all_equal: Flexible equality comparison for data frames.

In sctyner/dplyr050: A Grammar of Data Manipulation

Description

You can use all_equal with any data frame, and dplyr also provides tbl_df methods for all.equal.

Usage

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

## S3 method for class 'tbl_df'
all.equal(target, current, ignore_col_order = TRUE,
  ignore_row_order = TRUE, convert = FALSE, ...)

Arguments

target, current	Two data frames to compare.
ignore_col_order	Should order of columns be ignored?
ignore_row_order	Should order of rows be ignored?
convert	Should similar classes be converted? Currently this will convert factor to character and integer to double.
...	Ignored. Needed for compatibility with all.equal.

Value

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.

Examples

scramble <- function(x) x[sample(nrow(x)), sample(ncol(x))]

# By default, ordering of rows and columns ignored
all_equal(mtcars, scramble(mtcars))

# But those can be overriden if desired
all_equal(mtcars, scramble(mtcars), ignore_col_order = FALSE)
all_equal(mtcars, scramble(mtcars), ignore_row_order = FALSE)

# By default all_equal is sensitive to variable differences
df1 <- data.frame(x = "a")
df2 <- data.frame(x = factor("a"))
all_equal(df1, df2)
# But you can request dplyr convert similar types
all_equal(df1, df2, convert = TRUE)

sctyner/dplyr050 documentation built on May 17, 2019, 2:22 p.m.