map(_:)

Declaration

func map<T>(_ lazyTransform: @escaping (MLDataTable.Row) -> T) -> MLDataColumn<T> where T : MLDataValueConvertible

Parameters

• lazyTransform:

  A thread-safe row transformation function.

  The implementation of your transform must accept a row from the data table and return a type that conforms to Mldatavalueconvertible.

Return Value

A new MLDataColumn.

Discussion

Use this method to create a new column derived from the existing data in the table. The closure you pass evaluates lazily only when the transformed values are needed for a subsequent operation. Your implementation should accept a data table row and must be thread-safe because the framework may invoke the closure concurrently on unspecified threads.

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For example, to perform the column derivation operation shown above, begin by creating a table of data.

let data: [String: MLDataValueConvertible] = [
    "Day": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
    "Temperature": [91.3, 85.8, 79.5, 83.4, 72.2]
]

var table = try MLDataTable(dictionary: data)

After creating the table, use map(_:) to create a new column of data from the original data. The example closure implementation below is stateless and safe to invoke concurrently on any thread, so no synchronization is necessary.

let derivedColumn = table.map { row -> String in
    guard let day = row["Day"]?.stringValue,
          let temperature = row["Temperature"]?.doubleValue else {
            fatalError("Missing or invalid columns in row.")
    }
    return String(format: "%@ %.1fº", day, temperature)
}

Then use addColumn(_:named:) to add the derived column to a table.

table.addColumn(derivedColumn, named: "Description")