seplyr is an attempt to work with the dplyr 0.7.* 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()/seplyr::rename_se(). dplyr::rename() is used as follows.

suppressPackageStartupMessages(library("dplyr"))

datasets::mtcars %>%
  rename(cylinders = cyl, gears = gear) %>%
  head()
##                    mpg cylinders disp  hp drat    wt  qsec vs am gears carb
## Mazda RX4         21.0         6  160 110 3.90 2.620 16.46  0  1     4    4
## Mazda RX4 Wag     21.0         6  160 110 3.90 2.875 17.02  0  1     4    4
## Datsun 710        22.8         4  108  93 3.85 2.320 18.61  1  1     4    1
## Hornet 4 Drive    21.4         6  258 110 3.08 3.215 19.44  1  0     3    1
## Hornet Sportabout 18.7         8  360 175 3.15 3.440 17.02  0  0     3    2
## Valiant           18.1         6  225 105 2.76 3.460 20.22  1  0     3    1

Notice 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)
##         cyl        gear 
## "cylinders"     "gears"

Because 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.

## Loading required package: wrapr
## 
## Attaching package: 'wrapr'
## The following object is masked from 'package:dplyr':
## 
##     coalesce
datasets::mtcars %.>%
  rename_se(., c("cylinders" := "cyl", "gears" := "gear")) %.>%
  head(.)
##                    mpg cylinders disp  hp drat    wt  qsec vs am gears carb
## Mazda RX4         21.0         6  160 110 3.90 2.620 16.46  0  1     4    4
## Mazda RX4 Wag     21.0         6  160 110 3.90 2.875 17.02  0  1     4    4
## Datsun 710        22.8         4  108  93 3.85 2.320 18.61  1  1     4    1
## Hornet 4 Drive    21.4         6  258 110 3.08 3.215 19.44  1  0     3    1
## Hornet Sportabout 18.7         8  360 175 3.15 3.440 17.02  0  0     3    2
## Valiant           18.1         6  225 105 2.76 3.460 20.22  1  0     3    1

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'))
##   b a
## 1 1 2

Please see help("%.>%", package="wrapr") for details on “dot pipe.”