checkDataFrame(x, types = character(0L), any.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,
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,
min.rows = NULL, min.cols = NULL, nrows = NULL, ncols = NULL,
row.names = NULL, col.names = NULL)
x. Defaults to a heuristic to determine
the name using deparse and substitute.logical(1)]
Are missing values allowed? Default is TRUE.integer(1)]
Minimum number of rows.integer(1)]
Minimum number of columns.integer(1)]
Exact number of rows.integer(1)]
Exact number of columns.character(1)]
Check for row names. Default is checkNamed for possible values.character(1)]
Check for column names. Default is checkNamed for possible values.character]
Character vector of class names. Each list element must inherit
from at least one of the provided types.
The types TRUE.
If the check is not successful, assertDataFrame throws an error message,
testDataFrame returns FALSE and checkDataFrame returns
a string with the error message.assertArray,
checkArray, testArray;
assertAtomicVector,
checkAtomicVector,
testAtomicVector;
assertAtomic, checkAtomic,
testAtomic; assertCharacter,
checkCharacter,
testCharacter; assertComplex,
checkComplex, testComplex;
assertEnvironment,
checkEnvironment,
testEnvironment;
assertFactor, checkFactor,
testFactor; assertFunction,
checkFunction, testFunction;
assertIntegerish,
checkIntegerish,
testIntegerish;
assertInteger, checkInteger,
testInteger; assertList,
checkList, testList;
assertLogical, checkLogical,
testLogical; assertMatrix,
checkMatrix, testMatrix;
assertNumeric, checkNumeric,
testNumeric; assertVector,
checkVector, testVectortestDataFrame(iris, "data.frame")
testDataFrame(iris, "data.frame", min.rows = 1, col.names = "named")Run the code above in your browser using DataLab