When comparing two tbl_df using all.equal(), column and row order is ignored by default, and types are not coerced. The dplyr package is necessary to use this function.

all_equal(target, current, ignore_col_order = TRUE, ignore_row_order = TRUE,
  convert = FALSE, ...)

# S3 method for tbl_df
all.equal(target, current, ...)


target, current

Two data frames to compare.


Should order of columns be ignored?


Should order of rows be ignored?


Should similar classes be converted? Currently this will convert factor to character and integer to double.


Ignored. Needed for compatibility with all.equal().


TRUE if equal, otherwise a character vector describing the reasons why they're not equal. Use isTRUE() if using the result in an if expression.


scramble <- function(x) x[sample(nrow(x)), sample(ncol(x))] mtcars_df <- as_tibble(mtcars) # By default, ordering of rows and columns ignored all.equal(mtcars_df, scramble(mtcars_df))
#> [1] TRUE
# But those can be overriden if desired all.equal(mtcars_df, scramble(mtcars_df), ignore_col_order = FALSE)
#> [1] "Same column names, but different order"
all.equal(mtcars_df, scramble(mtcars_df), ignore_row_order = FALSE)
#> [1] "Same row values, but different order"
# By default all.equal is sensitive to variable differences df1 <- tibble(x = "a") df2 <- tibble(x = factor("a")) all.equal(df1, df2)
#> [1] "Incompatible type for column 'x': x character, y factor"
# But you can request to convert similar types all.equal(df1, df2, convert = TRUE)
#> Warning: joining character vector and factor, coercing into character vector
#> [1] TRUE