• Extreme Optimization
  • Features
  • Solutions
  • Documentation
  • QuickStart Samples
  • Sample Applications
  • Downloads
  • Technical Support
  • Download trial
  • How to buy
  • Blog
  • Company
  • Resources
• Documentation
  • Introduction
  • Deployment Guide
  • Nuget packages
  • Configuration
  • Using Parallelism
  • Mathematics Library User's Guide
  • Vector and Matrix Library User's Guide
  • Data Analysis Library User's Guide
  • Statistics Library User's Guide
  • Data Access Library User's Guide
  • Reference
• Reference
  • Extreme
  • Extreme.Collections
  • Extreme.Data
  • Extreme.Data.Json
  • Extreme.Data.Matlab
  • Extreme.Data.R
  • Extreme.Data.Stata
  • Extreme.Data.Text
  • Extreme.DataAnalysis
  • Extreme.DataAnalysis.Linq
  • Extreme.DataAnalysis.Models
  • Extreme.Mathematics
  • Extreme.Mathematics.Algorithms
  • Extreme.Mathematics.Calculus
  • Extreme.Mathematics.Calculus.OrdinaryDifferentialEquations
  • Extreme.Mathematics.Curves
  • Extreme.Mathematics.Curves.Nonlinear
  • Extreme.Mathematics.Distributed
  • Extreme.Mathematics.EquationSolvers
  • Extreme.Mathematics.Generic
  • Extreme.Mathematics.LinearAlgebra
  • Extreme.Mathematics.LinearAlgebra.Implementation
  • Extreme.Mathematics.LinearAlgebra.IterativeSolvers
  • Extreme.Mathematics.LinearAlgebra.IterativeSolvers.Preconditioners
  • Extreme.Mathematics.Optimization
  • Extreme.Mathematics.Optimization.LineSearches
  • Extreme.Mathematics.Random
  • Extreme.Mathematics.SignalProcessing
  • Extreme.Providers
  • Extreme.Providers.InteropServices
  • Extreme.Statistics
  • Extreme.Statistics.Distributions
  • Extreme.Statistics.Multivariate
  • Extreme.Statistics.Tests
  • Extreme.Statistics.TimeSeriesAnalysis
• Extreme.Mathematics
  • AccuracyGoal Structure
  • AlgorithmStatus Enumeration
  • ArrayAttributes Structure
  • ArrayMath Class
  • ArrayMutability Enumeration
  • BigFloat Class
  • BigInteger Structure
  • BigRational Structure
  • CategoricalVector(T) Class
  • Complex(T) Structure
  • Constants Class
  • ConvergenceCriterion Enumeration
  • CoreImplementations(T) Class
  • DecimalMath Class
  • Dimension Enumeration
  • DimensionMismatchException Class
  • DimensionType Enumeration
  • DistributedDataLocation Enumeration
  • DoubleComparer Class
  • Elementary Class
  • ElementType(T) Class
  • FunctionMath Class
  • FunctionWithDerivative Delegate
  • GenericCoreProvider(T) Class
  • GenericImplementations Class
  • ICategoricalVector Interface
  • IDistributed Interface
  • InsufficientDataException Class
  • IntegerMath Class
  • Intent Enumeration
  • Interval Structure
  • Interval(T) Structure
  • IPermutable Interface
  • ISummarizable Interface
  • Iterators Class
  • IVector Interface
  • MachineConstants Class
  • ManagedCoreProviderOfSingle Class
  • Math(T) Class
  • Matrix Class
  • Matrix(T) Class
  • MatrixDiagonal Enumeration
  • MatrixElementOrder Enumeration
  • MatrixExtensions Class
  • MatrixNorm Enumeration
  • MatrixOperationSide Enumeration
  • MatrixStructure Enumeration
  • MatrixTriangle Enumeration
  • MutabilityBehaviour Enumeration
  • NumericsConfiguration Class
  • Operations(T) Class
  • Permutation Class
  • Quad Structure
  • RandomExtensions Class
  • Range Structure
  • RoundingMode Enumeration
  • SingleConstants Class
  • SinglePrecisionImplementations Class
  • Slice Structure
  • SolutionReport(T) Class
  • SolutionReport(T, TError) Class
  • Special Class
  • SummaryOptions Class
  • SymbolicMath Class
  • TotalLossOfPrecisionException Class
  • TransposeOperation Enumeration
  • TypedVectorWrapper(K, T) Structure
  • Vector Class
  • Vector(T) Class
  • VectorExtensions Class
• ICategoricalVector Interface
  • Properties
  • Methods

ICategoricalVector Interface

Extreme Optimization Numerical Libraries for .NET Professional

Represents the common methods and properties for indexed collections that contain categorical data.

Namespace:  Extreme.Mathematics
Assembly:  Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1

Syntax

---

C#

VB

C++

F#

Copy

public interface ICategoricalVector : IVector, 
	IGrouping

Public Interface ICategoricalVector
	Inherits IVector, IGrouping

public interface class ICategoricalVector : IVector, 
	IGrouping

type ICategoricalVector =  
    interface
        interface IVector
        interface IGrouping
    end

The ICategoricalVector type exposes the following members.

Properties

---

	Name	Description
	CategoryIndex	Gets the index containing the categories.
	Count	Gets the number of groups. (Inherited from IGrouping.)
	ElementType	Gets the element type of the vector. (Inherited from IVector.)
	Encoding	Gets or sets the encoding used when creating indicator variables.
	FormatString	Gets a format string used when formatting elements of the vector. (Inherited from IVector.)
	Index	Gets the index of the object. (Inherited from IVector.)
	Length	Gets the length of the vector. (Inherited from IVector.)
	LevelIndexes	Gets a vector that contains the level indexes of the elements.
	Name	Gets the name of the object. (Inherited from IVector.)

Top

Methods

---

	Name	Description
	AggregateIntoT, U(VectorT, AggregatorT, U, VectorU)	Aggregates the specified vector over each group and returns the result. (Inherited from IGrouping.)
	AggregateIntoT, U(VectorT, VectorT, Aggregator2T, U, VectorU)	Aggregates the specified vector over each group and returns the result. (Inherited from IGrouping.)
	Append	Appends a vector at the end of this vector and returns the result. (Inherited from IVector.)
	AppendMissingValues	Appends the specified number of missing values to this vector and returns the result. (Inherited from IVector.)
	AsU	Returns the object as a strongly typed vector of the specified type. (Inherited from IVector.)
	AsCategorical	Converts the vector to a categorical vector. (Inherited from IVector.)
	GetCounts	Returns a histogram of the number of observations in each group. (Inherited from IGrouping.)
	GetIndexes	Gets a sequence of indexes for the grouping. (Inherited from IGrouping.)
	GetSlice	Returns a new object that contains the values at the specified positions. (Inherited from IVector.)
	GetValue	Gets the value at the specified index. (Inherited from IVector.)
	GetValues(IEnumerableInt32)	Returns a new object that contains the values at the specified positions. (Inherited from IVector.)
	GetValues(Int32)	Returns a new object that contains the values at the specified positions. (Inherited from IVector.)
	IsMissing	Indicates whether the value at the specified index is missing. (Inherited from IVector.)
	Protect	Returns a shallow read-only copy of the vector. (Inherited from IVector.)
	ReplaceMissingValues	Replaces all missing values in a vector with the previous or next non-missing value. (Inherited from IVector.)
	Sort	Returns a permutation that can be used to sort the data in the vector in the specified order. (Inherited from IVector.)
	WithCategoriesT	Constructs a new categorical vector using the specified category index.

Top

Extension Methods

---

	Name	Description
	BinT(IntervalIndexT)	Overloaded. Sorts values into bins and returns the result as a categorical vector. (Defined by Vector.)
	BinT(IListT, SpecialBins)	Overloaded. Sorts values into bins and returns the result as a categorical vector. (Defined by Vector.)
	CreateHistogram	Returns a histogram of the counts for each value in a vector. (Defined by Histogram.)
	UnstackR, C	Transforms a vector with a two-level index into a data frame whose columns correspond to the second level in the index. (Defined by DataFrame.)
	UseBackwardDifferenceEncoding	Specifies that backward difference encoding should be used when creating indicator variables. (Defined by VectorExtensions.)
	UseDeviationEncoding	Specifies that deviance encoding should be used when creating indicator variables. (Defined by VectorExtensions.)
	UseDummyEncoding	Specifies that dummy encoding (also called treatment encoding) should be used when creating indicator variables. (Defined by VectorExtensions.)
	UseForwardDifferenceEncoding	Specifies that forward difference encoding should be used when creating indicator variables. (Defined by VectorExtensions.)
	UseHelmertEncoding	Specifies that Helmert encoding should be used when creating indicator variables. (Defined by VectorExtensions.)
	UseInverseHelmertEncoding	Specifies that inverse Helmert encoding should be used when creating indicator variables. (Defined by VectorExtensions.)
	UsePolynomialEncoding	Specifies that orthogonal polynomial encoding should be used when creating indicator variables. (Defined by VectorExtensions.)
	UseSimpleEncoding	Specifies that simple encoding should be used when creating indicator variables. (Defined by VectorExtensions.)

Top

See Also

---

Reference

Extreme.Mathematics Namespace

Copyright © 2004-2021, Extreme Optimization. All rights reserved.
Extreme Optimization, Complexity made simple, M#, and M Sharp are trademarks of ExoAnalytics Inc.
Microsoft, Visual C#, Visual Basic, Visual Studio, Visual Studio.NET, and the Optimized for Visual Studio logo
are registered trademarks of Microsoft Corporation.