Assign intermediate output to temp variable as part of dplyr pipeline

Question

Q: In an R dplyr pipeline, how can I assign some intermediate output to a temp variable for use further down the pipeline?

My approach below works. But it assigns into the global frame, which is undesirable. There has to be a better way, right? I figured my approach involving the commented line would get the desired results. No dice. Confused why that didn't work.

df <- data.frame(a = LETTERS[1:3], b=1:3)
df %>%
  filter(b < 3) %>%
  assign("tmp", ., envir = .GlobalEnv) %>% # works
  #assign("tmp", .) %>% # doesn't work
  mutate(b = b*2) %>%
  bind_rows(tmp)
  a b
1 A 2
2 B 4
3 A 1
4 B 2

Answer 1

This does not create an object in the global environment:

df %>% 
   filter(b < 3) %>% 
   { 
     { . -> tmp } %>% 
     mutate(b = b*2) %>% 
     bind_rows(tmp) 
   }

This can also be used for debugging if you use . ->> tmp instead of . -> tmp or insert this into the pipeline:

{ browser(); . } %>% 

Answer 2

I often find the need to save an intermediate product in a pipeline. While my use case is typically to avoid duplicating filters for later splitting, manipulation and reassembly, the technique can work well here:

df %>%
  filter(b < 3) %>%
  {. ->> intermediateResult} %>%  # this saves intermediate 
  mutate(b = b*2) %>%
  bind_rows(intermediateResult)    

Answer 3

pipeR is a package that extends the capabilities of the pipe without adding different pipes (as magrittr does). To assign, you pass a variable name, quoted with ~ in parentheses as an element in your pipe:

library(dplyr)
library(pipeR)

df %>>%
  filter(b < 3) %>>%
  (~tmp) %>>% 
  mutate(b = b*2) %>>%
  bind_rows(tmp)
##   a b
## 1 A 2
## 2 B 4
## 3 A 1
## 4 B 2

tmp
##   a b
## 1 A 1
## 2 B 2

While the syntax is not terribly descriptive, pipeR is very well documented.