DataFrame<R, C> Class

public class DataFrame<R, C> : IDataFrame, 
	ISummarizable, IList<DataFrameRow<R, C>>, ICollection<DataFrameRow<R, C>>, 
	IEnumerable<DataFrameRow<R, C>>, IEnumerable

Public Class DataFrame(Of R, C)
	Implements IDataFrame, ISummarizable, IList(Of DataFrameRow(Of R, C)), 
	ICollection(Of DataFrameRow(Of R, C)), IEnumerable(Of DataFrameRow(Of R, C)), 
	IEnumerable

generic<typename R, typename C>
public ref class DataFrame : IDataFrame, 
	ISummarizable, IList<DataFrameRow<R, C>^>, ICollection<DataFrameRow<R, C>^>, 
	IEnumerable<DataFrameRow<R, C>^>, IEnumerable

type DataFrame<'R, 'C> = 
    class
        interface IDataFrame
        interface ISummarizable
        interface IList<DataFrameRow<'R, 'C>>
        interface ICollection<DataFrameRow<'R, 'C>>
        interface IEnumerable<DataFrameRow<'R, 'C>>
        interface IEnumerable
    end

Inheritance

Object  →  DataFrame<R, C>

Implements

IDataFrame, ISummarizable, ICollection<DataFrameRow<R, C>>, IEnumerable<DataFrameRow<R, C>>, IList<DataFrameRow<R, C>>, IEnumerable

Type Parameters

R

The element type of the row index.

C

The element type of the column index.

Use the DataFrame<R, C> type to represent a 2-dimensional collection of possibly heterogeneous data. The rows and columns are indexed by keys of type R and C, respectively. Rows and columns can be accessed through their keys or ordinal position.

Any operation that changes the rows of a data frame always returns a new data frame. Columns can be added and removed from a data frame without creating a new data frame. The values in a column are immutable, so direct modification of data values is not supported.

The columns of a data frame are stored as strongly typed vectors. However, the column types are not part of the type definition of the data frame. This means that the element type of the column must be specified when accessing a column, or an untyped vector is returned as an IVector object. Some care must be taken to specify the correct element type, or an exception may be thrown at runtime.

The fact that the data is stored in columns means that accessing the data is most efficient column-wise. When computing values based on multiple columns, it is better to write the operation in terms of the column vectors than to iterate through the rows of the data frame.

The data frame class supports many data manipulation and transformation operations, including adding and removing columns, selecting rows, structural operations like stacking and creating pivot tables, processing missing values and aggregation. By including the Numerics.NET.DataAnalysis.Linq namespace, LINQ queries are also supported.

Hierarchical row and column indexes are supported. In order to return the proper type of the indexes, some structural operations are defined as extension methods in the static DataFrame class.

Reference