![]() # See help("Deprecated") and help("plyr-deprecated"). Mtcars %>% rename( list( mpg = "miles_per_gallon")) %>% extract( 1: 2) %>% head # Warning: 'rename' is deprecated. Mtcars %>% count( "gear") # Warning: 'count' is deprecated. Mtcars %>% plyr:: arrange(-wt) %>% head mpg Mtcars %>% ddply( "cyl", plyr::summarise, mean_mpg = mean(mpg)) cyl Mtcars %>% ddply( "cyl", summarize, mean_mpg = mean(mpg)) cyl The original plyr implementations can be accessed via shortcuts (prefix p).Ī 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 ![]() Tests in the pdlyr package will assure that this package can be safely loaded with nflicts = FALSE. # The following objects are masked from package:plyr: This document explores alternative solutions.įor 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: Doesn’t safeguard new code that attempts to use dplyr primitives with plyr.Load dplyr after plyr, modify usage of conflicting symbols in the code.Requires extensive code rewriting for existing projects.Don’t load, always access via explicit qualification.Have a look at the following R syntax: data > Create tibble with frequencies groupby ( x, y) > summarise ( n n ()) > mutate ( freq n / sum ( n)) summarise () has grouped output by 'x'. Load only one of both packages, access functionality from the other package via explicit qualification (e.g., dplyr::summarise). In order to create a frequency table with the dplyr package, we can use a combination of the groupby, summarise, n, mutate, and sum functions. ![]() There are workarounds, but all of them seem to have specific disadvantages: This means that existing projects that use plyr cannot simply load dplyr using library(dplyr) without potentially breaking existing code. (both_exports <- intersect(plyr_exports, dplyr_exports)) # "arrange" "count" "desc" "failwith" "id" "mutate" ![]() When loading both plyr and dplyr, the last package loaded overwrites symbols exported by the package loaded first: library(plyr)Ĭurrently, the following symbols are affected: plyr_exports <- ls( "package:plyr") ![]()
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