Deprecation Warning Use DataSource instead of MLDataTable when initializing in Create ML

I am running the following code in Xcode 14.3 Playgrounds. I am using macOS Ventura 13.1.

let csvFile = Bundle.main.url(forResource: "all-data", withExtension: "csv")!
let dataTable = try MLDataTable(contentsOf: csvFile)


let (classifierEvaluationTable, classifierTrainingTable) = dataTable.randomSplit(by: 0.20, seed: 5)

let classifier = try MLTextClassifier(trainingData: classifierTrainingTable, textColumn: "text", labelColumn: "sentiment")

I get the following warning:

'init(trainingData:textColumn:labelColumn:parameters:)' was deprecated in macOS 13.0: Use DataSource instead of MLDataTable when initializing.

The problem is that there is no documentation on how to create DataFrame or DataSource.

Handling some time on that case. We can use DataFrame, so the warnings will avoid. At this time it's not deprecated.

There is an example, what I found how to rewrite this.

Previous version:

let csvFile = Bundle.main.url(forResource: "all-data", withExtension: "csv")!
let dataTable = try MLDataTable(contentsOf: csvFile)


let (classifierEvaluationTable, classifierTrainingTable) = dataTable.randomSplit(by: 0.20, seed: 5)

let classifier = try MLTextClassifier(trainingData: classifierTrainingTable, textColumn: "text", labelColumn: "sentiment")

Updated:

additionally add this

import TabularData

let csvFile = Bundle.main.url(forResource: "all-data", withExtension: "csv")!
let dataFrame = DataFrame(contentsOfCSVFile: csvFile)

let (classifierEvaluationSlice, classifierTrainingSlice) = dataFrame.split(by: 0.20, seed: 5)


let classifierTrainingFrame = DataFrame(classifierTrainingSlice)
let classifier = try MLTextClassifier(trainingData: classifierEvaluationFrame, textColumn: "text", labelColumn: "sentiment"))

Additionally we can compare & print metrics and save file:

let classifierEvaluationFrame = DataFrame(classifierEvaluationSlice)
let metrics = model.evaluation(on: classifierEvaluationFrame, textColumn: "text", labelColumn: "sentiment"))
print(metrics.classificationError)
    
let modelPath = URL(filePath: "YourPath/YourModelName.mlmodel")
try model.write(to: modelPath)