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QuickStart Samples

Manipulating Columns QuickStart Sample (C#)

Illustrates how to transform and manipulate the columns of a data frame in C#.

View this sample in: Visual Basic F#

using System;
using System.Collections.Generic;

using Extreme.Mathematics;
using Extreme.DataAnalysis;

using Index = Extreme.DataAnalysis.Index;

namespace Extreme.Numerics.QuickStart.CSharp
    /// <summary>
    /// Illustrates how to transform and manipulate the columns
    /// of a data frame.
    /// </summary>
    class ManipulatingColumns

        static void Main(string[] args)
            // The license is verified at runtime. We're using
            // a demo license here. For more information, see
            Extreme.License.Verify("Demo license");

            // Let's start with a data frame with a DateTime index:
            int rowCount = 1000;
            var dates = Index.CreateDateRange(new DateTime(2016, 01, 17), rowCount, Recurrence.Daily);
            var frame = DataFrame.FromColumns(new Dictionary<string, object>() {
                    { "values1", Vector.CreateRandom(rowCount) },
                    { "values2", Vector.CreateRandom(rowCount) },
                    }, dates);

            // The columns of a data frame are immutable,
            // but the collection of columns is not.

            // We can add columns:
            frame.AddColumn("vzlues3", Vector.CreateRandom(rowCount));
            frame.AddColumn("values4", Vector.CreateRandom(rowCount));
            frame.AddColumn("values6", Vector.CreateRandom(rowCount));
            // Rename columns:
            frame.RenameColumn("values4", "vzlues5");
            frame.RenameColumns(s => s.StartsWith("vzlues"), s => "values" + s.Substring(6));
            // And remove columns:

            // You can transform a column and add the result 
            // in various places:
            // As the last column:
            frame.MapAndAppend<double>("values1", x => Vector.Cos(x), "cosValues1");
            // After a specific column:
            frame.MapAndInsertAfter<double>("values1", x => Vector.Sin(x), "sinValues1");
            // Replacing the column
            frame.MapAndReplace<double>("values6", x => Vector.Exp(x), "expValues6");

            // The same operations can be performed on multiple columns
            // at once:
            var columns = new[] { "values1", "values2" };
            // We can supply the keys for the new columns explicitly:
            var negColumns = new[] { "-values1", "-values2" };
            frame.MapAndAppend<double>(columns, x => -x, negColumns);
            // or as a function of the original key:
            frame.MapAndInsertAfter<double>(columns, x => 2.0 * x, s => "2*" + s);

            // A more complex example: replace missing values
            // with the mean of a group.

            // We create a categorical variable with 5 categories
            // so we will have 5 group means.
            var group = frame.GetColumn("values1").Bin(5);
            // and a variable that has some missing values:
            var withNAs = frame.GetColumn("values2").Clone()
                .SetValues(double.NaN, x => x < 0.15);
            // Note that, since columns are immutable, we have to 
            // make a clone before we can set values.
            Console.WriteLine(withNAs.GetSlice(0, 12));

            // Now for the actual calculation, which has 3 steps:
            // First, we compute the means for each group:
            var meansPerGroup = withNAs.AggregateBy(group, Aggregators.Mean);

            // Next, create a vector with the means of the group
            // that each element belongs to:
            var means = group.WithCategories(meansPerGroup);
            // Next, we replace the missing values with the corresponding
            // elements from that vector.
            var withNAsReplaced = withNAs.ReplaceMissingValues(means);

            // Row-based operations

            // Data frames are column-based data structures.
            // Even though it is not recommended, it is possible
            // to perform operations on rows:

            frame.AddColumn("values3", Vector.CreateRandom(rowCount));
            var avg1 = Vector.Create<double>(frame.RowCount);
            int i = 0;
            foreach (var row in frame.Rows)
                avg1[i] = (row.Get<double>("values1")
                        + row.Get<double>("values2")
                        + row.Get<double>("values3")) / 3;
            frame.AddColumn("Average", avg1);

            // Performing the operation directly on the columns
            // is much more efficient:
            var avg2 = (frame.GetColumn("values1")
                     + frame.GetColumn("values2")
                     + frame.GetColumn("values3")) / 3.0;
            frame.AddColumn("Average2", avg2);

            Console.Write("Press any key to exit.");