

Question

I often like to fit and examine multiple models that relate two variables in an R dataframe.

I can do that using syntax like this:

require(tidyverse)
require(broom)
models <- list(hp ~ exp(cyl), hp ~ cyl)
map_df(models, ~tidy(lm(data=mtcars, formula=.x)))

But I'm used to the pipe syntax and was hoping to be able to something like this:

mtcars %>% map_df(models, ~tidy(lm(data=., formula=.x)))

That makes it clear that I'm "starting" with mtcars and then doing stuff to it to generate my output. But that syntax doesn't work, giving an error Error: Index 1 must have length 1.

Is there a way to write my purrr:map() function in a way that I can pipe mtcars into it to get the same output as the working code above? I.e.

mtcars %>% <<<something>>>

Answer 1

tl/dr: mtcars %>% {map_df(models, function(.x) tidy(lm(data=., formula=.x)))}

Or mtcars %>% map_df(models, ~tidy(lm(..1,..2)), ..2 = .)

---

There are 2 problems with the solution you've tried.

The first is that you need to use curly braces if you want to place the dot in an unusual place.

library(magrittr)
1 %>% divide_by(2)   # 0.5     -> this works
1 %>% divide_by(2,.) # 2       -> this works as well
1 %>% divide_by(2,mean(.,3))   #  this doesn't    
1 %>% divide_by(.,2,mean(.,3)) #  as it's equivalent to this one
1 %>% {divide_by(2,mean(.,3))} #  but this one works as it forces all dots to be explicit.

The second is that you can't use the dot with the ~ formulation in the way you intended, try map(c(1,2), ~ 3+.) and map(c(1,2), ~ 3+.x) (or even map(c(1,2), ~ 3+..1)) and you'll see you get the same result. By the time you use the dot in a ~ formula it's not linked to the pipe function anymore.

To make sure the dot is interpreted as mtcars you need to use the good old function(x) ... definition.

This works:

mtcars %>% {map_df(models, function(.x) tidy(lm(data=., formula=.x)))}

Finally, as a bonus, here's what I came up with, trying to find a solution without curly braces :

mtcars %>% map(models,lm,.) %>% map_df(tidy)
mtcars %>% map_df(models, ~tidy(lm(..1,..2)), ..2 = .)