seplyr is an attempt to work with the
R package through standard evaluation interfaces with a minimum of change and minimum of cognitive friction. Beyond championing standard evaluation it attempts to introduce as few of its own opinions as possible.
A case in point is
dplyr::rename() is used as follows.
suppressPackageStartupMessages(library("dplyr")) datasets::mtcars %>% rename(cylinders = cyl, gears = gear) %>% head()
dplyr::rename() renamings are written as assignments making them very similar to
dplyr::mutate(). This is the reverse from how
R usually handles list or mapping structures.
In named vectors or named lists keys are written on the left and values are written on the right as follows.
mp <- c("cyl" = "cylinders", "gear" = "gears") print(mp)
seplyr is intended to be a set of adapters for
dplyr we simply adopt
dplyr::rename()'s convention. This allows the user to mechanically translate their experience and expectations from scripting over
dplyr::rename() to directly use
seplyr::rename_se() as follows.
library("seplyr") datasets::mtcars %.>% rename_se(., c("cylinders" := "cyl", "gears" := "gear")) %.>% head(.)
We hope this makes it easy to translate one-off analyses into re-usable scripts by incrementally replacing known variable names with parametric versions. The
:= operator is just a convenience function for building up maps, we could also have written
rename_se(c("cylinders" = "cyl", "gears" = "gear")) or passed in a named vector built up elsewhere.
rename_se interprets all left-hand names as new column names and all right-hand names as old column names. This allows
rename_se to be used to swap columns:
data.frame(a = 1, b = 2) %.>% rename_se(., c('a', 'b') := c('b', 'a'))
help("%.>%", package="wrapr") for details on "dot pipe."
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