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checkmate (version 1.6.1)

checkDataFrame: Check if an argument is a data frame

Description

Check if an argument is a data frame

Usage

checkDataFrame(x, types = character(0L), any.missing = TRUE,
  all.missing = TRUE, min.rows = NULL, min.cols = NULL, nrows = NULL,
  ncols = NULL, row.names = NULL, col.names = NULL)

assertDataFrame(x, types = character(0L), any.missing = TRUE, all.missing = TRUE, min.rows = NULL, min.cols = NULL, nrows = NULL, ncols = NULL, row.names = NULL, col.names = NULL, .var.name)

testDataFrame(x, types = character(0L), any.missing = TRUE, all.missing = TRUE, min.rows = NULL, min.cols = NULL, nrows = NULL, ncols = NULL, row.names = NULL, col.names = NULL)

expect_data_frame(x, types = character(0L), any.missing = TRUE, all.missing = TRUE, min.rows = NULL, min.cols = NULL, nrows = NULL, ncols = NULL, row.names = NULL, col.names = NULL, info = NULL, label = NULL)

Arguments

x
[any] Object to check.
types
[character] Character vector of class names. Each list element must inherit from at least one of the provided types. The types logical, integer, integerish, double, n
any.missing
[logical(1)] Are missing values allowed? Default is TRUE.
all.missing
[logical(1)] Are matricies with only missing values allowed? Default is TRUE.
min.rows
[integer(1)] Minimum number of rows.
min.cols
[integer(1)] Minimum number of columns.
nrows
[integer(1)] Exact number of rows.
ncols
[integer(1)] Exact number of columns.
row.names
[character(1)] Check for row names. Default is NULL (no check). See checkNamed for possible values. Note that you can use checkSubs
col.names
[character(1)] Check for column names. Default is NULL (no check). See checkNamed for possible values. Note that you can use checkS
.var.name
[character(1)] Name for x. Defaults to a heuristic to determine the name using deparse and substitute.
info
[character(1)] Extra information to be included in the message for the testthat reporter. See expect_that.
label
[character(1)] Same as .var.name, but passed down to expect_that.

Value

  • Depending on the function prefix: If the check is successful, all functions return TRUE. If the check is not successful, assertDataFrame throws an error message, testDataFrame returns FALSE, checkDataFrame returns a string with the error message. The function expect_data_frame will return an expectation.

See Also

Other basetypes: assertArray, checkArray, expect_array, testArray; assertAtomicVector, checkAtomicVector, expect_atomic_vector, testAtomicVector; assertAtomic, checkAtomic, expect_atomic, testAtomic; assertCharacter, checkCharacter, expect_character, testCharacter; assertComplex, checkComplex, expect_complex, testComplex; assertEnvironment, checkEnvironment, expect_environment, testEnvironment; assertFactor, checkFactor, expect_factor, testFactor; assertFunction, checkFunction, expect_function, testFunction; assertIntegerish, checkIntegerish, expect_integerish, testIntegerish; assertInteger, checkInteger, expect_integer, testInteger; assertList, checkList, expect_list, testList; assertLogical, checkLogical, expect_logical, testLogical; assertMatrix, checkMatrix, expect_matrix, testMatrix; assertNumeric, checkNumeric, expect_numeric, testNumeric; assertVector, checkVector, expect_vector, testVector

Examples

Run this code
testDataFrame(iris)
testDataFrame(iris, types = c("numeric", "factor"), min.rows = 1, col.names = "named")

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