Adding .id for pluck

yonicd · March 8, 2018, 5:10pm

@jennybryan Is there a native way in purrr to add an .id to the pluck output so the list objects get named by some other column in the output list elements?

I put together this solution which changes how pluck works a bit, but creates the functionality that seems to be lacking (imo).

In this solution I am assuming .id columns are singletons that can be pasted together

library(purrr)
library(tidyr)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

#create of function copy

  mypluck <- pluck

#add formal for .id columns

  fpluck <- formals(mypluck)
  
  fpluck <-  append(fpluck,list(.id=NULL))
  
  formals(mypluck) <- fpluck

#add to body new .id functionality

  bpluck <- body(mypluck)
  
  bpluck[[2]] <- quote(out <- .Call(extract_impl, .x, dots_splice(...), .default))
  
  bpluck[[3]] <- quote(if(!is.null(.id)) names(out) <- .x[.id]%>%tidyr::unite_('key',.id)%>%pull(key))
  
  bpluck[[4]] <- quote(return(out))

#update new function body

  body(mypluck) <- bpluck

  
  
test_data <- data_frame(id=c(1,2,3),method=c('a','b','c'),x=list(1,2,3))

test_data%>%pluck('x')
#> [[1]]
#> [1] 1
#> 
#> [[2]]
#> [1] 2
#> 
#> [[3]]
#> [1] 3

test_data%>%mypluck('x',.id = c('method'))
#> $a
#> [1] 1
#> 
#> $b
#> [1] 2
#> 
#> $c
#> [1] 3

test_data%>%mypluck('x',.id = c('method','id'))
#> $a_1
#> [1] 1
#> 
#> $b_2
#> [1] 2
#> 
#> $c_3
#> [1] 3

Session info

devtools::session_info()
#> Session info -------------------------------------------------------------
#>  setting  value                       
#>  version  R version 3.3.3 (2017-03-06)
#>  system   x86_64, darwin13.4.0        
#>  ui       X11                         
#>  language (EN)                        
#>  collate  en_US.UTF-8                 
#>  tz       America/New_York            
#>  date     2018-03-08
#> Packages -----------------------------------------------------------------
#>  package    * version    date       source                      
#>  assertthat   0.2.0      2017-04-11 CRAN (R 3.3.2)              
#>  backports    1.1.2      2017-12-13 CRAN (R 3.3.2)              
#>  base       * 3.3.3      2017-03-07 local                       
#>  bindr        0.1        2016-11-13 CRAN (R 3.3.2)              
#>  bindrcpp     0.2        2017-06-17 CRAN (R 3.3.2)              
#>  datasets   * 3.3.3      2017-03-07 local                       
#>  devtools     1.13.5     2018-02-18 CRAN (R 3.3.3)              
#>  digest       0.6.13     2017-12-14 CRAN (R 3.3.2)              
#>  dplyr      * 0.7.4      2017-09-28 CRAN (R 3.3.2)              
#>  evaluate     0.10.1     2017-06-24 CRAN (R 3.3.2)              
#>  glue         1.2.0      2017-10-29 CRAN (R 3.3.2)              
#>  graphics   * 3.3.3      2017-03-07 local                       
#>  grDevices  * 3.3.3      2017-03-07 local                       
#>  htmltools    0.3.6      2017-04-28 CRAN (R 3.3.2)              
#>  knitr        1.18       2017-12-27 CRAN (R 3.3.2)              
#>  magrittr     1.5        2014-11-22 CRAN (R 3.3.0)              
#>  memoise      1.1.0      2017-04-21 CRAN (R 3.3.2)              
#>  methods    * 3.3.3      2017-03-07 local                       
#>  pkgconfig    2.0.1      2017-03-21 CRAN (R 3.3.2)              
#>  purrr      * 0.2.4      2017-10-18 CRAN (R 3.3.2)              
#>  R6           2.2.2      2017-06-17 CRAN (R 3.3.2)              
#>  Rcpp         0.12.14    2017-11-23 CRAN (R 3.3.2)              
#>  rlang        0.2.0      2018-02-20 CRAN (R 3.3.3)              
#>  rmarkdown    1.8        2017-11-17 CRAN (R 3.3.2)              
#>  rprojroot    1.3-2      2018-01-03 CRAN (R 3.3.3)              
#>  stats      * 3.3.3      2017-03-07 local                       
#>  stringi      1.1.6      2017-11-17 CRAN (R 3.3.2)              
#>  stringr      1.2.0      2017-02-18 CRAN (R 3.3.2)              
#>  tibble       1.3.4      2017-08-22 CRAN (R 3.3.2)              
#>  tidyr      * 0.7.2      2017-10-16 CRAN (R 3.3.2)              
#>  tidyselect   0.2.3      2017-11-06 CRAN (R 3.3.2)              
#>  tools        3.3.3      2017-03-07 local                       
#>  utils      * 3.3.3      2017-03-07 local                       
#>  withr        2.1.1.9000 2018-03-03 Github (r-lib/withr@5d05571)
#>  yaml         2.1.16     2017-12-12 CRAN (R 3.3.2)

danr · March 8, 2018, 5:17pm

Please look at the FAQ about name mentioning.

FAQ: Should I @name mention other users in my post? Guides & FAQs

What is @name mentioning? @name mentioning is when you type someone's username with an @ preceding it. Doing this sends a notification to the user. Depending on their settings, it may also send them an email message. For example, with @JacqueHousteauGram in my text, Jacque here will be dynamically notified in community (and via email if he's configured for it). Please don't use this feature excessively In general, it is considered bad form to @name mention someone not otherwise engaged in the conversation. Why should I limit how much I @name mention others? It can be annoying Active people who were being frequently mentioned in topics were first to request that this practice be minimized…

In general asking a particular person to answer your question will not get you an answer any sooner.

yonicd · March 8, 2018, 5:37pm

So you don't have an answer to the actual question in the post?

yonicd · March 8, 2018, 5:46pm

one unintended consequence of no names is the inability to bind after a pluck

test_data <- data_frame(id=c(1,2,3),method=c('a','b','c'),x=list(1,2,3))

test_data%>%pluck('x')
#> [[1]]
#> [1] 1
#> 
#> [[2]]
#> [1] 2
#> 
#> [[3]]
#> [1] 3

test_data%>%pluck('x')%>%bind_cols()
#> Error in cbind_all(x): Not compatible with STRSXP: [type=NULL].

test_data%>%mypluck('x',.id = c('method'))
#> $a
#> [1] 1
#> 
#> $b
#> [1] 2
#> 
#> $c
#> [1] 3

test_data%>%mypluck('x',.id = c('method'))%>%bind_cols()
#> # A tibble: 1 x 3
#>       a     b     c
#>   <dbl> <dbl> <dbl>
#> 1     1     2     3

test_data%>%mypluck('x',.id = c('method','id'))
#> $a_1
#> [1] 1
#> 
#> $b_2
#> [1] 2
#> 
#> $c_3
#> [1] 3

test_data%>%mypluck('x',.id = c('method','id'))%>%bind_cols()
#> # A tibble: 1 x 3
#>     a_1   b_2   c_3
#>   <dbl> <dbl> <dbl>
#> 1     1     2     3

alistaire · March 8, 2018, 8:23pm

Using set_names is more readable:

library(tidyverse)

test_data <- data_frame(id = c(1, 2, 3), 
                        method = c('a', 'b', 'c'), 
                        x = list(1, 2, 3)) 

test_data %>% 
    mutate(x = set_names(x, method)) %>% 
    pull(x)
#> $a
#> [1] 1
#> 
#> $b
#> [1] 2
#> 
#> $c
#> [1] 3

Instead of using bind_cols, use spread:

test_data %>% 
    unite(key, method, id) %>% 
    spread(key, x) %>% 
    unnest()
#> # A tibble: 1 x 3
#>     a_1   b_2   c_3
#>   <dbl> <dbl> <dbl>
#> 1    1.    2.    3.

jennybryan · March 8, 2018, 9:17pm

I haven't digested everything that's above, but note I think I've requested something very related to this.

Therefore this issue thread should be interesting:

github.com/tidyverse/purrr

Named vector from list

opened 11:52PM - 29 Oct 16 UTC

closed 11:35AM - 24 Aug 22 UTC

jennybc

feature vctrs

I frequently want to create a named atomic vector by extracting from a homogeneo…us list: - values = elements extracted via name "foo" - names = elements extracted via name "bar" Here's an example for specific case when target = character vector: ``` r library(purrr) ## install_github("jennybc/repurrrsive") library(repurrrsive) enlist_chr <- function(l, name, value) { nms <- map_chr(l, name) vals <- map_chr(l, value) set_names(vals, nms) } enlist_chr(got_chars[c(1, 3, 10, 29)], "name", "culture") #> Arya Stark Catelyn Stark Theon Greyjoy Varamyr #> "Northmen" "Rivermen" "Ironborn" "Free Folk" ``` Or here's a more general version, used to name the list itself based on contents. ``` r enlist <- function(l, fname, fvalue) { nms <- map_chr(l, as_function(fname)) vals <- map(l, as_function(fvalue)) set_names(vals, nms) } names(got_chars) #> NULL enlist(got_chars[1:4], "name", identity) %>% names() #> [1] "Arya Stark" "Brandon Stark" "Catelyn Stark" "Eddard Stark" ``` Other functions in this space: `enlist_*()` would produce named vector input suitable for the aspirational `mapnm_*()` from #240. It's also related to `tibble::enframe()`, which takes a named vector as input and returns a two-column tibble. An inverse of `tibble::enframe()` has been proposed (https://github.com/tidyverse/tibble/issues/146).

yonicd · March 9, 2018, 1:16pm

both look great (i started with first option before the post). I noted that i would need to mutate all columns i would of liked to pluck, which gets old after a while.

imo it would make my life easier to not have to call 2 or 3 functions instead of just adding an .id param to pluck.

yonicd · March 9, 2018, 1:17pm

interesting thread, thank you for sharing. Did anything come of it in the end?