Simple Time Series in Visual Basic QuickStart Sample

Illustrates how to perform simple operations on time series data using classes in the Extreme.Statistics.TimeSeriesAnalysis namespace in Visual Basic.

View this sample in: C# F# IronPython

Option Infer On

Imports Extreme.Data.Text
Imports Extreme.DataAnalysis
Imports Extreme.Statistics

    ' Illustrates the use of the TimeSeriesCollection class to represent
    ' and manipulate time series data.
    Module SimpleTimeSeries

        Sub Main()
        ' The license is verified at runtime. We're using
        ' a demo license here. For more information, see
        Extreme.License.Verify("Demo license")

        ' Time series data frames can be created in a variety of ways.
        ' Here we read from a CSV file And specify the column to use as the index
        Dim timeSeries = DelimitedTextFile.ReadDataFrame(Of DateTime)(
                "..\..\..\..\Data\MicrosoftStock.csv", "Date")

        ' The RowCount property returns the number of
        ' observations:
        Console.WriteLine("# observations: {0}", timeSeries.RowCount)

        ' Accessing variables

        ' Variables are accessed by name or numeric index.
        ' They need to be cast to the appropriate specialized
        ' type (NumericalVariable, DateTimeVariable, etc.)
        Dim close = timeSeries("Close").As(Of Double)
        Console.WriteLine("Average close price: ${0:F2}", close.Mean())

        ' Variables can also be accessed by numeric index:
        Console.WriteLine("3rd variable: {0}", timeSeries(2).Name)

        ' The GetSubset method returns the data from the specified range.
        Dim y2004 As DateTime = New DateTime(2004, 1, 1)
        Dim y2005 As DateTime = New DateTime(2005, 1, 1)
        Dim series2004 = timeSeries.GetRows(y2004, y2005)
        Console.WriteLine("Opening price on the first trading day of 2004: {0}",

        ' Transforming the Frequency

        ' The first step is to define the aggregator function
        ' for each variable. This function specifies how each
        ' observation in the new time series is calculated
        ' from the observations in the original series.

        ' The Aggregator class has a number of 
        ' pre-defined aggregator functions:
        Dim allAggregators = New Dictionary(Of String, AggregatorGroup)() From
                {"Open", Aggregators.First},
                {"Close", Aggregators.Last},
                {"High", Aggregators.Max},
                {"Low", Aggregators.Min},
                {"Volume", Aggregators.Sum}

        ' We can specify a subset of the series by providing
        ' the start and end dates.

        ' The TransformFrequency method returns a new series
        ' containing the aggregated data:

        Dim monthlySeries = timeSeries.GetRows(y2004, y2005).
                Resample(Recurrence.Monthly, allAggregators)

        ' We can now print the results:
        Console.WriteLine("Monthly statistics for Microsoft Corp. (MSFT)")

        Console.WriteLine("Press Enter key to continue.")
    End Sub

End Module