Extreme Optimization™: Complexity made simple.

Math and Statistics
Libraries for .NET
  • Home
  • Features
    • Math Library
    • Vector and Matrix Library
    • Statistics Library
    • Performance
    • Usability
  • Documentation
    • Introduction
    • Math Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Reference
  • Resources
    • Downloads
    • QuickStart Samples
    • Sample Applications
    • Frequently Asked Questions
    • Technical Support
  • Order
  • Company
    • About us
    • Testimonials
    • Customers
    • Press Releases
    • Careers
    • Partners
    • Contact us
Introduction
Deployment Guide
Nuget packages
Configuration
Using Parallelism
Expand Mathematics Library User's GuideMathematics Library User's Guide
Expand Vector and Matrix Library User's GuideVector and Matrix Library User's Guide
Expand Data Analysis Library User's GuideData Analysis Library User's Guide
Expand Statistics Library User's GuideStatistics Library User's Guide
Expand Data Access Library User's GuideData Access Library User's Guide
Expand ReferenceReference
  • 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.DataAnalysis
    • Accumulator(T, U) Class
    • Aggregator(T, U) Class
    • Aggregator2(T, U) Class
    • Aggregator2Group Class
    • Aggregator2Group(T) Class
    • AggregatorGroup Class
    • AggregatorGroup(T) Class
    • Aggregators Class
    • BoundaryIntervalBehavior Enumeration
    • CategoricalEncoding Class
    • DataFrame Class
    • DataFrame(R, C) Class
    • DataFrameRow(R, C) Class
    • DateTimeExtensions Class
    • DateTimeUnit Enumeration
    • Direction Enumeration
    • Grouping Class
    • Grouping(TKey) Class
    • Histogram Class
    • Histogram(T) Class
    • IAccumulator(T, U) Interface
    • IAccumulator2(T, U) Interface
    • IAccumulator2(T, U, V) Interface
    • IAggregator Interface
    • IAggregator(T) Interface
    • IAggregator2 Interface
    • IAggregator2(T) Interface
    • IDataFrame Interface
    • IGrouping Interface
    • IIndex Interface
    • Index Class
    • Index(T) Class
    • IntervalIndex(T) Class
    • IPivot Interface
    • JoinIndex Class
    • JoinType Enumeration
    • MissingValueAction Enumeration
    • MissingValueException Class
    • MultipleMissingValueAction Enumeration
    • Parameter(T) Class
    • ParameterVector(T) Class
    • Pivot Class
    • Pivot(R, C) Class
    • RankTiebreaker Enumeration
    • Recurrence Class
    • SortOrder Enumeration
    • SpecialBins Enumeration
    • Subset Class
    • TransformedParameter(T) Class
    • TypePreservingAggregatorGroup Class
    • VectorExtensions Class
  • Pivot Class
    • Pivot Constructor
    • Properties
    • Methods
  • Methods
    • AggregateInto Method Overloads
    • CountsMatrix Method
    • GetCounts Method
    • GetIndexes Method Overloads
  • GetCounts Method

PivotGetCounts Method

Extreme Optimization Numerical Libraries for .NET Professional
Returns a histogram of the number of observations in each group.

Namespace:  Extreme.DataAnalysis
Assembly:  Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
Syntax
C#
VB
C++
F#
Copy
public Vector<double> GetCounts()
Public Function GetCounts As Vector(Of Double)
public:
virtual Vector<double>^ GetCounts() sealed
abstract GetCounts : unit -> Vector<float> 
override GetCounts : unit -> Vector<float>

Return Value

Type: VectorDouble
A vector containing the number of observations in each group.

Implements

IGroupingGetCounts
See Also

Reference

Pivot Class
Extreme.DataAnalysis Namespace

Copyright (c) 2004-2021 ExoAnalytics Inc.

Send comments on this topic to support@extremeoptimization.com

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.