ndi.fun.table.identifyValidRows
IDENTIFYVALIDROWS Identifies valid rows in a MATLAB table based on specified criteria.
validInd = IDENTIFYVALIDROWS(variableTable)
Checks no specific variables by default. All rows are considered valid unless
checkVariables and invalidValues are provided. This usage returns all true.
validInd = IDENTIFYVALIDROWS(variableTable, checkVariables)
Checks the variables specified in 'checkVariables' for NaN values.
Rows where any of the specified variables contain NaN are marked as invalid.
validInd = IDENTIFYVALIDROWS(variableTable, checkVariables, invalidValues)
Checks the variables in 'checkVariables' against corresponding 'invalidValues'.
INPUT ARGUMENTS:
variableTable: A MATLAB table. Rows typically correspond to observations
and columns to variables.
checkVariables: (Optional) Names of variables within 'variableTable' to be checked.
Can be a character vector, a string scalar, a string array,
or a cell array of character vectors/strings.
Default: {} (empty cell array). If empty, and 'invalidValues'
is also empty or not provided, all rows are marked valid.
invalidValues: (Optional) Specifies the values to be considered invalid for
the corresponding variables in 'checkVariables'.
- If not provided or empty (and 'checkVariables' is provided):
Defaults to checking for NaN in each 'checkVariables'.
- If a single scalar value (numeric, char, string, logical):
This value is treated as the invalid marker for ALL variables
listed in 'checkVariables'.
- If a cell array: Must contain the same number of elements as
'checkVariables'. Each cell 'invalidValues{j}' specifies the
invalid value for the variable 'checkVariables{j}'.
Elements can be numeric (including NaN), char, string, or logical.
OUTPUT ARGUMENTS:
validInd: A logical column vector with the same number of rows as
'variableTable'. 'true' indicates a valid row, 'false'
indicates an invalid row.