ICategoricalVector Interface

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

Definition

Namespace: Numerics.NET
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.1.5
C# 
public interface ICategoricalVector : IVector, 
	IGrouping
Implements
IGrouping, IVector

Properties

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)
Preliminary
Length Gets the length of the vector.
(Inherited from IVector)
LevelIndexes Gets a vector that contains the level indexes of the elements.
LevelIndexesSpan Gets a vector that contains the level indexes of the elements.
Name Gets the name of the object.
(Inherited from IVector)
Preliminary

Methods

AggregateInto<T, TResult>(Vector<T>, Aggregator<T, TResult>, Vector<TResult>) Aggregates the specified vector over each group and returns the result.
(Inherited from IGrouping)
AggregateInto<T1, T2, TResult>(Vector<T1>, Vector<T2>, BinaryAggregator<T1, T2, TResult>, Vector<TResult>) Aggregates the specified vector over each group and returns the result.
(Inherited from IGrouping)
AggregateInto<T, TResult, TPredicate>(Vector<T>, Aggregator<T, TResult>, TPredicate, Nullable<Boolean>, Vector<TResult>) Aggregates the specified vector over each group and returns the result.
(Inherited from IGrouping)
AggregateInto<T, TResult, TPredicate>(Aggregator<T, TResult>, Int32, ReadOnlySpanSlice<T>, TPredicate, Boolean, SpanSlice<TResult>) 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)
As<U> 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(IEnumerable<Int32>) 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)
WithCategories<T> Constructs a new categorical vector using the specified category index.

Extension Methods

Bin<T> Sorts values into bins and returns the result as a categorical vector.
(Defined by Vector)
Bin<T> 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)
Unstack<R, 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)

See Also