Problem statement

When loading both plyr and dplyr, the last package loaded overwrites symbols exported by the package loaded first:

library(plyr)
library(dplyr)

Currently, the following symbols are affected:

plyr_exports <- ls("package:plyr")
dplyr_exports <- ls("package:dplyr")
(both_exports <- intersect(plyr_exports, dplyr_exports))

## [1] "arrange"   "count"     "desc"      "failwith"  "id"        "mutate"   
## [7] "rename"    "summarise" "summarize"

This means that existing projects that use plyr cannot simply load dplyr using library(dplyr) without potentially breaking existing code. There are workarounds, but all of them seem to have specific disadvantages:

• Load only one of both packages, access functionality from the other package via explicit qualification (e.g., dplyr::summarise).
  • Cumbersome
• Don’t load, always access via explicit qualification
  • Requires extensive code rewriting for existing projects
• Load dplyr after plyr, modify usage of conflicting symbols in the code
  • Doesn’t safeguard new code that attempts to use dplyr primitives with plyr

This document explores alternative solutions.

Analysis

Let’s take a closer look at the interface of the functions exported from both packages:

We can split the overlaps in two groups:

• The first argument is a data frame or table object
• No data frame or table object, but identical formals

body_l %>%
  llply(. %>% { identical(as.character(.$plyr), as.character(.$dplyr)) } ) %>%
  ldply(. %>% data.frame(identical_body = .), .id = "name")

body_l$failwith$plyr

{
  f <- match.fun(f)
  function(...) try_default(f(...), default, quiet = quiet)
}

body_l$failwith$dplyr

{
  function(...) {
    out <- default
    try(out <- f(...), silent = quiet)
    out
}
}

Concept

For fully seamless transition between plyr and dplyr, a compatibility package looks like a possible option. It would provide the union of the exported functions of both packages, and compatibility wrappers for the two functions count and rename that need special attention.

Deprecating the functions count and rename in the plyr package seems simpler. For an even more radical solution, all overlapping functions could be deprecated, referring to identical functionality in dplyr:

• mutate -> dplyr::mutate
  • row names are lost
• summari[sz]e -> dplyr::summari[sz]e
• arrange(df, ...) -> dplyr::arrange(.data, ...)
• count(df, vars, wt_var) -> dplyr::count_(x, vars, wt, sort = FALSE)
  • modified call
  • rename n column to freq
• rename(x, replace, warn_missing) -> dplyr::rename_(.data, replace)
  • replace needs to be massaged
  • warn_missing is always TRUE
• desc(), failwith(), id() -> dplyr::...

Summary

For practical use, a thin compatibility layer seems to work reasonably well for a project that was created using plyr and is now transitioning towards dplyr:

attach(pdlyr::dplyr_compat)

## The following objects are masked from package:dplyr:
## 
##     count, mutate, rename
## 
## The following objects are masked from package:plyr:
## 
##     count, mutate, rename

Tests in the pdlyr package will assure that this package can be safely loaded with warn.conflicts = FALSE. The original plyr implementations can be accessed via shortcuts (prefix p).

A few usage examples:

mtcars %>% mutate(lphkm = 100 * 3.785411784 / 1.609344 / mpg) %>% head

## Warning in mutate(., lphkm = 100 * 3.785411784/1.609344/mpg): Row names
## will be lost

mtcars %>% plyr::mutate(lphkm = 100 * 3.785411784 / 1.609344 / mpg) %>% head

mtcars %>% ddply("cyl", summarize, mean_mpg = mean(mpg))

mtcars %>% ddply("cyl", plyr::summarise, mean_mpg = mean(mpg))

mtcars %>% arrange(-wt) %>% head

mtcars %>% plyr::arrange(-wt) %>% head

mtcars %>% count("gear")

## Warning: 'count' is deprecated.
## Use 'dplyr::count_' instead.
## See help("Deprecated") and help("plyr-deprecated").

mtcars %>% plyr::count("gear")

mtcars %>% rename(list(mpg = "miles_per_gallon")) %>% extract(1:2) %>% head

## Warning: 'rename' is deprecated.
## Use 'dplyr::rename_' instead.
## See help("Deprecated") and help("plyr-deprecated").

mtcars %>% plyr::rename(list(mpg = "miles_per_gallon")) %>% extract(1:2) %>% head

Last changed: 2015-05-27 11:36:17 UTC