This code is part of the ML.NET taxi fare prediction demo.

mlnet-taxidemo-loadingcsv.cs

/// <summary>
/// The program class.
/// </summary>
class Program
{
    // file paths to data files
    static readonly string dataPath = Path.Combine(Environment.CurrentDirectory, "yellow_tripdata_2018-12.csv");

    /// <summary>
    /// The main application entry point.
    /// </summary>
    /// <param name="args">The command line arguments.</param>
    static void Main(string[] args)
    {
        // create the machine learning context
        var mlContext = new MLContext();

        // set up the text loader 
        var textLoader = mlContext.Data.CreateTextLoader(
            new TextLoader.Options() 
            {
                Separators = new[] { ',' },
                HasHeader = true,
                Columns = new[] 
                {
                    new TextLoader.Column("VendorId", DataKind.String, 0),
                    new TextLoader.Column("RateCode", DataKind.String, 5),
                    new TextLoader.Column("PassengerCount", DataKind.Single, 3),
                    new TextLoader.Column("TripDistance", DataKind.Single, 4),
                    new TextLoader.Column("PaymentType", DataKind.String, 9),
                    new TextLoader.Column("FareAmount", DataKind.Single, 10)
                }
            }
        );

        // load the data 
        Console.Write("Loading training data....");
        var dataView = textLoader.Load(dataPath);
        Console.WriteLine("done");

        // split into a training and test partition
        var partitions = mlContext.Regression.TrainTestSplit(dataView, testFraction: 0.2);

        // rest of the code goes here...
    }
}