Generate tidyverse code to replicate data edits

data_code compares an original dataset with an edited version and generates tidyverse-style R code (using dplyr verbs) that transforms the original data into the edited version. The generated code uses rename(), select(), mutate(), slice(), and tibble::add_row() to replicate column renames, column additions/removals, cell value changes, and row additions/removals. When meaningful row names are present (i.e. non-default row names such as those in mtcars), the generated code preserves them using tibble::rownames_to_column() and tibble::column_to_rownames().

Usage

data_code(x, x_edit, name = "data")

Arguments

x

original data prior to editing, a data.frame or matrix. If NULL, creation code will be generated for x_edit.

x_edit

edited data after modifications, a data.frame or matrix.

name

character string for the name of the data object in the generated code, set to "data" by default.

Value

a character string containing tidyverse code that can be printed to the console or written to an R script.

Author

Dillon Hammill, dillon.hammill21@gmail.com

Examples

# original data
x <- data.frame(
  A = c(1, 2, 3),
  B = c("x", "y", "z"),
  stringsAsFactors = FALSE
)

# edited data (changed a value and renamed a column)
x_edit <- data.frame(
  A = c(1, 5, 3),
  Beta = c("x", "y", "z"),
  stringsAsFactors = FALSE
)

# generate code
cat(data_code(x, x_edit, name = "x"))
#> library(dplyr)
#> 
#> x <- x %>%
#>   rename(Beta = B) %>%
#>   mutate(A = replace(A, 2, 5))