dplyr + magrittr + qplot = no plot?

Question

I want to use qplot (ggplot2) and then forward the data with magrittr:

This works:

mtcars %>% qplot(mpg, cyl, data=.)

This produces an error:

mtcars %>% qplot(mpg, cyl, data=.) %>% summarise(mean(mpg))

And those produce only summary statistics:

mtcars %T>% qplot(mpg, cyl, data=.) %>% summarise(mean(mpg))
mtcars %>% {qplot(mpg, cyl, data=.); .} %>% summarise(mean(mpg))
mtcars %T>% {qplot(mpg, cyl, data=.)} %>% summarise(mean(mpg))

What is the problem? I already found this solution, but it does not help, as you see from the code attached.

It seems youre passing the ggplot object. Is it possible to apply summarise in the ggplot object? — zelite, Dec 04 '14 at 14:15
but `%T>%` or `%>% {f(.); .}` do not pas the resulting object along but return the imput object (see: http://blog.rstudio.org/2014/12/01/magrittr-1-5/). — Tim, Dec 04 '14 at 14:16
what about: `mtcars %>% {print(qplot(mpg, cyl, data=.)); .} %>% summarise(mean(mpg))` ? is that what you want? Maybe related to: http://cran.r-project.org/doc/FAQ/R-FAQ.html#Why-do-lattice_002ftrellis-graphics-not-work_003f — zelite, Dec 04 '14 at 14:18

score 6 · Accepted Answer · answered Dec 04 '14 at 15:06

6

All ggplot2 functions return an object that represents a plot - to see it you need to print it. That normally happens automatically when you're working in the console, but needs to explicit inside a function or a chain.

The most elegant solution I could come up with is this:

library("ggplot2")
library("magrittr")
library("dplyr")

echo <- function(x) {
  print(x)
  x
}
mtcars %>% 
  {echo(qplot(mpg, cyl, data = .))} %>% 
  summarise(mean(mpg))

It seems like there should be a better way.

answered Dec 04 '14 at 15:06

hadley

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Thanks! It really asks for a better solution since you encourage to combine `magrittr`, `dplyr` and `ggplot2`, and `magritr` 1.5 `%T>$` is less effective if you have to use this kind of tricks to make it work for plotting. – Tim Dec 04 '14 at 15:11
@Tim The example seems forced to me because usually the plot is the last thing in the pipe. – hadley Dec 04 '14 at 15:40
Actually this is real life one (simplified): `get data -> plot summaries -> group and rearrange -> compute some statistics etc.` In this case plot's role was for preliminary data check. – Tim Dec 04 '14 at 16:42
1

A little simpler: `mtcars %T>% { print(qplot(mpg, cyl, data = .)) } %>% summarise(mean(mpg))` or alternatively `mtcars %T>% { summarise(., mean(mpg)) %>% print ; } %>% qplot(mpg, cyl, data = .)`. The latter is more in-line with the comment by @hadley about keeping the plot at the end of the pipe. – r2evans Dec 04 '14 at 18:26
I submitted a feature request to the magritr package at https://github.com/tidyverse/magrittr/issues/140 something like %g>% would probably make this easier. – Jerry T Feb 01 '17 at 16:53

Ruben · Answer 2 · 2016-10-24T07:23:54.663

This seems more clean to me, because it does not require using %T>% (which IMHO makes a pipe harder to re-arrange and read) and no {} around the expression to avoid passing the object there. I'm not sure how much harm there is in passing the object and ignoring it.

I've never had a use for the %T>% tee where I didn't also want to print or plot. And I never wanted to print/plot the object being piped itself (usually a big dataset). So I never use %T>%.

library("ggplot2")
library("dplyr")


pap = function(pass, to_print = NULL, side_effect = NULL) {
  if( !is.null(to_print)) {
    if (is.function(to_print)) {
      print(to_print(pass))
    } else {
      print(to_print)
    }
  }
  side_effect
  invisible(pass)
}

mtcars  %>% 
   pap(summary) %>% 
   pap(side_effect = plot(.)) %>% 
   pap(qplot(mpg, cyl, data = .)) %>% 
   summarise(mean(mpg))

I usually don't use plotting as side-effect in my pipes, so the solution above works best for me (requires "extra typing" for side-effect plot). I'd like to be able to disambiguate between these intended scenarios (e.g. plot vs. qplot) automatically, but haven't found a reliable way.

dplyr + magrittr + qplot = no plot?

2 Answers2

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